Repository: Ao-Lee/Vgg-Face-Fine-tune
Branch: master
Commit: 6d254964dc39
Files: 32
Total size: 343.7 KB

Directory structure:
gitextract_5eh4rqbz/

├── README.md
├── TestCases/
│   ├── test_align_database.py
│   ├── test_best_threshold_generation.py
│   ├── test_detection.py
│   ├── test_verification_on_general_dataset.py
│   ├── test_verification_on_single_pair.py
│   └── verification_text_files/
│       ├── ARFace/
│       │   ├── validation.txt
│       │   └── validation_test_gen.py
│       ├── LFW/
│       │   ├── pairsDevTest.txt
│       │   ├── validation.txt
│       │   └── validation_test_gen.py
│       └── PCD/
│           ├── read me.txt
│           └── validation.txt
├── UtilsAlign/
│   ├── __init__.py
│   ├── base/
│   │   ├── __init__.py
│   │   ├── det1.npy
│   │   ├── det2.npy
│   │   ├── det3.npy
│   │   └── detect.py
│   ├── bbox.py
│   ├── common.py
│   ├── database.py
│   └── landmarks.py
├── UtilsData/
│   ├── __init__.py
│   ├── dataloader.py
│   ├── dataset.py
│   └── sampler.py
├── cfg.py
├── data.py
├── train.py
├── utils.py
└── vggface.py

================================================
FILE CONTENTS
================================================

================================================
FILE: README.md
================================================

# what content does this project contain
1. face detection and alignment
![Alt text](https://github.com/Ao-Lee/Vgg-Face-Fine-tune/raw/master/TestCases/imgs/detection/_01.jpg)

2. face verification predictions
![Alt text](https://github.com/Ao-Lee/Vgg-Face-Fine-tune/raw/master/TestCases/imgs/verification/example.png)

3. fine tune a pre-trained model with your customized dataset

# how it works
the network used in this project is vgg16 and it was pre-trained by Oxford to classify 2622 identities. Check [this paper](https://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf) for more details. Since their model was trained for a classification purpose, it must be
tuned to fit verification tasks. A triplet loss is used in this project just as what the paper describes. For more details about triplet loss, check [this](https://arxiv.org/abs/1503.03832) Google facenet paper

# how to install
1. install anaconda for python 3
2. install tensorflow
3. install keras (theno backend is not tested)
4. install other python packages such as tqdm

# how to perform face detection and alignment
run TestCases\test_align_database.py

# Datasets used 
different face datasets were used in this project, they are
LFW dataset (http://vis-www.cs.umass.edu/lfw/)
AR dataset (http://www2.ece.ohio-state.edu/~aleix/ARdatabase.html)
CAS-PEAL dataset (http://www.jdl.ac.cn/peal/)

# how to perform verification
any face dataset can be used, since lfw data set is easy to download and prepare, we use lfw dataset for illustration
1. download lfw dataset. Since we have our own align implementation. it is recommended to download data without alignment. the quick link is [here](http://vis-www.cs.umass.edu/lfw/lfw.tgz)
2. align the lfw database. Open TestCases\test_align_database.py and edit the following two lines
```
source = 'imgs\\align_test\\origin'
target = 'imgs\\align_test\\aligned'
```
run test_align_database.py after running, you should get a folder of aligned images.

3. download the model:
	* todo: provide download link
4. open cfg.py and modify the '_dir_models' variable, it changes the absolute path to the model
5. open TestCases\test_verification_on_general_dataset.py and change dir_image to be the root directory of aligned images
6.run test_verification_on_general_dataset.py

# how to train the network
- we still use lfw dataset to illustrate the process, in practice, any face dataset can be used
- note that it is recommended to use a GPU to train. Training on a cpu machine could be very slow.

1. open train.py and modify this line:
	reader_LFW = LFWReader(dir_images='E:\\DM\\Faces\\Data\\LFW\\aligned')
	set the directory to be the absolute path of aligned lfw images
2. run the train.py code



================================================
FILE: TestCases/test_align_database.py
================================================
import sys
sys.path.append("..")
from UtilsAlign import AlignDatabase, GetAlignFuncByBoundingBox

if __name__ == '__main__':
    
    source = 'imgs\\align_test\\origin'
    target = 'imgs\\align_test\\aligned'
    
    F = GetAlignFuncByBoundingBox(output_size=224, margin=24)
    AlignDatabase(source, target, align_func=F)
    


================================================
FILE: TestCases/test_best_threshold_generation.py
================================================
import numpy as np
from os.path import join, isfile
import pandas as pd
from tqdm import tqdm
from sklearn import metrics

import sys
sys.path.append('..')
from vggface import VggFace
from utils import Verify, GetBestThreshold
import cfg

# dir_image = 'E:\\DM\\Faces\\Data\\ARFace\\aligned'
# dir_txt = 'ARFace\\validation.txt'

# dir_image = 'E:\\DM\\Faces\\Data\\LFW\\aligned'
# dir_txt = 'LFW\\validation.txt'

dir_image = 'E:\\DM\\Faces\\Data\\PCD\\aligned'
dir_txt = 'verification_text_files\\PCD\\validation.txt'

def GetDataFrame():
    return pd.read_table(dir_txt, sep='\t')
    
def GetResult(model):
    df = GetDataFrame()
    dists = []
    labels = []
    for idx in tqdm(range(len(df))):
        path1 = join(dir_image, df.loc[idx,'img1'])
        path2 = join(dir_image, df.loc[idx,'img2'])
        if (not isfile(path1)) or (not isfile(path2)):
            continue
        dist = Verify(path1, path2, model)
        dists.append(dist)
        labels.append(df.loc[idx,'class'])
       
    labels = np.array(labels)
    dists = np.array(dists)
    return labels, dists


if __name__ == '__main__':
    model = VggFace(cfg.dir_model_v2, is_origin=True)
    labels, dists = GetResult(model)
    
    labels = (labels=='S').astype(np.int)
    threshold, _ = GetBestThreshold(dists, labels)
    predictions = (dists < threshold).astype(np.int)
    
    auc = metrics.roc_auc_score(np.logical_not(labels), dists)
    acc = metrics.accuracy_score(labels, predictions)
    print('auc is: {}'.format(auc))
    print('threshold is {}'.format(threshold))
    print('accuracy is {}'.format(acc))


================================================
FILE: TestCases/test_detection.py
================================================
import numpy as np
from PIL import Image, ImageDraw
from scipy.misc import imsave
from os.path import join, isfile

import sys
sys.path.append("..")
from utils import Inputs2ArrayImage, MergeImage
from UtilsAlign import GetLandmarks

F = GetLandmarks()

def DrawPoint(draw, x, y):
    r = 1
    draw.ellipse((x-r, y-r, x+r, y+r), fill=(0,0,255,255))
 
def ModifyImg(img):
    bounding_boxes, landmarks = F(img)
    img = Image.fromarray(img)
    B = bounding_boxes[:,:-1]
    
    draw = ImageDraw.Draw(img)
    for b in B:
        shape = ((b[0], b[1]), (b[2], b[3]))
        draw.rectangle(shape, outline='blue')
        
    for m in landmarks.T:
        DrawPoint(draw, m[0], m[5])
        DrawPoint(draw, m[1], m[6])
        
    return np.array(img)
    

if __name__=='__main__':
    root = 'imgs\detection'
    names = ['01.jpg', '02.jpg']

    for name in names:
        path = join(root, name)
        assert(isfile(path))

        img = Inputs2ArrayImage(path)
        img_modified = ModifyImg(img)
        img_merge = MergeImage(img, img_modified)
        
        new_name = '_' + name
        new_path = join(root, new_name)
        imsave(new_path, img_merge)
    
    
    
      

================================================
FILE: TestCases/test_verification_on_general_dataset.py
================================================
import numpy as np
from os.path import join, isfile
import pandas as pd
from tqdm import tqdm
from sklearn import metrics
from keras import backend as K
import sys
sys.path.append('..')
from vggface import VggFace
from utils import Verify
import cfg

# dir_image = 'E:\\DM\\Faces\\Data\\ARFace\\aligned'
# dir_txt = 'ARFace\\validation.txt'

# dir_image = 'E:\\DM\\Faces\\Data\\LFW\\aligned'
# dir_txt = 'LFW\\validation.txt'

dir_image = 'E:\\DM\\Faces\\Data\\PCD\\aligned'
dir_txt = 'verification_text_files\\PCD\\validation.txt'
K.set_image_dim_ordering('th')


def GetDataFrame():
    return pd.read_table(dir_txt, sep='\t')
    
def GetResult(model):
    df = GetDataFrame()
    dists = []
    labels = []
    for idx in tqdm(range(len(df))):
        path1 = join(dir_image, df.loc[idx,'img1'])
        path2 = join(dir_image, df.loc[idx,'img2'])
        if (not isfile(path1)) or (not isfile(path2)):
            continue
        dist = Verify(path1, path2, model)
        dists.append(dist)
        labels.append(df.loc[idx,'class'])
       
    labels = np.array(labels)
    dists = np.array(dists)
    return labels, dists


if __name__ == '__main__':
    threshold = 1.1
    model = VggFace(cfg.dir_model_v2, is_origin=True)
    labels, dists = GetResult(model)
    labels = (labels=='S').astype(np.int)
    predictions = (dists < threshold).astype(np.int)
    
    auc = metrics.roc_auc_score(np.logical_not(labels), dists)
    acc = metrics.accuracy_score(labels, predictions)
    print('auc is: {}'.format(auc))
    print('accuracy is {}'.format(acc))


================================================
FILE: TestCases/test_verification_on_single_pair.py
================================================
from os.path import join, isdir
from os import listdir
import matplotlib.pyplot as plt
import sys
import numpy as np

sys.path.append('..')
from vggface import VggFace
from utils import Verify, MergeImage, Inputs2ArrayImage
import cfg

threshold = 1.1

def _VerifyFolder(path_to_folder, model):
    paths = listdir(path_to_folder)
    assert len(paths)==2
    path01 = join(path_to_folder, paths[0])
    path02 = join(path_to_folder, paths[1])
    dist = Verify(path01, path02, model)
    result = 'same' if dist < threshold else 'different'
    color = (0,255,0) if dist < threshold else (255,0,0)
    
    img1 = Inputs2ArrayImage(path01, dtype=np.uint8)
    img2 = Inputs2ArrayImage(path02, dtype=np.uint8)
    img_merged = MergeImage(img1, img2, color=color)

    name1 = _GetPersonName(paths[0])
    name2 = _GetPersonName(paths[1])
    
    title = '(' + name1 + ')' + ' - ' + result +  ' - ' + '(' + name2 + ')'
    return img_merged, title

def _ShowImage(img, title):
    plt.figure()
    plt.imshow(img.astype('uint8'))
    plt.title(title)
    plt.show()
    plt.close()
        
def _GetPersonName(filename):
    # filename = 'Adolfo_Rodriguez_Saa_0001.jpg'
    return filename[:-9]

if __name__ == '__main__':
    root = 'imgs\\verification'
    output_file = 'example.jpg'
    model = VggFace(path=cfg.dir_model_v2, is_origin=True)
    folders = listdir(root)
    imgs = []
    titles = []
    
    folders = [folder for folder in folders if isdir(join(root, folder))]

    for folder in folders:
        img, title = _VerifyFolder(join(root, folder), model)
        imgs.append(img)
        titles.append(title)
    
    f,axes = plt.subplots(len(folders), 1, figsize=(10,16))
    for ax, img, title in zip(axes, imgs, titles):
        ax.imshow(img)
        ax.set_axis_off()
        ax.set_title(title)
        
    #plt.show()
    #plt.savefig()
    #plt.close()
        
    


================================================
FILE: TestCases/verification_text_files/ARFace/validation.txt
================================================
img1	img2	class
M-001-01.bmp	M-001-02.bmp	S
M-001-01.bmp	M-001-03.bmp	S
M-001-01.bmp	M-001-04.bmp	S
M-001-01.bmp	M-001-05.bmp	S
M-001-01.bmp	M-001-06.bmp	S
M-001-01.bmp	M-001-07.bmp	S
M-001-01.bmp	M-001-08.bmp	S
M-001-01.bmp	M-001-09.bmp	S
M-001-01.bmp	M-001-10.bmp	S
M-001-01.bmp	M-001-11.bmp	S
M-001-01.bmp	M-001-12.bmp	S
M-001-01.bmp	M-001-13.bmp	S
M-001-01.bmp	M-001-14.bmp	S
M-001-01.bmp	M-001-15.bmp	S
M-001-01.bmp	M-001-16.bmp	S
M-001-01.bmp	M-001-17.bmp	S
M-001-01.bmp	M-001-18.bmp	S
M-001-01.bmp	M-001-19.bmp	S
M-001-01.bmp	M-001-20.bmp	S
M-001-01.bmp	M-001-21.bmp	S
M-001-01.bmp	M-001-22.bmp	S
M-001-01.bmp	M-001-23.bmp	S
M-001-01.bmp	M-001-24.bmp	S
M-001-01.bmp	M-001-25.bmp	S
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M-003-01.bmp	M-003-15.bmp	S
M-003-01.bmp	M-003-16.bmp	S
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M-006-01.bmp	M-006-11.bmp	S
M-006-01.bmp	M-006-12.bmp	S
M-006-01.bmp	M-006-13.bmp	S
M-006-01.bmp	M-006-14.bmp	S
M-006-01.bmp	M-006-15.bmp	S
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M-007-01.bmp	M-007-22.bmp	S
M-007-01.bmp	M-007-23.bmp	S
M-007-01.bmp	M-007-24.bmp	S
M-007-01.bmp	M-007-25.bmp	S
M-007-01.bmp	M-007-26.bmp	S
M-008-01.bmp	M-008-02.bmp	S
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M-008-01.bmp	M-008-10.bmp	S
M-008-01.bmp	M-008-11.bmp	S
M-008-01.bmp	M-008-12.bmp	S
M-008-01.bmp	M-008-13.bmp	S
M-008-01.bmp	M-008-14.bmp	S
M-008-01.bmp	M-008-15.bmp	S
M-008-01.bmp	M-008-16.bmp	S
M-008-01.bmp	M-008-17.bmp	S
M-008-01.bmp	M-008-18.bmp	S
M-008-01.bmp	M-008-19.bmp	S
M-008-01.bmp	M-008-20.bmp	S
M-008-01.bmp	M-008-21.bmp	S
M-008-01.bmp	M-008-22.bmp	S
M-008-01.bmp	M-008-23.bmp	S
M-008-01.bmp	M-008-24.bmp	S
M-008-01.bmp	M-008-25.bmp	S
M-008-01.bmp	M-008-26.bmp	S
M-009-01.bmp	M-009-02.bmp	S
M-009-01.bmp	M-009-03.bmp	S
M-009-01.bmp	M-009-04.bmp	S
M-009-01.bmp	M-009-05.bmp	S
M-009-01.bmp	M-009-06.bmp	S
M-009-01.bmp	M-009-07.bmp	S
M-009-01.bmp	M-009-08.bmp	S
M-009-01.bmp	M-009-09.bmp	S
M-009-01.bmp	M-009-10.bmp	S
M-009-01.bmp	M-009-11.bmp	S
M-009-01.bmp	M-009-12.bmp	S
M-009-01.bmp	M-009-13.bmp	S
M-009-01.bmp	M-009-14.bmp	S
M-009-01.bmp	M-009-15.bmp	S
M-009-01.bmp	M-009-16.bmp	S
M-009-01.bmp	M-009-17.bmp	S
M-009-01.bmp	M-009-18.bmp	S
M-009-01.bmp	M-009-19.bmp	S
M-009-01.bmp	M-009-20.bmp	S
M-009-01.bmp	M-009-21.bmp	S
M-009-01.bmp	M-009-22.bmp	S
M-009-01.bmp	M-009-23.bmp	S
M-009-01.bmp	M-009-24.bmp	S
M-009-01.bmp	M-009-25.bmp	S
M-009-01.bmp	M-009-26.bmp	S
M-010-01.bmp	M-010-02.bmp	S
M-010-01.bmp	M-010-03.bmp	S
M-010-01.bmp	M-010-04.bmp	S
M-010-01.bmp	M-010-05.bmp	S
M-010-01.bmp	M-010-06.bmp	S
M-010-01.bmp	M-010-07.bmp	S
M-010-01.bmp	M-010-08.bmp	S
M-010-01.bmp	M-010-09.bmp	S
M-010-01.bmp	M-010-10.bmp	S
M-010-01.bmp	M-010-11.bmp	S
M-010-01.bmp	M-010-12.bmp	S
M-010-01.bmp	M-010-13.bmp	S
M-010-01.bmp	M-010-14.bmp	S
M-010-01.bmp	M-010-15.bmp	S
M-010-01.bmp	M-010-16.bmp	S
M-010-01.bmp	M-010-17.bmp	S
M-010-01.bmp	M-010-18.bmp	S
M-010-01.bmp	M-010-19.bmp	S
M-010-01.bmp	M-010-20.bmp	S
M-010-01.bmp	M-010-21.bmp	S
M-010-01.bmp	M-010-22.bmp	S
M-010-01.bmp	M-010-23.bmp	S
M-010-01.bmp	M-010-24.bmp	S
M-010-01.bmp	M-010-25.bmp	S
M-010-01.bmp	M-010-26.bmp	S
M-011-01.bmp	M-011-02.bmp	S
M-011-01.bmp	M-011-03.bmp	S
M-011-01.bmp	M-011-04.bmp	S
M-011-01.bmp	M-011-05.bmp	S
M-011-01.bmp	M-011-06.bmp	S
M-011-01.bmp	M-011-07.bmp	S
M-011-01.bmp	M-011-08.bmp	S
M-011-01.bmp	M-011-09.bmp	S
M-011-01.bmp	M-011-10.bmp	S
M-011-01.bmp	M-011-11.bmp	S
M-011-01.bmp	M-011-12.bmp	S
M-011-01.bmp	M-011-13.bmp	S
M-011-01.bmp	M-011-14.bmp	S
M-011-01.bmp	M-011-15.bmp	S
M-011-01.bmp	M-011-16.bmp	S
M-011-01.bmp	M-011-17.bmp	S
M-011-01.bmp	M-011-18.bmp	S
M-011-01.bmp	M-011-19.bmp	S
M-011-01.bmp	M-011-20.bmp	S
M-011-01.bmp	M-011-21.bmp	S
M-011-01.bmp	M-011-22.bmp	S
M-011-01.bmp	M-011-23.bmp	S
M-011-01.bmp	M-011-24.bmp	S
M-011-01.bmp	M-011-25.bmp	S
M-011-01.bmp	M-011-26.bmp	S
M-012-01.bmp	M-012-02.bmp	S
M-012-01.bmp	M-012-03.bmp	S
M-012-01.bmp	M-012-04.bmp	S
M-012-01.bmp	M-012-05.bmp	S
M-012-01.bmp	M-012-06.bmp	S
M-012-01.bmp	M-012-07.bmp	S
M-012-01.bmp	M-012-08.bmp	S
M-012-01.bmp	M-012-09.bmp	S
M-012-01.bmp	M-012-10.bmp	S
M-012-01.bmp	M-012-11.bmp	S
M-012-01.bmp	M-012-12.bmp	S
M-012-01.bmp	M-012-13.bmp	S
M-012-01.bmp	M-012-14.bmp	S
M-012-01.bmp	M-012-15.bmp	S
M-012-01.bmp	M-012-16.bmp	S
M-012-01.bmp	M-012-17.bmp	S
M-012-01.bmp	M-012-18.bmp	S
M-012-01.bmp	M-012-19.bmp	S
M-012-01.bmp	M-012-20.bmp	S
M-012-01.bmp	M-012-21.bmp	S
M-012-01.bmp	M-012-22.bmp	S
M-012-01.bmp	M-012-23.bmp	S
M-012-01.bmp	M-012-24.bmp	S
M-012-01.bmp	M-012-25.bmp	S
M-012-01.bmp	M-012-26.bmp	S
M-013-01.bmp	M-013-02.bmp	S
M-013-01.bmp	M-013-03.bmp	S
M-013-01.bmp	M-013-04.bmp	S
M-013-01.bmp	M-013-05.bmp	S
M-013-01.bmp	M-013-06.bmp	S
M-013-01.bmp	M-013-07.bmp	S
M-013-01.bmp	M-013-08.bmp	S
M-013-01.bmp	M-013-09.bmp	S
M-013-01.bmp	M-013-10.bmp	S
M-013-01.bmp	M-013-11.bmp	S
M-013-01.bmp	M-013-12.bmp	S
M-013-01.bmp	M-013-13.bmp	S
M-013-01.bmp	M-013-14.bmp	S
M-013-01.bmp	M-013-15.bmp	S
M-013-01.bmp	M-013-16.bmp	S
M-013-01.bmp	M-013-17.bmp	S
M-013-01.bmp	M-013-18.bmp	S
M-013-01.bmp	M-013-19.bmp	S
M-013-01.bmp	M-013-20.bmp	S
M-013-01.bmp	M-013-21.bmp	S
M-013-01.bmp	M-013-22.bmp	S
M-013-01.bmp	M-013-23.bmp	S
M-013-01.bmp	M-013-24.bmp	S
M-013-01.bmp	M-013-25.bmp	S
M-013-01.bmp	M-013-26.bmp	S
M-014-01.bmp	M-014-02.bmp	S
M-014-01.bmp	M-014-03.bmp	S
M-014-01.bmp	M-014-04.bmp	S
M-014-01.bmp	M-014-05.bmp	S
M-014-01.bmp	M-014-06.bmp	S
M-014-01.bmp	M-014-07.bmp	S
M-014-01.bmp	M-014-08.bmp	S
M-014-01.bmp	M-014-09.bmp	S
M-014-01.bmp	M-014-10.bmp	S
M-014-01.bmp	M-014-11.bmp	S
M-014-01.bmp	M-014-12.bmp	S
M-014-01.bmp	M-014-13.bmp	S
M-014-01.bmp	M-014-14.bmp	S
M-014-01.bmp	M-014-15.bmp	S
M-014-01.bmp	M-014-16.bmp	S
M-014-01.bmp	M-014-17.bmp	S
M-014-01.bmp	M-014-18.bmp	S
M-014-01.bmp	M-014-19.bmp	S
M-014-01.bmp	M-014-20.bmp	S
M-014-01.bmp	M-014-21.bmp	S
M-014-01.bmp	M-014-22.bmp	S
M-014-01.bmp	M-014-23.bmp	S
M-014-01.bmp	M-014-24.bmp	S
M-014-01.bmp	M-014-25.bmp	S
M-014-01.bmp	M-014-26.bmp	S
M-015-01.bmp	M-015-02.bmp	S
M-015-01.bmp	M-015-03.bmp	S
M-015-01.bmp	M-015-04.bmp	S
M-015-01.bmp	M-015-05.bmp	S
M-015-01.bmp	M-015-06.bmp	S
M-015-01.bmp	M-015-07.bmp	S
M-015-01.bmp	M-015-08.bmp	S
M-015-01.bmp	M-015-09.bmp	S
M-015-01.bmp	M-015-10.bmp	S
M-015-01.bmp	M-015-11.bmp	S
M-015-01.bmp	M-015-12.bmp	S
M-015-01.bmp	M-015-13.bmp	S
M-015-01.bmp	M-015-14.bmp	S
M-015-01.bmp	M-015-15.bmp	S
M-015-01.bmp	M-015-16.bmp	S
M-015-01.bmp	M-015-17.bmp	S
M-015-01.bmp	M-015-18.bmp	S
M-015-01.bmp	M-015-19.bmp	S
M-015-01.bmp	M-015-20.bmp	S
M-015-01.bmp	M-015-21.bmp	S
M-015-01.bmp	M-015-22.bmp	S
M-015-01.bmp	M-015-23.bmp	S
M-015-01.bmp	M-015-24.bmp	S
M-015-01.bmp	M-015-25.bmp	S
M-015-01.bmp	M-015-26.bmp	S
M-016-01.bmp	M-016-02.bmp	S
M-016-01.bmp	M-016-03.bmp	S
M-016-01.bmp	M-016-04.bmp	S
M-016-01.bmp	M-016-05.bmp	S
M-016-01.bmp	M-016-06.bmp	S
M-016-01.bmp	M-016-07.bmp	S
M-016-01.bmp	M-016-08.bmp	S
M-016-01.bmp	M-016-09.bmp	S
M-016-01.bmp	M-016-10.bmp	S
M-016-01.bmp	M-016-11.bmp	S
M-016-01.bmp	M-016-12.bmp	S
M-016-01.bmp	M-016-13.bmp	S
M-016-01.bmp	M-016-14.bmp	S
M-016-01.bmp	M-016-15.bmp	S
M-016-01.bmp	M-016-16.bmp	S
M-016-01.bmp	M-016-17.bmp	S
M-016-01.bmp	M-016-18.bmp	S
M-016-01.bmp	M-016-19.bmp	S
M-016-01.bmp	M-016-20.bmp	S
M-016-01.bmp	M-016-21.bmp	S
M-016-01.bmp	M-016-22.bmp	S
M-016-01.bmp	M-016-23.bmp	S
M-016-01.bmp	M-016-24.bmp	S
M-016-01.bmp	M-016-25.bmp	S
M-016-01.bmp	M-016-26.bmp	S
M-017-01.bmp	M-017-02.bmp	S
M-017-01.bmp	M-017-03.bmp	S
M-017-01.bmp	M-017-04.bmp	S
M-017-01.bmp	M-017-05.bmp	S
M-017-01.bmp	M-017-06.bmp	S
M-017-01.bmp	M-017-07.bmp	S
M-017-01.bmp	M-017-08.bmp	S
M-017-01.bmp	M-017-09.bmp	S
M-017-01.bmp	M-017-10.bmp	S
M-017-01.bmp	M-017-11.bmp	S
M-017-01.bmp	M-017-12.bmp	S
M-017-01.bmp	M-017-13.bmp	S
M-017-01.bmp	M-017-14.bmp	S
M-017-01.bmp	M-017-15.bmp	S
M-017-01.bmp	M-017-16.bmp	S
M-017-01.bmp	M-017-17.bmp	S
M-017-01.bmp	M-017-18.bmp	S
M-017-01.bmp	M-017-19.bmp	S
M-017-01.bmp	M-017-20.bmp	S
M-017-01.bmp	M-017-21.bmp	S
M-017-01.bmp	M-017-22.bmp	S
M-017-01.bmp	M-017-23.bmp	S
M-017-01.bmp	M-017-24.bmp	S
M-017-01.bmp	M-017-25.bmp	S
M-017-01.bmp	M-017-26.bmp	S
M-018-01.bmp	M-018-02.bmp	S
M-018-01.bmp	M-018-03.bmp	S
M-018-01.bmp	M-018-04.bmp	S
M-018-01.bmp	M-018-05.bmp	S
M-018-01.bmp	M-018-06.bmp	S
M-018-01.bmp	M-018-07.bmp	S
M-018-01.bmp	M-018-08.bmp	S
M-018-01.bmp	M-018-09.bmp	S
M-018-01.bmp	M-018-10.bmp	S
M-018-01.bmp	M-018-11.bmp	S
M-018-01.bmp	M-018-12.bmp	S
M-018-01.bmp	M-018-13.bmp	S
M-018-01.bmp	M-018-14.bmp	S
M-018-01.bmp	M-018-15.bmp	S
M-018-01.bmp	M-018-16.bmp	S
M-018-01.bmp	M-018-17.bmp	S
M-018-01.bmp	M-018-18.bmp	S
M-018-01.bmp	M-018-19.bmp	S
M-018-01.bmp	M-018-20.bmp	S
M-018-01.bmp	M-018-21.bmp	S
M-018-01.bmp	M-018-22.bmp	S
M-018-01.bmp	M-018-23.bmp	S
M-018-01.bmp	M-018-24.bmp	S
M-018-01.bmp	M-018-25.bmp	S
M-018-01.bmp	M-018-26.bmp	S
M-019-01.bmp	M-019-02.bmp	S
M-019-01.bmp	M-019-03.bmp	S
M-019-01.bmp	M-019-04.bmp	S
M-019-01.bmp	M-019-05.bmp	S
M-019-01.bmp	M-019-06.bmp	S
M-019-01.bmp	M-019-07.bmp	S
M-019-01.bmp	M-019-08.bmp	S
M-019-01.bmp	M-019-09.bmp	S
M-019-01.bmp	M-019-10.bmp	S
M-019-01.bmp	M-019-11.bmp	S
M-019-01.bmp	M-019-12.bmp	S
M-019-01.bmp	M-019-13.bmp	S
M-019-01.bmp	M-019-14.bmp	S
M-019-01.bmp	M-019-15.bmp	S
M-019-01.bmp	M-019-16.bmp	S
M-019-01.bmp	M-019-17.bmp	S
M-019-01.bmp	M-019-18.bmp	S
M-019-01.bmp	M-019-19.bmp	S
M-019-01.bmp	M-019-20.bmp	S
M-019-01.bmp	M-019-21.bmp	S
M-019-01.bmp	M-019-22.bmp	S
M-019-01.bmp	M-019-23.bmp	S
M-019-01.bmp	M-019-24.bmp	S
M-019-01.bmp	M-019-25.bmp	S
M-019-01.bmp	M-019-26.bmp	S
M-020-01.bmp	M-020-02.bmp	S
M-020-01.bmp	M-020-03.bmp	S
M-020-01.bmp	M-020-04.bmp	S
M-020-01.bmp	M-020-05.bmp	S
M-020-01.bmp	M-020-06.bmp	S
M-020-01.bmp	M-020-07.bmp	S
M-020-01.bmp	M-020-08.bmp	S
M-020-01.bmp	M-020-09.bmp	S
M-020-01.bmp	M-020-10.bmp	S
M-020-01.bmp	M-020-11.bmp	S
M-020-01.bmp	M-020-12.bmp	S
M-020-01.bmp	M-020-13.bmp	S
M-020-01.bmp	M-020-14.bmp	S
M-020-01.bmp	M-020-15.bmp	S
M-020-01.bmp	M-020-16.bmp	S
M-020-01.bmp	M-020-17.bmp	S
M-020-01.bmp	M-020-18.bmp	S
M-020-01.bmp	M-020-19.bmp	S
M-020-01.bmp	M-020-20.bmp	S
M-020-01.bmp	M-020-21.bmp	S
M-020-01.bmp	M-020-22.bmp	S
M-020-01.bmp	M-020-23.bmp	S
M-020-01.bmp	M-020-24.bmp	S
M-020-01.bmp	M-020-25.bmp	S
M-020-01.bmp	M-020-26.bmp	S
M-021-01.bmp	M-021-02.bmp	S
M-021-01.bmp	M-021-03.bmp	S
M-021-01.bmp	M-021-04.bmp	S
M-021-01.bmp	M-021-05.bmp	S
M-021-01.bmp	M-021-06.bmp	S
M-021-01.bmp	M-021-07.bmp	S
M-021-01.bmp	M-021-08.bmp	S
M-021-01.bmp	M-021-09.bmp	S
M-021-01.bmp	M-021-10.bmp	S
M-021-01.bmp	M-021-11.bmp	S
M-021-01.bmp	M-021-12.bmp	S
M-021-01.bmp	M-021-13.bmp	S
M-021-01.bmp	M-021-14.bmp	S
M-021-01.bmp	M-021-15.bmp	S
M-021-01.bmp	M-021-16.bmp	S
M-021-01.bmp	M-021-17.bmp	S
M-021-01.bmp	M-021-18.bmp	S
M-021-01.bmp	M-021-19.bmp	S
M-021-01.bmp	M-021-20.bmp	S
M-021-01.bmp	M-021-21.bmp	S
M-021-01.bmp	M-021-22.bmp	S
M-021-01.bmp	M-021-23.bmp	S
M-021-01.bmp	M-021-24.bmp	S
M-021-01.bmp	M-021-25.bmp	S
M-021-01.bmp	M-021-26.bmp	S
M-022-01.bmp	M-022-02.bmp	S
M-022-01.bmp	M-022-03.bmp	S
M-022-01.bmp	M-022-04.bmp	S
M-022-01.bmp	M-022-05.bmp	S
M-022-01.bmp	M-022-06.bmp	S
M-022-01.bmp	M-022-07.bmp	S
M-022-01.bmp	M-022-08.bmp	S
M-022-01.bmp	M-022-09.bmp	S
M-022-01.bmp	M-022-10.bmp	S
M-022-01.bmp	M-022-11.bmp	S
M-022-01.bmp	M-022-12.bmp	S
M-022-01.bmp	M-022-13.bmp	S
M-022-01.bmp	M-022-14.bmp	S
M-022-01.bmp	M-022-15.bmp	S
M-022-01.bmp	M-022-16.bmp	S
M-022-01.bmp	M-022-17.bmp	S
M-022-01.bmp	M-022-18.bmp	S
M-022-01.bmp	M-022-19.bmp	S
M-022-01.bmp	M-022-20.bmp	S
M-022-01.bmp	M-022-21.bmp	S
M-022-01.bmp	M-022-22.bmp	S
M-022-01.bmp	M-022-23.bmp	S
M-022-01.bmp	M-022-24.bmp	S
M-022-01.bmp	M-022-25.bmp	S
M-022-01.bmp	M-022-26.bmp	S
M-023-01.bmp	M-023-02.bmp	S
M-023-01.bmp	M-023-03.bmp	S
M-023-01.bmp	M-023-04.bmp	S
M-023-01.bmp	M-023-05.bmp	S
M-023-01.bmp	M-023-06.bmp	S
M-023-01.bmp	M-023-07.bmp	S
M-023-01.bmp	M-023-08.bmp	S
M-023-01.bmp	M-023-09.bmp	S
M-023-01.bmp	M-023-10.bmp	S
M-023-01.bmp	M-023-11.bmp	S
M-023-01.bmp	M-023-12.bmp	S
M-023-01.bmp	M-023-13.bmp	S
M-023-01.bmp	M-023-14.bmp	S
M-023-01.bmp	M-023-15.bmp	S
M-023-01.bmp	M-023-16.bmp	S
M-023-01.bmp	M-023-17.bmp	S
M-023-01.bmp	M-023-18.bmp	S
M-023-01.bmp	M-023-19.bmp	S
M-023-01.bmp	M-023-20.bmp	S
M-023-01.bmp	M-023-21.bmp	S
M-023-01.bmp	M-023-22.bmp	S
M-023-01.bmp	M-023-23.bmp	S
M-023-01.bmp	M-023-24.bmp	S
M-023-01.bmp	M-023-25.bmp	S
M-023-01.bmp	M-023-26.bmp	S
M-024-01.bmp	M-024-02.bmp	S
M-024-01.bmp	M-024-03.bmp	S
M-024-01.bmp	M-024-04.bmp	S
M-024-01.bmp	M-024-05.bmp	S
M-024-01.bmp	M-024-06.bmp	S
M-024-01.bmp	M-024-07.bmp	S
M-024-01.bmp	M-024-08.bmp	S
M-024-01.bmp	M-024-09.bmp	S
M-024-01.bmp	M-024-10.bmp	S
M-024-01.bmp	M-024-11.bmp	S
M-024-01.bmp	M-024-12.bmp	S
M-024-01.bmp	M-024-13.bmp	S
M-024-01.bmp	M-024-14.bmp	S
M-024-01.bmp	M-024-15.bmp	S
M-024-01.bmp	M-024-16.bmp	S
M-024-01.bmp	M-024-17.bmp	S
M-024-01.bmp	M-024-18.bmp	S
M-024-01.bmp	M-024-19.bmp	S
M-024-01.bmp	M-024-20.bmp	S
M-024-01.bmp	M-024-21.bmp	S
M-024-01.bmp	M-024-22.bmp	S
M-024-01.bmp	M-024-23.bmp	S
M-024-01.bmp	M-024-24.bmp	S
M-024-01.bmp	M-024-25.bmp	S
M-024-01.bmp	M-024-26.bmp	S
M-025-01.bmp	M-025-02.bmp	S
M-025-01.bmp	M-025-03.bmp	S
M-025-01.bmp	M-025-04.bmp	S
M-025-01.bmp	M-025-05.bmp	S
M-025-01.bmp	M-025-06.bmp	S
M-025-01.bmp	M-025-07.bmp	S
M-025-01.bmp	M-025-08.bmp	S
M-025-01.bmp	M-025-09.bmp	S
M-025-01.bmp	M-025-10.bmp	S
M-025-01.bmp	M-025-11.bmp	S
M-025-01.bmp	M-025-12.bmp	S
M-025-01.bmp	M-025-13.bmp	S
M-025-01.bmp	M-025-14.bmp	S
M-025-01.bmp	M-025-15.bmp	S
M-025-01.bmp	M-025-16.bmp	S
M-025-01.bmp	M-025-17.bmp	S
M-025-01.bmp	M-025-18.bmp	S
M-025-01.bmp	M-025-19.bmp	S
M-025-01.bmp	M-025-20.bmp	S
M-025-01.bmp	M-025-21.bmp	S
M-025-01.bmp	M-025-22.bmp	S
M-025-01.bmp	M-025-23.bmp	S
M-025-01.bmp	M-025-24.bmp	S
M-025-01.bmp	M-025-25.bmp	S
M-025-01.bmp	M-025-26.bmp	S
M-026-01.bmp	M-026-02.bmp	S
M-026-01.bmp	M-026-03.bmp	S
M-026-01.bmp	M-026-04.bmp	S
M-026-01.bmp	M-026-05.bmp	S
M-026-01.bmp	M-026-06.bmp	S
M-026-01.bmp	M-026-07.bmp	S
M-026-01.bmp	M-026-08.bmp	S
M-026-01.bmp	M-026-09.bmp	S
M-026-01.bmp	M-026-10.bmp	S
M-026-01.bmp	M-026-11.bmp	S
M-026-01.bmp	M-026-12.bmp	S
M-026-01.bmp	M-026-13.bmp	S
M-026-01.bmp	M-026-14.bmp	S
M-026-01.bmp	M-026-15.bmp	S
M-026-01.bmp	M-026-16.bmp	S
M-026-01.bmp	M-026-17.bmp	S
M-026-01.bmp	M-026-18.bmp	S
M-026-01.bmp	M-026-19.bmp	S
M-026-01.bmp	M-026-20.bmp	S
M-026-01.bmp	M-026-21.bmp	S
M-026-01.bmp	M-026-22.bmp	S
M-026-01.bmp	M-026-23.bmp	S
M-026-01.bmp	M-026-24.bmp	S
M-026-01.bmp	M-026-25.bmp	S
M-026-01.bmp	M-026-26.bmp	S
M-027-01.bmp	M-027-02.bmp	S
M-027-01.bmp	M-027-03.bmp	S
M-027-01.bmp	M-027-04.bmp	S
M-027-01.bmp	M-027-05.bmp	S
M-027-01.bmp	M-027-06.bmp	S
M-027-01.bmp	M-027-07.bmp	S
M-027-01.bmp	M-027-08.bmp	S
M-027-01.bmp	M-027-09.bmp	S
M-027-01.bmp	M-027-10.bmp	S
M-027-01.bmp	M-027-11.bmp	S
M-027-01.bmp	M-027-12.bmp	S
M-027-01.bmp	M-027-13.bmp	S
M-027-01.bmp	M-027-14.bmp	S
M-027-01.bmp	M-027-15.bmp	S
M-027-01.bmp	M-027-16.bmp	S
M-027-01.bmp	M-027-17.bmp	S
M-027-01.bmp	M-027-18.bmp	S
M-027-01.bmp	M-027-19.bmp	S
M-027-01.bmp	M-027-20.bmp	S
M-027-01.bmp	M-027-21.bmp	S
M-027-01.bmp	M-027-22.bmp	S
M-027-01.bmp	M-027-23.bmp	S
M-027-01.bmp	M-027-24.bmp	S
M-027-01.bmp	M-027-25.bmp	S
M-027-01.bmp	M-027-26.bmp	S
M-028-01.bmp	M-028-02.bmp	S
M-028-01.bmp	M-028-03.bmp	S
M-028-01.bmp	M-028-04.bmp	S
M-028-01.bmp	M-028-05.bmp	S
M-028-01.bmp	M-028-06.bmp	S
M-028-01.bmp	M-028-07.bmp	S
M-028-01.bmp	M-028-08.bmp	S
M-028-01.bmp	M-028-09.bmp	S
M-028-01.bmp	M-028-10.bmp	S
M-028-01.bmp	M-028-11.bmp	S
M-028-01.bmp	M-028-12.bmp	S
M-028-01.bmp	M-028-13.bmp	S
M-028-01.bmp	M-028-14.bmp	S
M-028-01.bmp	M-028-15.bmp	S
M-028-01.bmp	M-028-16.bmp	S
M-028-01.bmp	M-028-17.bmp	S
M-028-01.bmp	M-028-18.bmp	S
M-028-01.bmp	M-028-19.bmp	S
M-028-01.bmp	M-028-20.bmp	S
M-028-01.bmp	M-028-21.bmp	S
M-028-01.bmp	M-028-22.bmp	S
M-028-01.bmp	M-028-23.bmp	S
M-028-01.bmp	M-028-24.bmp	S
M-028-01.bmp	M-028-25.bmp	S
M-028-01.bmp	M-028-26.bmp	S
M-029-01.bmp	M-029-02.bmp	S
M-029-01.bmp	M-029-03.bmp	S
M-029-01.bmp	M-029-04.bmp	S
M-029-01.bmp	M-029-05.bmp	S
M-029-01.bmp	M-029-06.bmp	S
M-029-01.bmp	M-029-07.bmp	S
M-029-01.bmp	M-029-08.bmp	S
M-029-01.bmp	M-029-09.bmp	S
M-029-01.bmp	M-029-10.bmp	S
M-029-01.bmp	M-029-11.bmp	S
M-029-01.bmp	M-029-12.bmp	S
M-029-01.bmp	M-029-13.bmp	S
M-029-01.bmp	M-029-14.bmp	S
M-029-01.bmp	M-029-15.bmp	S
M-029-01.bmp	M-029-16.bmp	S
M-029-01.bmp	M-029-17.bmp	S
M-029-01.bmp	M-029-18.bmp	S
M-029-01.bmp	M-029-19.bmp	S
M-029-01.bmp	M-029-20.bmp	S
M-029-01.bmp	M-029-21.bmp	S
M-029-01.bmp	M-029-22.bmp	S
M-029-01.bmp	M-029-23.bmp	S
M-029-01.bmp	M-029-24.bmp	S
M-029-01.bmp	M-029-25.bmp	S
M-029-01.bmp	M-029-26.bmp	S
M-030-01.bmp	M-030-02.bmp	S
M-030-01.bmp	M-030-03.bmp	S
M-030-01.bmp	M-030-04.bmp	S
M-030-01.bmp	M-030-05.bmp	S
M-030-01.bmp	M-030-06.bmp	S
M-030-01.bmp	M-030-07.bmp	S
M-030-01.bmp	M-030-08.bmp	S
M-030-01.bmp	M-030-09.bmp	S
M-030-01.bmp	M-030-10.bmp	S
M-030-01.bmp	M-030-11.bmp	S
M-030-01.bmp	M-030-12.bmp	S
M-030-01.bmp	M-030-13.bmp	S
M-030-01.bmp	M-030-14.bmp	S
M-030-01.bmp	M-030-15.bmp	S
M-030-01.bmp	M-030-16.bmp	S
M-030-01.bmp	M-030-17.bmp	S
M-030-01.bmp	M-030-18.bmp	S
M-030-01.bmp	M-030-19.bmp	S
M-030-01.bmp	M-030-20.bmp	S
M-030-01.bmp	M-030-21.bmp	S
M-030-01.bmp	M-030-22.bmp	S
M-030-01.bmp	M-030-23.bmp	S
M-030-01.bmp	M-030-24.bmp	S
M-030-01.bmp	M-030-25.bmp	S
M-030-01.bmp	M-030-26.bmp	S
M-031-01.bmp	M-031-02.bmp	S
M-031-01.bmp	M-031-03.bmp	S
M-031-01.bmp	M-031-04.bmp	S
M-031-01.bmp	M-031-05.bmp	S
M-031-01.bmp	M-031-06.bmp	S
M-031-01.bmp	M-031-07.bmp	S
M-031-01.bmp	M-031-08.bmp	S
M-031-01.bmp	M-031-09.bmp	S
M-031-01.bmp	M-031-10.bmp	S
M-031-01.bmp	M-031-11.bmp	S
M-031-01.bmp	M-031-12.bmp	S
M-031-01.bmp	M-031-13.bmp	S
M-031-01.bmp	M-031-14.bmp	S
M-031-01.bmp	M-031-15.bmp	S
M-031-01.bmp	M-031-16.bmp	S
M-031-01.bmp	M-031-17.bmp	S
M-031-01.bmp	M-031-18.bmp	S
M-031-01.bmp	M-031-19.bmp	S
M-031-01.bmp	M-031-20.bmp	S
M-031-01.bmp	M-031-21.bmp	S
M-031-01.bmp	M-031-22.bmp	S
M-031-01.bmp	M-031-23.bmp	S
M-031-01.bmp	M-031-24.bmp	S
M-031-01.bmp	M-031-25.bmp	S
M-031-01.bmp	M-031-26.bmp	S
M-032-01.bmp	M-032-02.bmp	S
M-032-01.bmp	M-032-03.bmp	S
M-032-01.bmp	M-032-04.bmp	S
M-032-01.bmp	M-032-05.bmp	S
M-032-01.bmp	M-032-06.bmp	S
M-032-01.bmp	M-032-07.bmp	S
M-032-01.bmp	M-032-08.bmp	S
M-032-01.bmp	M-032-09.bmp	S
M-032-01.bmp	M-032-10.bmp	S
M-032-01.bmp	M-032-11.bmp	S
M-032-01.bmp	M-032-12.bmp	S
M-032-01.bmp	M-032-13.bmp	S
M-032-01.bmp	M-032-14.bmp	S
M-032-01.bmp	M-032-15.bmp	S
M-032-01.bmp	M-032-16.bmp	S
M-032-01.bmp	M-032-17.bmp	S
M-032-01.bmp	M-032-18.bmp	S
M-032-01.bmp	M-032-19.bmp	S
M-032-01.bmp	M-032-20.bmp	S
M-032-01.bmp	M-032-21.bmp	S
M-032-01.bmp	M-032-22.bmp	S
M-032-01.bmp	M-032-23.bmp	S
M-032-01.bmp	M-032-24.bmp	S
M-032-01.bmp	M-032-25.bmp	S
M-032-01.bmp	M-032-26.bmp	S
M-033-01.bmp	M-033-02.bmp	S
M-033-01.bmp	M-033-03.bmp	S
M-033-01.bmp	M-033-04.bmp	S
M-033-01.bmp	M-033-05.bmp	S
M-033-01.bmp	M-033-06.bmp	S
M-033-01.bmp	M-033-07.bmp	S
M-033-01.bmp	M-033-08.bmp	S
M-033-01.bmp	M-033-09.bmp	S
M-033-01.bmp	M-033-10.bmp	S
M-033-01.bmp	M-033-11.bmp	S
M-033-01.bmp	M-033-12.bmp	S
M-033-01.bmp	M-033-13.bmp	S
M-033-01.bmp	M-033-14.bmp	S
M-033-01.bmp	M-033-15.bmp	S
M-033-01.bmp	M-033-16.bmp	S
M-033-01.bmp	M-033-17.bmp	S
M-033-01.bmp	M-033-18.bmp	S
M-033-01.bmp	M-033-19.bmp	S
M-033-01.bmp	M-033-20.bmp	S
M-033-01.bmp	M-033-21.bmp	S
M-033-01.bmp	M-033-22.bmp	S
M-033-01.bmp	M-033-23.bmp	S
M-033-01.bmp	M-033-24.bmp	S
M-033-01.bmp	M-033-25.bmp	S
M-033-01.bmp	M-033-26.bmp	S
M-034-01.bmp	M-034-02.bmp	S
M-034-01.bmp	M-034-03.bmp	S
M-034-01.bmp	M-034-04.bmp	S
M-034-01.bmp	M-034-05.bmp	S
M-034-01.bmp	M-034-06.bmp	S
M-034-01.bmp	M-034-07.bmp	S
M-034-01.bmp	M-034-08.bmp	S
M-034-01.bmp	M-034-09.bmp	S
M-034-01.bmp	M-034-10.bmp	S
M-034-01.bmp	M-034-11.bmp	S
M-034-01.bmp	M-034-12.bmp	S
M-034-01.bmp	M-034-13.bmp	S
M-034-01.bmp	M-034-14.bmp	S
M-034-01.bmp	M-034-15.bmp	S
M-034-01.bmp	M-034-16.bmp	S
M-034-01.bmp	M-034-17.bmp	S
M-034-01.bmp	M-034-18.bmp	S
M-034-01.bmp	M-034-19.bmp	S
M-034-01.bmp	M-034-20.bmp	S
M-034-01.bmp	M-034-21.bmp	S
M-034-01.bmp	M-034-22.bmp	S
M-034-01.bmp	M-034-23.bmp	S
M-034-01.bmp	M-034-24.bmp	S
M-034-01.bmp	M-034-25.bmp	S
M-034-01.bmp	M-034-26.bmp	S
M-035-01.bmp	M-035-02.bmp	S
M-035-01.bmp	M-035-03.bmp	S
M-035-01.bmp	M-035-04.bmp	S
M-035-01.bmp	M-035-05.bmp	S
M-035-01.bmp	M-035-06.bmp	S
M-035-01.bmp	M-035-07.bmp	S
M-035-01.bmp	M-035-08.bmp	S
M-035-01.bmp	M-035-09.bmp	S
M-035-01.bmp	M-035-10.bmp	S
M-035-01.bmp	M-035-11.bmp	S
M-035-01.bmp	M-035-12.bmp	S
M-035-01.bmp	M-035-13.bmp	S
M-035-01.bmp	M-035-14.bmp	S
M-035-01.bmp	M-035-15.bmp	S
M-035-01.bmp	M-035-16.bmp	S
M-035-01.bmp	M-035-17.bmp	S
M-035-01.bmp	M-035-18.bmp	S
M-035-01.bmp	M-035-19.bmp	S
M-035-01.bmp	M-035-20.bmp	S
M-035-01.bmp	M-035-21.bmp	S
M-035-01.bmp	M-035-22.bmp	S
M-035-01.bmp	M-035-23.bmp	S
M-035-01.bmp	M-035-24.bmp	S
M-035-01.bmp	M-035-25.bmp	S
M-035-01.bmp	M-035-26.bmp	S
M-036-01.bmp	M-036-02.bmp	S
M-036-01.bmp	M-036-03.bmp	S
M-036-01.bmp	M-036-04.bmp	S
M-036-01.bmp	M-036-05.bmp	S
M-036-01.bmp	M-036-06.bmp	S
M-036-01.bmp	M-036-07.bmp	S
M-036-01.bmp	M-036-08.bmp	S
M-036-01.bmp	M-036-09.bmp	S
M-036-01.bmp	M-036-10.bmp	S
M-036-01.bmp	M-036-11.bmp	S
M-036-01.bmp	M-036-12.bmp	S
M-036-01.bmp	M-036-13.bmp	S
M-036-01.bmp	M-036-14.bmp	S
M-036-01.bmp	M-036-15.bmp	S
M-036-01.bmp	M-036-16.bmp	S
M-036-01.bmp	M-036-17.bmp	S
M-036-01.bmp	M-036-18.bmp	S
M-036-01.bmp	M-036-19.bmp	S
M-036-01.bmp	M-036-20.bmp	S
M-036-01.bmp	M-036-21.bmp	S
M-036-01.bmp	M-036-22.bmp	S
M-036-01.bmp	M-036-23.bmp	S
M-036-01.bmp	M-036-24.bmp	S
M-036-01.bmp	M-036-25.bmp	S
M-036-01.bmp	M-036-26.bmp	S
M-037-01.bmp	M-037-02.bmp	S
M-037-01.bmp	M-037-03.bmp	S
M-037-01.bmp	M-037-04.bmp	S
M-037-01.bmp	M-037-05.bmp	S
M-037-01.bmp	M-037-06.bmp	S
M-037-01.bmp	M-037-07.bmp	S
M-037-01.bmp	M-037-08.bmp	S
M-037-01.bmp	M-037-09.bmp	S
M-037-01.bmp	M-037-10.bmp	S
M-037-01.bmp	M-037-11.bmp	S
M-037-01.bmp	M-037-12.bmp	S
M-037-01.bmp	M-037-13.bmp	S
M-037-01.bmp	M-037-14.bmp	S
M-037-01.bmp	M-037-15.bmp	S
M-037-01.bmp	M-037-16.bmp	S
M-037-01.bmp	M-037-17.bmp	S
M-037-01.bmp	M-037-18.bmp	S
M-037-01.bmp	M-037-19.bmp	S
M-037-01.bmp	M-037-20.bmp	S
M-037-01.bmp	M-037-21.bmp	S
M-037-01.bmp	M-037-22.bmp	S
M-037-01.bmp	M-037-23.bmp	S
M-037-01.bmp	M-037-24.bmp	S
M-037-01.bmp	M-037-25.bmp	S
M-037-01.bmp	M-037-26.bmp	S
M-038-01.bmp	M-038-02.bmp	S
M-038-01.bmp	M-038-03.bmp	S
M-038-01.bmp	M-038-04.bmp	S
M-038-01.bmp	M-038-05.bmp	S
M-038-01.bmp	M-038-06.bmp	S
M-038-01.bmp	M-038-07.bmp	S
M-038-01.bmp	M-038-08.bmp	S
M-038-01.bmp	M-038-09.bmp	S
M-038-01.bmp	M-038-10.bmp	S
M-038-01.bmp	M-038-11.bmp	S
M-038-01.bmp	M-038-12.bmp	S
M-038-01.bmp	M-038-13.bmp	S
M-038-01.bmp	M-038-14.bmp	S
M-038-01.bmp	M-038-15.bmp	S
M-038-01.bmp	M-038-16.bmp	S
M-038-01.bmp	M-038-17.bmp	S
M-038-01.bmp	M-038-18.bmp	S
M-038-01.bmp	M-038-19.bmp	S
M-038-01.bmp	M-038-20.bmp	S
M-038-01.bmp	M-038-21.bmp	S
M-038-01.bmp	M-038-22.bmp	S
M-038-01.bmp	M-038-23.bmp	S
M-038-01.bmp	M-038-24.bmp	S
M-038-01.bmp	M-038-25.bmp	S
M-038-01.bmp	M-038-26.bmp	S
M-039-01.bmp	M-039-02.bmp	S
M-039-01.bmp	M-039-03.bmp	S
M-039-01.bmp	M-039-04.bmp	S
M-039-01.bmp	M-039-05.bmp	S
M-039-01.bmp	M-039-06.bmp	S
M-039-01.bmp	M-039-07.bmp	S
M-039-01.bmp	M-039-08.bmp	S
M-039-01.bmp	M-039-09.bmp	S
M-039-01.bmp	M-039-10.bmp	S
M-039-01.bmp	M-039-11.bmp	S
M-039-01.bmp	M-039-12.bmp	S
M-039-01.bmp	M-039-13.bmp	S
M-039-01.bmp	M-039-14.bmp	S
M-039-01.bmp	M-039-15.bmp	S
M-039-01.bmp	M-039-16.bmp	S
M-039-01.bmp	M-039-17.bmp	S
M-039-01.bmp	M-039-18.bmp	S
M-039-01.bmp	M-039-19.bmp	S
M-039-01.bmp	M-039-20.bmp	S
M-039-01.bmp	M-039-21.bmp	S
M-039-01.bmp	M-039-22.bmp	S
M-039-01.bmp	M-039-23.bmp	S
M-039-01.bmp	M-039-24.bmp	S
M-039-01.bmp	M-039-25.bmp	S
M-039-01.bmp	M-039-26.bmp	S
M-040-01.bmp	M-040-02.bmp	S
M-040-01.bmp	M-040-03.bmp	S
M-040-01.bmp	M-040-04.bmp	S
M-040-01.bmp	M-040-05.bmp	S
M-040-01.bmp	M-040-06.bmp	S
M-040-01.bmp	M-040-07.bmp	S
M-040-01.bmp	M-040-08.bmp	S
M-040-01.bmp	M-040-09.bmp	S
M-040-01.bmp	M-040-10.bmp	S
M-040-01.bmp	M-040-11.bmp	S
M-040-01.bmp	M-040-12.bmp	S
M-040-01.bmp	M-040-13.bmp	S
M-040-01.bmp	M-040-14.bmp	S
M-040-01.bmp	M-040-15.bmp	S
M-040-01.bmp	M-040-16.bmp	S
M-040-01.bmp	M-040-17.bmp	S
M-040-01.bmp	M-040-18.bmp	S
M-040-01.bmp	M-040-19.bmp	S
M-040-01.bmp	M-040-20.bmp	S
M-040-01.bmp	M-040-21.bmp	S
M-040-01.bmp	M-040-22.bmp	S
M-040-01.bmp	M-040-23.bmp	S
M-040-01.bmp	M-040-24.bmp	S
M-040-01.bmp	M-040-25.bmp	S
M-040-01.bmp	M-040-26.bmp	S
M-041-01.bmp	M-041-02.bmp	S
M-041-01.bmp	M-041-03.bmp	S
M-041-01.bmp	M-041-04.bmp	S
M-041-01.bmp	M-041-05.bmp	S
M-041-01.bmp	M-041-06.bmp	S
M-041-01.bmp	M-041-07.bmp	S
M-041-01.bmp	M-041-08.bmp	S
M-041-01.bmp	M-041-09.bmp	S
M-041-01.bmp	M-041-10.bmp	S
M-041-01.bmp	M-041-11.bmp	S
M-041-01.bmp	M-041-12.bmp	S
M-041-01.bmp	M-041-13.bmp	S
M-041-01.bmp	M-041-14.bmp	S
M-041-01.bmp	M-041-15.bmp	S
M-041-01.bmp	M-041-16.bmp	S
M-041-01.bmp	M-041-17.bmp	S
M-041-01.bmp	M-041-18.bmp	S
M-041-01.bmp	M-041-19.bmp	S
M-041-01.bmp	M-041-20.bmp	S
M-041-01.bmp	M-041-21.bmp	S
M-041-01.bmp	M-041-22.bmp	S
M-041-01.bmp	M-041-23.bmp	S
M-041-01.bmp	M-041-24.bmp	S
M-041-01.bmp	M-041-25.bmp	S
M-041-01.bmp	M-041-26.bmp	S
M-042-01.bmp	M-042-02.bmp	S
M-042-01.bmp	M-042-03.bmp	S
M-042-01.bmp	M-042-04.bmp	S
M-042-01.bmp	M-042-05.bmp	S
M-042-01.bmp	M-042-06.bmp	S
M-042-01.bmp	M-042-07.bmp	S
M-042-01.bmp	M-042-08.bmp	S
M-042-01.bmp	M-042-09.bmp	S
M-042-01.bmp	M-042-10.bmp	S
M-042-01.bmp	M-042-11.bmp	S
M-042-01.bmp	M-042-12.bmp	S
M-042-01.bmp	M-042-13.bmp	S
M-042-01.bmp	M-042-14.bmp	S
M-042-01.bmp	M-042-15.bmp	S
M-042-01.bmp	M-042-16.bmp	S
M-042-01.bmp	M-042-17.bmp	S
M-042-01.bmp	M-042-18.bmp	S
M-042-01.bmp	M-042-19.bmp	S
M-042-01.bmp	M-042-20.bmp	S
M-042-01.bmp	M-042-21.bmp	S
M-042-01.bmp	M-042-22.bmp	S
M-042-01.bmp	M-042-23.bmp	S
M-042-01.bmp	M-042-24.bmp	S
M-042-01.bmp	M-042-25.bmp	S
M-042-01.bmp	M-042-26.bmp	S
M-043-01.bmp	M-043-02.bmp	S
M-043-01.bmp	M-043-03.bmp	S
M-043-01.bmp	M-043-04.bmp	S
M-043-01.bmp	M-043-05.bmp	S
M-043-01.bmp	M-043-06.bmp	S
M-043-01.bmp	M-043-07.bmp	S
M-043-01.bmp	M-043-08.bmp	S
M-043-01.bmp	M-043-09.bmp	S
M-043-01.bmp	M-043-10.bmp	S
M-043-01.bmp	M-043-11.bmp	S
M-043-01.bmp	M-043-12.bmp	S
M-043-01.bmp	M-043-13.bmp	S
M-043-01.bmp	M-043-14.bmp	S
M-043-01.bmp	M-043-15.bmp	S
M-043-01.bmp	M-043-16.bmp	S
M-043-01.bmp	M-043-17.bmp	S
M-043-01.bmp	M-043-18.bmp	S
M-043-01.bmp	M-043-19.bmp	S
M-043-01.bmp	M-043-20.bmp	S
M-043-01.bmp	M-043-21.bmp	S
M-043-01.bmp	M-043-22.bmp	S
M-043-01.bmp	M-043-23.bmp	S
M-043-01.bmp	M-043-24.bmp	S
M-043-01.bmp	M-043-25.bmp	S
M-043-01.bmp	M-043-26.bmp	S
M-044-01.bmp	M-044-02.bmp	S
M-044-01.bmp	M-044-03.bmp	S
M-044-01.bmp	M-044-04.bmp	S
M-044-01.bmp	M-044-05.bmp	S
M-044-01.bmp	M-044-06.bmp	S
M-044-01.bmp	M-044-07.bmp	S
M-044-01.bmp	M-044-08.bmp	S
M-044-01.bmp	M-044-09.bmp	S
M-044-01.bmp	M-044-10.bmp	S
M-044-01.bmp	M-044-11.bmp	S
M-044-01.bmp	M-044-12.bmp	S
M-044-01.bmp	M-044-13.bmp	S
M-044-01.bmp	M-044-14.bmp	S
M-044-01.bmp	M-044-15.bmp	S
M-044-01.bmp	M-044-16.bmp	S
M-044-01.bmp	M-044-17.bmp	S
M-044-01.bmp	M-044-18.bmp	S
M-044-01.bmp	M-044-19.bmp	S
M-044-01.bmp	M-044-20.bmp	S
M-044-01.bmp	M-044-21.bmp	S
M-044-01.bmp	M-044-22.bmp	S
M-044-01.bmp	M-044-23.bmp	S
M-044-01.bmp	M-044-24.bmp	S
M-044-01.bmp	M-044-25.bmp	S
M-044-01.bmp	M-044-26.bmp	S
M-045-01.bmp	M-045-02.bmp	S
M-045-01.bmp	M-045-03.bmp	S
M-045-01.bmp	M-045-04.bmp	S
M-045-01.bmp	M-045-05.bmp	S
M-045-01.bmp	M-045-06.bmp	S
M-045-01.bmp	M-045-07.bmp	S
M-045-01.bmp	M-045-08.bmp	S
M-045-01.bmp	M-045-09.bmp	S
M-045-01.bmp	M-045-10.bmp	S
M-045-01.bmp	M-045-11.bmp	S
M-045-01.bmp	M-045-12.bmp	S
M-045-01.bmp	M-045-13.bmp	S
M-045-01.bmp	M-045-14.bmp	S
M-045-01.bmp	M-045-15.bmp	S
M-045-01.bmp	M-045-16.bmp	S
M-045-01.bmp	M-045-17.bmp	S
M-045-01.bmp	M-045-18.bmp	S
M-045-01.bmp	M-045-19.bmp	S
M-045-01.bmp	M-045-20.bmp	S
M-045-01.bmp	M-045-21.bmp	S
M-045-01.bmp	M-045-22.bmp	S
M-045-01.bmp	M-045-23.bmp	S
M-045-01.bmp	M-045-24.bmp	S
M-045-01.bmp	M-045-25.bmp	S
M-045-01.bmp	M-045-26.bmp	S
M-046-01.bmp	M-046-02.bmp	S
M-046-01.bmp	M-046-03.bmp	S
M-046-01.bmp	M-046-04.bmp	S
M-046-01.bmp	M-046-05.bmp	S
M-046-01.bmp	M-046-06.bmp	S
M-046-01.bmp	M-046-07.bmp	S
M-046-01.bmp	M-046-08.bmp	S
M-046-01.bmp	M-046-09.bmp	S
M-046-01.bmp	M-046-10.bmp	S
M-046-01.bmp	M-046-11.bmp	S
M-046-01.bmp	M-046-12.bmp	S
M-046-01.bmp	M-046-13.bmp	S
M-046-01.bmp	M-046-14.bmp	S
M-046-01.bmp	M-046-15.bmp	S
M-046-01.bmp	M-046-16.bmp	S
M-046-01.bmp	M-046-17.bmp	S
M-046-01.bmp	M-046-18.bmp	S
M-046-01.bmp	M-046-19.bmp	S
M-046-01.bmp	M-046-20.bmp	S
M-046-01.bmp	M-046-21.bmp	S
M-046-01.bmp	M-046-22.bmp	S
M-046-01.bmp	M-046-23.bmp	S
M-046-01.bmp	M-046-24.bmp	S
M-046-01.bmp	M-046-25.bmp	S
M-046-01.bmp	M-046-26.bmp	S
M-047-01.bmp	M-047-02.bmp	S
M-047-01.bmp	M-047-03.bmp	S
M-047-01.bmp	M-047-04.bmp	S
M-047-01.bmp	M-047-05.bmp	S
M-047-01.bmp	M-047-06.bmp	S
M-047-01.bmp	M-047-07.bmp	S
M-047-01.bmp	M-047-08.bmp	S
M-047-01.bmp	M-047-09.bmp	S
M-047-01.bmp	M-047-10.bmp	S
M-047-01.bmp	M-047-11.bmp	S
M-047-01.bmp	M-047-12.bmp	S
M-047-01.bmp	M-047-13.bmp	S
M-047-01.bmp	M-047-14.bmp	S
M-047-01.bmp	M-047-15.bmp	S
M-047-01.bmp	M-047-16.bmp	S
M-047-01.bmp	M-047-17.bmp	S
M-047-01.bmp	M-047-18.bmp	S
M-047-01.bmp	M-047-19.bmp	S
M-047-01.bmp	M-047-20.bmp	S
M-047-01.bmp	M-047-21.bmp	S
M-047-01.bmp	M-047-22.bmp	S
M-047-01.bmp	M-047-23.bmp	S
M-047-01.bmp	M-047-24.bmp	S
M-047-01.bmp	M-047-25.bmp	S
M-047-01.bmp	M-047-26.bmp	S
M-048-01.bmp	M-048-02.bmp	S
M-048-01.bmp	M-048-03.bmp	S
M-048-01.bmp	M-048-04.bmp	S
M-048-01.bmp	M-048-05.bmp	S
M-048-01.bmp	M-048-06.bmp	S
M-048-01.bmp	M-048-07.bmp	S
M-048-01.bmp	M-048-08.bmp	S
M-048-01.bmp	M-048-09.bmp	S
M-048-01.bmp	M-048-10.bmp	S
M-048-01.bmp	M-048-11.bmp	S
M-048-01.bmp	M-048-12.bmp	S
M-048-01.bmp	M-048-13.bmp	S
M-048-01.bmp	M-048-14.bmp	S
M-048-01.bmp	M-048-15.bmp	S
M-048-01.bmp	M-048-16.bmp	S
M-048-01.bmp	M-048-17.bmp	S
M-048-01.bmp	M-048-18.bmp	S
M-048-01.bmp	M-048-19.bmp	S
M-048-01.bmp	M-048-20.bmp	S
M-048-01.bmp	M-048-21.bmp	S
M-048-01.bmp	M-048-22.bmp	S
M-048-01.bmp	M-048-23.bmp	S
M-048-01.bmp	M-048-24.bmp	S
M-048-01.bmp	M-048-25.bmp	S
M-048-01.bmp	M-048-26.bmp	S
M-049-01.bmp	M-049-02.bmp	S
M-049-01.bmp	M-049-03.bmp	S
M-049-01.bmp	M-049-04.bmp	S
M-049-01.bmp	M-049-05.bmp	S
M-049-01.bmp	M-049-06.bmp	S
M-049-01.bmp	M-049-07.bmp	S
M-049-01.bmp	M-049-08.bmp	S
M-049-01.bmp	M-049-09.bmp	S
M-049-01.bmp	M-049-10.bmp	S
M-049-01.bmp	M-049-11.bmp	S
M-049-01.bmp	M-049-12.bmp	S
M-049-01.bmp	M-049-13.bmp	S
M-049-01.bmp	M-049-14.bmp	S
M-049-01.bmp	M-049-15.bmp	S
M-049-01.bmp	M-049-16.bmp	S
M-049-01.bmp	M-049-17.bmp	S
M-049-01.bmp	M-049-18.bmp	S
M-049-01.bmp	M-049-19.bmp	S
M-049-01.bmp	M-049-20.bmp	S
M-049-01.bmp	M-049-21.bmp	S
M-049-01.bmp	M-049-22.bmp	S
M-049-01.bmp	M-049-23.bmp	S
M-049-01.bmp	M-049-24.bmp	S
M-049-01.bmp	M-049-25.bmp	S
M-049-01.bmp	M-049-26.bmp	S
M-050-01.bmp	M-050-02.bmp	S
M-050-01.bmp	M-050-03.bmp	S
M-050-01.bmp	M-050-04.bmp	S
M-050-01.bmp	M-050-05.bmp	S
M-050-01.bmp	M-050-06.bmp	S
M-050-01.bmp	M-050-07.bmp	S
M-050-01.bmp	M-050-08.bmp	S
M-050-01.bmp	M-050-09.bmp	S
M-050-01.bmp	M-050-10.bmp	S
M-050-01.bmp	M-050-11.bmp	S
M-050-01.bmp	M-050-12.bmp	S
M-050-01.bmp	M-050-13.bmp	S
M-050-01.bmp	M-050-14.bmp	S
M-050-01.bmp	M-050-15.bmp	S
M-050-01.bmp	M-050-16.bmp	S
M-050-01.bmp	M-050-17.bmp	S
M-050-01.bmp	M-050-18.bmp	S
M-050-01.bmp	M-050-19.bmp	S
M-050-01.bmp	M-050-20.bmp	S
M-050-01.bmp	M-050-21.bmp	S
M-050-01.bmp	M-050-22.bmp	S
M-050-01.bmp	M-050-23.bmp	S
M-050-01.bmp	M-050-24.bmp	S
M-050-01.bmp	M-050-25.bmp	S
M-050-01.bmp	M-050-26.bmp	S
W-001-01.bmp	W-001-02.bmp	S
W-001-01.bmp	W-001-03.bmp	S
W-001-01.bmp	W-001-04.bmp	S
W-001-01.bmp	W-001-05.bmp	S
W-001-01.bmp	W-001-06.bmp	S
W-001-01.bmp	W-001-07.bmp	S
W-001-01.bmp	W-001-08.bmp	S
W-001-01.bmp	W-001-09.bmp	S
W-001-01.bmp	W-001-10.bmp	S
W-001-01.bmp	W-001-11.bmp	S
W-001-01.bmp	W-001-12.bmp	S
W-001-01.bmp	W-001-13.bmp	S
W-001-01.bmp	W-001-14.bmp	S
W-001-01.bmp	W-001-15.bmp	S
W-001-01.bmp	W-001-16.bmp	S
W-001-01.bmp	W-001-17.bmp	S
W-001-01.bmp	W-001-18.bmp	S
W-001-01.bmp	W-001-19.bmp	S
W-001-01.bmp	W-001-20.bmp	S
W-001-01.bmp	W-001-21.bmp	S
W-001-01.bmp	W-001-22.bmp	S
W-001-01.bmp	W-001-23.bmp	S
W-001-01.bmp	W-001-24.bmp	S
W-001-01.bmp	W-001-25.bmp	S
W-001-01.bmp	W-001-26.bmp	S
W-002-01.bmp	W-002-02.bmp	S
W-002-01.bmp	W-002-03.bmp	S
W-002-01.bmp	W-002-04.bmp	S
W-002-01.bmp	W-002-05.bmp	S
W-002-01.bmp	W-002-06.bmp	S
W-002-01.bmp	W-002-07.bmp	S
W-002-01.bmp	W-002-08.bmp	S
W-002-01.bmp	W-002-09.bmp	S
W-002-01.bmp	W-002-10.bmp	S
W-002-01.bmp	W-002-11.bmp	S
W-002-01.bmp	W-002-12.bmp	S
W-002-01.bmp	W-002-13.bmp	S
W-002-01.bmp	W-002-14.bmp	S
W-002-01.bmp	W-002-15.bmp	S
W-002-01.bmp	W-002-16.bmp	S
W-002-01.bmp	W-002-17.bmp	S
W-002-01.bmp	W-002-18.bmp	S
W-002-01.bmp	W-002-19.bmp	S
W-002-01.bmp	W-002-20.bmp	S
W-002-01.bmp	W-002-21.bmp	S
W-002-01.bmp	W-002-22.bmp	S
W-002-01.bmp	W-002-23.bmp	S
W-002-01.bmp	W-002-24.bmp	S
W-002-01.bmp	W-002-25.bmp	S
W-002-01.bmp	W-002-26.bmp	S
W-003-01.bmp	W-003-02.bmp	S
W-003-01.bmp	W-003-03.bmp	S
W-003-01.bmp	W-003-04.bmp	S
W-003-01.bmp	W-003-05.bmp	S
W-003-01.bmp	W-003-06.bmp	S
W-003-01.bmp	W-003-07.bmp	S
W-003-01.bmp	W-003-08.bmp	S
W-003-01.bmp	W-003-09.bmp	S
W-003-01.bmp	W-003-10.bmp	S
W-003-01.bmp	W-003-11.bmp	S
W-003-01.bmp	W-003-12.bmp	S
W-003-01.bmp	W-003-13.bmp	S
W-003-01.bmp	W-003-14.bmp	S
W-003-01.bmp	W-003-15.bmp	S
W-003-01.bmp	W-003-16.bmp	S
W-003-01.bmp	W-003-17.bmp	S
W-003-01.bmp	W-003-18.bmp	S
W-003-01.bmp	W-003-19.bmp	S
W-003-01.bmp	W-003-20.bmp	S
W-003-01.bmp	W-003-21.bmp	S
W-003-01.bmp	W-003-22.bmp	S
W-003-01.bmp	W-003-23.bmp	S
W-003-01.bmp	W-003-24.bmp	S
W-003-01.bmp	W-003-25.bmp	S
W-003-01.bmp	W-003-26.bmp	S
W-004-01.bmp	W-004-02.bmp	S
W-004-01.bmp	W-004-03.bmp	S
W-004-01.bmp	W-004-04.bmp	S
W-004-01.bmp	W-004-05.bmp	S
W-004-01.bmp	W-004-06.bmp	S
W-004-01.bmp	W-004-07.bmp	S
W-004-01.bmp	W-004-08.bmp	S
W-004-01.bmp	W-004-09.bmp	S
W-004-01.bmp	W-004-10.bmp	S
W-004-01.bmp	W-004-11.bmp	S
W-004-01.bmp	W-004-12.bmp	S
W-004-01.bmp	W-004-13.bmp	S
W-004-01.bmp	W-004-14.bmp	S
W-004-01.bmp	W-004-15.bmp	S
W-004-01.bmp	W-004-16.bmp	S
W-004-01.bmp	W-004-17.bmp	S
W-004-01.bmp	W-004-18.bmp	S
W-004-01.bmp	W-004-19.bmp	S
W-004-01.bmp	W-004-20.bmp	S
W-004-01.bmp	W-004-21.bmp	S
W-004-01.bmp	W-004-22.bmp	S
W-004-01.bmp	W-004-23.bmp	S
W-004-01.bmp	W-004-24.bmp	S
W-004-01.bmp	W-004-25.bmp	S
W-004-01.bmp	W-004-26.bmp	S
W-005-01.bmp	W-005-02.bmp	S
W-005-01.bmp	W-005-03.bmp	S
W-005-01.bmp	W-005-04.bmp	S
W-005-01.bmp	W-005-05.bmp	S
W-005-01.bmp	W-005-06.bmp	S
W-005-01.bmp	W-005-07.bmp	S
W-005-01.bmp	W-005-08.bmp	S
W-005-01.bmp	W-005-09.bmp	S
W-005-01.bmp	W-005-10.bmp	S
W-005-01.bmp	W-005-11.bmp	S
W-005-01.bmp	W-005-12.bmp	S
W-005-01.bmp	W-005-13.bmp	S
W-005-01.bmp	W-005-14.bmp	S
W-005-01.bmp	W-005-15.bmp	S
W-005-01.bmp	W-005-16.bmp	S
W-005-01.bmp	W-005-17.bmp	S
W-005-01.bmp	W-005-18.bmp	S
W-005-01.bmp	W-005-19.bmp	S
W-005-01.bmp	W-005-20.bmp	S
W-005-01.bmp	W-005-21.bmp	S
W-005-01.bmp	W-005-22.bmp	S
W-005-01.bmp	W-005-23.bmp	S
W-005-01.bmp	W-005-24.bmp	S
W-005-01.bmp	W-005-25.bmp	S
W-005-01.bmp	W-005-26.bmp	S
W-006-01.bmp	W-006-02.bmp	S
W-006-01.bmp	W-006-03.bmp	S
W-006-01.bmp	W-006-04.bmp	S
W-006-01.bmp	W-006-05.bmp	S
W-006-01.bmp	W-006-06.bmp	S
W-006-01.bmp	W-006-07.bmp	S
W-006-01.bmp	W-006-08.bmp	S
W-006-01.bmp	W-006-09.bmp	S
W-006-01.bmp	W-006-10.bmp	S
W-006-01.bmp	W-006-11.bmp	S
W-006-01.bmp	W-006-12.bmp	S
W-006-01.bmp	W-006-13.bmp	S
W-006-01.bmp	W-006-14.bmp	S
W-006-01.bmp	W-006-15.bmp	S
W-006-01.bmp	W-006-16.bmp	S
W-006-01.bmp	W-006-17.bmp	S
W-006-01.bmp	W-006-18.bmp	S
W-006-01.bmp	W-006-19.bmp	S
W-006-01.bmp	W-006-20.bmp	S
W-006-01.bmp	W-006-21.bmp	S
W-006-01.bmp	W-006-22.bmp	S
W-006-01.bmp	W-006-23.bmp	S
W-006-01.bmp	W-006-24.bmp	S
W-006-01.bmp	W-006-25.bmp	S
W-006-01.bmp	W-006-26.bmp	S
W-007-01.bmp	W-007-02.bmp	S
W-007-01.bmp	W-007-03.bmp	S
W-007-01.bmp	W-007-04.bmp	S
W-007-01.bmp	W-007-05.bmp	S
W-007-01.bmp	W-007-06.bmp	S
W-007-01.bmp	W-007-07.bmp	S
W-007-01.bmp	W-007-08.bmp	S
W-007-01.bmp	W-007-09.bmp	S
W-007-01.bmp	W-007-10.bmp	S
W-007-01.bmp	W-007-11.bmp	S
W-007-01.bmp	W-007-12.bmp	S
W-007-01.bmp	W-007-13.bmp	S
W-007-01.bmp	W-007-14.bmp	S
W-007-01.bmp	W-007-15.bmp	S
W-007-01.bmp	W-007-16.bmp	S
W-007-01.bmp	W-007-17.bmp	S
W-007-01.bmp	W-007-18.bmp	S
W-007-01.bmp	W-007-19.bmp	S
W-007-01.bmp	W-007-20.bmp	S
W-007-01.bmp	W-007-21.bmp	S
W-007-01.bmp	W-007-22.bmp	S
W-007-01.bmp	W-007-23.bmp	S
W-007-01.bmp	W-007-24.bmp	S
W-007-01.bmp	W-007-25.bmp	S
W-007-01.bmp	W-007-26.bmp	S
W-008-01.bmp	W-008-02.bmp	S
W-008-01.bmp	W-008-03.bmp	S
W-008-01.bmp	W-008-04.bmp	S
W-008-01.bmp	W-008-05.bmp	S
W-008-01.bmp	W-008-06.bmp	S
W-008-01.bmp	W-008-07.bmp	S
W-008-01.bmp	W-008-08.bmp	S
W-008-01.bmp	W-008-09.bmp	S
W-008-01.bmp	W-008-10.bmp	S
W-008-01.bmp	W-008-11.bmp	S
W-008-01.bmp	W-008-12.bmp	S
W-008-01.bmp	W-008-13.bmp	S
W-008-01.bmp	W-008-14.bmp	S
W-008-01.bmp	W-008-15.bmp	S
W-008-01.bmp	W-008-16.bmp	S
W-008-01.bmp	W-008-17.bmp	S
W-008-01.bmp	W-008-18.bmp	S
W-008-01.bmp	W-008-19.bmp	S
W-008-01.bmp	W-008-20.bmp	S
W-008-01.bmp	W-008-21.bmp	S
W-008-01.bmp	W-008-22.bmp	S
W-008-01.bmp	W-008-23.bmp	S
W-008-01.bmp	W-008-24.bmp	S
W-008-01.bmp	W-008-25.bmp	S
W-008-01.bmp	W-008-26.bmp	S
W-009-01.bmp	W-009-02.bmp	S
W-009-01.bmp	W-009-03.bmp	S
W-009-01.bmp	W-009-04.bmp	S
W-009-01.bmp	W-009-05.bmp	S
W-009-01.bmp	W-009-06.bmp	S
W-009-01.bmp	W-009-07.bmp	S
W-009-01.bmp	W-009-08.bmp	S
W-009-01.bmp	W-009-09.bmp	S
W-009-01.bmp	W-009-10.bmp	S
W-009-01.bmp	W-009-11.bmp	S
W-009-01.bmp	W-009-12.bmp	S
W-009-01.bmp	W-009-13.bmp	S
W-009-01.bmp	W-009-14.bmp	S
W-009-01.bmp	W-009-15.bmp	S
W-009-01.bmp	W-009-16.bmp	S
W-009-01.bmp	W-009-17.bmp	S
W-009-01.bmp	W-009-18.bmp	S
W-009-01.bmp	W-009-19.bmp	S
W-009-01.bmp	W-009-20.bmp	S
W-009-01.bmp	W-009-21.bmp	S
W-009-01.bmp	W-009-22.bmp	S
W-009-01.bmp	W-009-23.bmp	S
W-009-01.bmp	W-009-24.bmp	S
W-009-01.bmp	W-009-25.bmp	S
W-009-01.bmp	W-009-26.bmp	S
W-010-01.bmp	W-010-02.bmp	S
W-010-01.bmp	W-010-03.bmp	S
W-010-01.bmp	W-010-04.bmp	S
W-010-01.bmp	W-010-05.bmp	S
W-010-01.bmp	W-010-06.bmp	S
W-010-01.bmp	W-010-07.bmp	S
W-010-01.bmp	W-010-08.bmp	S
W-010-01.bmp	W-010-09.bmp	S
W-010-01.bmp	W-010-10.bmp	S
W-010-01.bmp	W-010-11.bmp	S
W-010-01.bmp	W-010-12.bmp	S
W-010-01.bmp	W-010-13.bmp	S
W-010-01.bmp	W-010-14.bmp	S
W-010-01.bmp	W-010-15.bmp	S
W-010-01.bmp	W-010-16.bmp	S
W-010-01.bmp	W-010-17.bmp	S
W-010-01.bmp	W-010-18.bmp	S
W-010-01.bmp	W-010-19.bmp	S
W-010-01.bmp	W-010-20.bmp	S
W-010-01.bmp	W-010-21.bmp	S
W-010-01.bmp	W-010-22.bmp	S
W-010-01.bmp	W-010-23.bmp	S
W-010-01.bmp	W-010-24.bmp	S
W-010-01.bmp	W-010-25.bmp	S
W-010-01.bmp	W-010-26.bmp	S
W-011-01.bmp	W-011-02.bmp	S
W-011-01.bmp	W-011-03.bmp	S
W-011-01.bmp	W-011-04.bmp	S
W-011-01.bmp	W-011-05.bmp	S
W-011-01.bmp	W-011-06.bmp	S
W-011-01.bmp	W-011-07.bmp	S
W-011-01.bmp	W-011-08.bmp	S
W-011-01.bmp	W-011-09.bmp	S
W-011-01.bmp	W-011-10.bmp	S
W-011-01.bmp	W-011-11.bmp	S
W-011-01.bmp	W-011-12.bmp	S
W-011-01.bmp	W-011-13.bmp	S
W-011-01.bmp	W-011-14.bmp	S
W-011-01.bmp	W-011-15.bmp	S
W-011-01.bmp	W-011-16.bmp	S
W-011-01.bmp	W-011-17.bmp	S
W-011-01.bmp	W-011-18.bmp	S
W-011-01.bmp	W-011-19.bmp	S
W-011-01.bmp	W-011-20.bmp	S
W-011-01.bmp	W-011-21.bmp	S
W-011-01.bmp	W-011-22.bmp	S
W-011-01.bmp	W-011-23.bmp	S
W-011-01.bmp	W-011-24.bmp	S
W-011-01.bmp	W-011-25.bmp	S
W-011-01.bmp	W-011-26.bmp	S
W-012-01.bmp	W-012-02.bmp	S
W-012-01.bmp	W-012-03.bmp	S
W-012-01.bmp	W-012-04.bmp	S
W-012-01.bmp	W-012-05.bmp	S
W-012-01.bmp	W-012-06.bmp	S
W-012-01.bmp	W-012-07.bmp	S
W-012-01.bmp	W-012-08.bmp	S
W-012-01.bmp	W-012-09.bmp	S
W-012-01.bmp	W-012-10.bmp	S
W-012-01.bmp	W-012-11.bmp	S
W-012-01.bmp	W-012-12.bmp	S
W-012-01.bmp	W-012-13.bmp	S
W-012-01.bmp	W-012-14.bmp	S
W-012-01.bmp	W-012-15.bmp	S
W-012-01.bmp	W-012-16.bmp	S
W-012-01.bmp	W-012-17.bmp	S
W-012-01.bmp	W-012-18.bmp	S
W-012-01.bmp	W-012-19.bmp	S
W-012-01.bmp	W-012-20.bmp	S
W-012-01.bmp	W-012-21.bmp	S
W-012-01.bmp	W-012-22.bmp	S
W-012-01.bmp	W-012-23.bmp	S
W-012-01.bmp	W-012-24.bmp	S
W-012-01.bmp	W-012-25.bmp	S
W-012-01.bmp	W-012-26.bmp	S
W-013-01.bmp	W-013-02.bmp	S
W-013-01.bmp	W-013-03.bmp	S
W-013-01.bmp	W-013-04.bmp	S
W-013-01.bmp	W-013-05.bmp	S
W-013-01.bmp	W-013-06.bmp	S
W-013-01.bmp	W-013-07.bmp	S
W-013-01.bmp	W-013-08.bmp	S
W-013-01.bmp	W-013-09.bmp	S
W-013-01.bmp	W-013-10.bmp	S
W-013-01.bmp	W-013-11.bmp	S
W-013-01.bmp	W-013-12.bmp	S
W-013-01.bmp	W-013-13.bmp	S
W-013-01.bmp	W-013-14.bmp	S
W-013-01.bmp	W-013-15.bmp	S
W-013-01.bmp	W-013-16.bmp	S
W-013-01.bmp	W-013-17.bmp	S
W-013-01.bmp	W-013-18.bmp	S
W-013-01.bmp	W-013-19.bmp	S
W-013-01.bmp	W-013-20.bmp	S
W-013-01.bmp	W-013-21.bmp	S
W-013-01.bmp	W-013-22.bmp	S
W-013-01.bmp	W-013-23.bmp	S
W-013-01.bmp	W-013-24.bmp	S
W-013-01.bmp	W-013-25.bmp	S
W-013-01.bmp	W-013-26.bmp	S
W-014-01.bmp	W-014-02.bmp	S
W-014-01.bmp	W-014-03.bmp	S
W-014-01.bmp	W-014-04.bmp	S
W-014-01.bmp	W-014-05.bmp	S
W-014-01.bmp	W-014-06.bmp	S
W-014-01.bmp	W-014-07.bmp	S
W-014-01.bmp	W-014-08.bmp	S
W-014-01.bmp	W-014-09.bmp	S
W-014-01.bmp	W-014-10.bmp	S
W-014-01.bmp	W-014-11.bmp	S
W-014-01.bmp	W-014-12.bmp	S
W-014-01.bmp	W-014-13.bmp	S
W-014-01.bmp	W-014-14.bmp	S
W-014-01.bmp	W-014-15.bmp	S
W-014-01.bmp	W-014-16.bmp	S
W-014-01.bmp	W-014-17.bmp	S
W-014-01.bmp	W-014-18.bmp	S
W-014-01.bmp	W-014-19.bmp	S
W-014-01.bmp	W-014-20.bmp	S
W-014-01.bmp	W-014-21.bmp	S
W-014-01.bmp	W-014-22.bmp	S
W-014-01.bmp	W-014-23.bmp	S
W-014-01.bmp	W-014-24.bmp	S
W-014-01.bmp	W-014-25.bmp	S
W-014-01.bmp	W-014-26.bmp	S
W-015-01.bmp	W-015-02.bmp	S
W-015-01.bmp	W-015-03.bmp	S
W-015-01.bmp	W-015-04.bmp	S
W-015-01.bmp	W-015-05.bmp	S
W-015-01.bmp	W-015-06.bmp	S
W-015-01.bmp	W-015-07.bmp	S
W-015-01.bmp	W-015-08.bmp	S
W-015-01.bmp	W-015-09.bmp	S
W-015-01.bmp	W-015-10.bmp	S
W-015-01.bmp	W-015-11.bmp	S
W-015-01.bmp	W-015-12.bmp	S
W-015-01.bmp	W-015-13.bmp	S
W-015-01.bmp	W-015-14.bmp	S
W-015-01.bmp	W-015-15.bmp	S
W-015-01.bmp	W-015-16.bmp	S
W-015-01.bmp	W-015-17.bmp	S
W-015-01.bmp	W-015-18.bmp	S
W-015-01.bmp	W-015-19.bmp	S
W-015-01.bmp	W-015-20.bmp	S
W-015-01.bmp	W-015-21.bmp	S
W-015-01.bmp	W-015-22.bmp	S
W-015-01.bmp	W-015-23.bmp	S
W-015-01.bmp	W-015-24.bmp	S
W-015-01.bmp	W-015-25.bmp	S
W-015-01.bmp	W-015-26.bmp	S
W-016-01.bmp	W-016-02.bmp	S
W-016-01.bmp	W-016-03.bmp	S
W-016-01.bmp	W-016-04.bmp	S
W-016-01.bmp	W-016-05.bmp	S
W-016-01.bmp	W-016-06.bmp	S
W-016-01.bmp	W-016-07.bmp	S
W-016-01.bmp	W-016-08.bmp	S
W-016-01.bmp	W-016-09.bmp	S
W-016-01.bmp	W-016-10.bmp	S
W-016-01.bmp	W-016-11.bmp	S
W-016-01.bmp	W-016-12.bmp	S
W-016-01.bmp	W-016-13.bmp	S
W-016-01.bmp	W-016-14.bmp	S
W-016-01.bmp	W-016-15.bmp	S
W-016-01.bmp	W-016-16.bmp	S
W-016-01.bmp	W-016-17.bmp	S
W-016-01.bmp	W-016-18.bmp	S
W-016-01.bmp	W-016-19.bmp	S
W-016-01.bmp	W-016-20.bmp	S
W-016-01.bmp	W-016-21.bmp	S
W-016-01.bmp	W-016-22.bmp	S
W-016-01.bmp	W-016-23.bmp	S
W-016-01.bmp	W-016-24.bmp	S
W-016-01.bmp	W-016-25.bmp	S
W-016-01.bmp	W-016-26.bmp	S
W-017-01.bmp	W-017-02.bmp	S
W-017-01.bmp	W-017-03.bmp	S
W-017-01.bmp	W-017-04.bmp	S
W-017-01.bmp	W-017-05.bmp	S
W-017-01.bmp	W-017-06.bmp	S
W-017-01.bmp	W-017-07.bmp	S
W-017-01.bmp	W-017-08.bmp	S
W-017-01.bmp	W-017-09.bmp	S
W-017-01.bmp	W-017-10.bmp	S
W-017-01.bmp	W-017-11.bmp	S
W-017-01.bmp	W-017-12.bmp	S
W-017-01.bmp	W-017-13.bmp	S
W-017-01.bmp	W-017-14.bmp	S
W-017-01.bmp	W-017-15.bmp	S
W-017-01.bmp	W-017-16.bmp	S
W-017-01.bmp	W-017-17.bmp	S
W-017-01.bmp	W-017-18.bmp	S
W-017-01.bmp	W-017-19.bmp	S
W-017-01.bmp	W-017-20.bmp	S
W-017-01.bmp	W-017-21.bmp	S
W-017-01.bmp	W-017-22.bmp	S
W-017-01.bmp	W-017-23.bmp	S
W-017-01.bmp	W-017-24.bmp	S
W-017-01.bmp	W-017-25.bmp	S
W-017-01.bmp	W-017-26.bmp	S
W-018-01.bmp	W-018-02.bmp	S
W-018-01.bmp	W-018-03.bmp	S
W-018-01.bmp	W-018-04.bmp	S
W-018-01.bmp	W-018-05.bmp	S
W-018-01.bmp	W-018-06.bmp	S
W-018-01.bmp	W-018-07.bmp	S
W-018-01.bmp	W-018-08.bmp	S
W-018-01.bmp	W-018-09.bmp	S
W-018-01.bmp	W-018-10.bmp	S
W-018-01.bmp	W-018-11.bmp	S
W-018-01.bmp	W-018-12.bmp	S
W-018-01.bmp	W-018-13.bmp	S
W-018-01.bmp	W-018-14.bmp	S
W-018-01.bmp	W-018-15.bmp	S
W-018-01.bmp	W-018-16.bmp	S
W-018-01.bmp	W-018-17.bmp	S
W-018-01.bmp	W-018-18.bmp	S
W-018-01.bmp	W-018-19.bmp	S
W-018-01.bmp	W-018-20.bmp	S
W-018-01.bmp	W-018-21.bmp	S
W-018-01.bmp	W-018-22.bmp	S
W-018-01.bmp	W-018-23.bmp	S
W-018-01.bmp	W-018-24.bmp	S
W-018-01.bmp	W-018-25.bmp	S
W-018-01.bmp	W-018-26.bmp	S
W-019-01.bmp	W-019-02.bmp	S
W-019-01.bmp	W-019-03.bmp	S
W-019-01.bmp	W-019-04.bmp	S
W-019-01.bmp	W-019-05.bmp	S
W-019-01.bmp	W-019-06.bmp	S
W-019-01.bmp	W-019-07.bmp	S
W-019-01.bmp	W-019-08.bmp	S
W-019-01.bmp	W-019-09.bmp	S
W-019-01.bmp	W-019-10.bmp	S
W-019-01.bmp	W-019-11.bmp	S
W-019-01.bmp	W-019-12.bmp	S
W-019-01.bmp	W-019-13.bmp	S
W-019-01.bmp	W-019-14.bmp	S
W-019-01.bmp	W-019-15.bmp	S
W-019-01.bmp	W-019-16.bmp	S
W-019-01.bmp	W-019-17.bmp	S
W-019-01.bmp	W-019-18.bmp	S
W-019-01.bmp	W-019-19.bmp	S
W-019-01.bmp	W-019-20.bmp	S
W-019-01.bmp	W-019-21.bmp	S
W-019-01.bmp	W-019-22.bmp	S
W-019-01.bmp	W-019-23.bmp	S
W-019-01.bmp	W-019-24.bmp	S
W-019-01.bmp	W-019-25.bmp	S
W-019-01.bmp	W-019-26.bmp	S
W-020-01.bmp	W-020-02.bmp	S
W-020-01.bmp	W-020-03.bmp	S
W-020-01.bmp	W-020-04.bmp	S
W-020-01.bmp	W-020-05.bmp	S
W-020-01.bmp	W-020-06.bmp	S
W-020-01.bmp	W-020-07.bmp	S
W-020-01.bmp	W-020-08.bmp	S
W-020-01.bmp	W-020-09.bmp	S
W-020-01.bmp	W-020-10.bmp	S
W-020-01.bmp	W-020-11.bmp	S
W-020-01.bmp	W-020-12.bmp	S
W-020-01.bmp	W-020-13.bmp	S
W-020-01.bmp	W-020-14.bmp	S
W-020-01.bmp	W-020-15.bmp	S
W-020-01.bmp	W-020-16.bmp	S
W-020-01.bmp	W-020-17.bmp	S
W-020-01.bmp	W-020-18.bmp	S
W-020-01.bmp	W-020-19.bmp	S
W-020-01.bmp	W-020-20.bmp	S
W-020-01.bmp	W-020-21.bmp	S
W-020-01.bmp	W-020-22.bmp	S
W-020-01.bmp	W-020-23.bmp	S
W-020-01.bmp	W-020-24.bmp	S
W-020-01.bmp	W-020-25.bmp	S
W-020-01.bmp	W-020-26.bmp	S
W-021-01.bmp	W-021-02.bmp	S
W-021-01.bmp	W-021-03.bmp	S
W-021-01.bmp	W-021-04.bmp	S
W-021-01.bmp	W-021-05.bmp	S
W-021-01.bmp	W-021-06.bmp	S
W-021-01.bmp	W-021-07.bmp	S
W-021-01.bmp	W-021-08.bmp	S
W-021-01.bmp	W-021-09.bmp	S
W-021-01.bmp	W-021-10.bmp	S
W-021-01.bmp	W-021-11.bmp	S
W-021-01.bmp	W-021-12.bmp	S
W-021-01.bmp	W-021-13.bmp	S
W-021-01.bmp	W-021-14.bmp	S
W-021-01.bmp	W-021-15.bmp	S
W-021-01.bmp	W-021-16.bmp	S
W-021-01.bmp	W-021-17.bmp	S
W-021-01.bmp	W-021-18.bmp	S
W-021-01.bmp	W-021-19.bmp	S
W-021-01.bmp	W-021-20.bmp	S
W-021-01.bmp	W-021-21.bmp	S
W-021-01.bmp	W-021-22.bmp	S
W-021-01.bmp	W-021-23.bmp	S
W-021-01.bmp	W-021-24.bmp	S
W-021-01.bmp	W-021-25.bmp	S
W-021-01.bmp	W-021-26.bmp	S
W-022-01.bmp	W-022-02.bmp	S
W-022-01.bmp	W-022-03.bmp	S
W-022-01.bmp	W-022-04.bmp	S
W-022-01.bmp	W-022-05.bmp	S
W-022-01.bmp	W-022-06.bmp	S
W-022-01.bmp	W-022-07.bmp	S
W-022-01.bmp	W-022-08.bmp	S
W-022-01.bmp	W-022-09.bmp	S
W-022-01.bmp	W-022-10.bmp	S
W-022-01.bmp	W-022-11.bmp	S
W-022-01.bmp	W-022-12.bmp	S
W-022-01.bmp	W-022-13.bmp	S
W-022-01.bmp	W-022-14.bmp	S
W-022-01.bmp	W-022-15.bmp	S
W-022-01.bmp	W-022-16.bmp	S
W-022-01.bmp	W-022-17.bmp	S
W-022-01.bmp	W-022-18.bmp	S
W-022-01.bmp	W-022-19.bmp	S
W-022-01.bmp	W-022-20.bmp	S
W-022-01.bmp	W-022-21.bmp	S
W-022-01.bmp	W-022-22.bmp	S
W-022-01.bmp	W-022-23.bmp	S
W-022-01.bmp	W-022-24.bmp	S
W-022-01.bmp	W-022-25.bmp	S
W-022-01.bmp	W-022-26.bmp	S
W-023-01.bmp	W-023-02.bmp	S
W-023-01.bmp	W-023-03.bmp	S
W-023-01.bmp	W-023-04.bmp	S
W-023-01.bmp	W-023-05.bmp	S
W-023-01.bmp	W-023-06.bmp	S
W-023-01.bmp	W-023-07.bmp	S
W-023-01.bmp	W-023-08.bmp	S
W-023-01.bmp	W-023-09.bmp	S
W-023-01.bmp	W-023-10.bmp	S
W-023-01.bmp	W-023-11.bmp	S
W-023-01.bmp	W-023-12.bmp	S
W-023-01.bmp	W-023-13.bmp	S
W-023-01.bmp	W-023-14.bmp	S
W-023-01.bmp	W-023-15.bmp	S
W-023-01.bmp	W-023-16.bmp	S
W-023-01.bmp	W-023-17.bmp	S
W-023-01.bmp	W-023-18.bmp	S
W-023-01.bmp	W-023-19.bmp	S
W-023-01.bmp	W-023-20.bmp	S
W-023-01.bmp	W-023-21.bmp	S
W-023-01.bmp	W-023-22.bmp	S
W-023-01.bmp	W-023-23.bmp	S
W-023-01.bmp	W-023-24.bmp	S
W-023-01.bmp	W-023-25.bmp	S
W-023-01.bmp	W-023-26.bmp	S
W-024-01.bmp	W-024-02.bmp	S
W-024-01.bmp	W-024-03.bmp	S
W-024-01.bmp	W-024-04.bmp	S
W-024-01.bmp	W-024-05.bmp	S
W-024-01.bmp	W-024-06.bmp	S
W-024-01.bmp	W-024-07.bmp	S
W-024-01.bmp	W-024-08.bmp	S
W-024-01.bmp	W-024-09.bmp	S
W-024-01.bmp	W-024-10.bmp	S
W-024-01.bmp	W-024-11.bmp	S
W-024-01.bmp	W-024-12.bmp	S
W-024-01.bmp	W-024-13.bmp	S
W-024-01.bmp	W-024-14.bmp	S
W-024-01.bmp	W-024-15.bmp	S
W-024-01.bmp	W-024-16.bmp	S
W-024-01.bmp	W-024-17.bmp	S
W-024-01.bmp	W-024-18.bmp	S
W-024-01.bmp	W-024-19.bmp	S
W-024-01.bmp	W-024-20.bmp	S
W-024-01.bmp	W-024-21.bmp	S
W-024-01.bmp	W-024-22.bmp	S
W-024-01.bmp	W-024-23.bmp	S
W-024-01.bmp	W-024-24.bmp	S
W-024-01.bmp	W-024-25.bmp	S
W-024-01.bmp	W-024-26.bmp	S
W-025-01.bmp	W-025-02.bmp	S
W-025-01.bmp	W-025-03.bmp	S
W-025-01.bmp	W-025-04.bmp	S
W-025-01.bmp	W-025-05.bmp	S
W-025-01.bmp	W-025-06.bmp	S
W-025-01.bmp	W-025-07.bmp	S
W-025-01.bmp	W-025-08.bmp	S
W-025-01.bmp	W-025-09.bmp	S
W-025-01.bmp	W-025-10.bmp	S
W-025-01.bmp	W-025-11.bmp	S
W-025-01.bmp	W-025-12.bmp	S
W-025-01.bmp	W-025-13.bmp	S
W-025-01.bmp	W-025-14.bmp	S
W-025-01.bmp	W-025-15.bmp	S
W-025-01.bmp	W-025-16.bmp	S
W-025-01.bmp	W-025-17.bmp	S
W-025-01.bmp	W-025-18.bmp	S
W-025-01.bmp	W-025-19.bmp	S
W-025-01.bmp	W-025-20.bmp	S
W-025-01.bmp	W-025-21.bmp	S
W-025-01.bmp	W-025-22.bmp	S
W-025-01.bmp	W-025-23.bmp	S
W-025-01.bmp	W-025-24.bmp	S
W-025-01.bmp	W-025-25.bmp	S
W-025-01.bmp	W-025-26.bmp	S
W-026-01.bmp	W-026-02.bmp	S
W-026-01.bmp	W-026-03.bmp	S
W-026-01.bmp	W-026-04.bmp	S
W-026-01.bmp	W-026-05.bmp	S
W-026-01.bmp	W-026-06.bmp	S
W-026-01.bmp	W-026-07.bmp	S
W-026-01.bmp	W-026-08.bmp	S
W-026-01.bmp	W-026-09.bmp	S
W-026-01.bmp	W-026-10.bmp	S
W-026-01.bmp	W-026-11.bmp	S
W-026-01.bmp	W-026-12.bmp	S
W-026-01.bmp	W-026-13.bmp	S
W-026-01.bmp	W-026-14.bmp	S
W-026-01.bmp	W-026-15.bmp	S
W-026-01.bmp	W-026-16.bmp	S
W-026-01.bmp	W-026-17.bmp	S
W-026-01.bmp	W-026-18.bmp	S
W-026-01.bmp	W-026-19.bmp	S
W-026-01.bmp	W-026-20.bmp	S
W-026-01.bmp	W-026-21.bmp	S
W-026-01.bmp	W-026-22.bmp	S
W-026-01.bmp	W-026-23.bmp	S
W-026-01.bmp	W-026-24.bmp	S
W-026-01.bmp	W-026-25.bmp	S
W-026-01.bmp	W-026-26.bmp	S
W-027-01.bmp	W-027-02.bmp	S
W-027-01.bmp	W-027-03.bmp	S
W-027-01.bmp	W-027-04.bmp	S
W-027-01.bmp	W-027-05.bmp	S
W-027-01.bmp	W-027-06.bmp	S
W-027-01.bmp	W-027-07.bmp	S
W-027-01.bmp	W-027-08.bmp	S
W-027-01.bmp	W-027-09.bmp	S
W-027-01.bmp	W-027-10.bmp	S
W-027-01.bmp	W-027-11.bmp	S
W-027-01.bmp	W-027-12.bmp	S
W-027-01.bmp	W-027-13.bmp	S
W-027-01.bmp	W-027-14.bmp	S
W-027-01.bmp	W-027-15.bmp	S
W-027-01.bmp	W-027-16.bmp	S
W-027-01.bmp	W-027-17.bmp	S
W-027-01.bmp	W-027-18.bmp	S
W-027-01.bmp	W-027-19.bmp	S
W-027-01.bmp	W-027-20.bmp	S
W-027-01.bmp	W-027-21.bmp	S
W-027-01.bmp	W-027-22.bmp	S
W-027-01.bmp	W-027-23.bmp	S
W-027-01.bmp	W-027-24.bmp	S
W-027-01.bmp	W-027-25.bmp	S
W-027-01.bmp	W-027-26.bmp	S
W-028-01.bmp	W-028-02.bmp	S
W-028-01.bmp	W-028-03.bmp	S
W-028-01.bmp	W-028-04.bmp	S
W-028-01.bmp	W-028-05.bmp	S
W-028-01.bmp	W-028-06.bmp	S
W-028-01.bmp	W-028-07.bmp	S
W-028-01.bmp	W-028-08.bmp	S
W-028-01.bmp	W-028-09.bmp	S
W-028-01.bmp	W-028-10.bmp	S
W-028-01.bmp	W-028-11.bmp	S
W-028-01.bmp	W-028-12.bmp	S
W-028-01.bmp	W-028-13.bmp	S
W-028-01.bmp	W-028-14.bmp	S
W-028-01.bmp	W-028-15.bmp	S
W-028-01.bmp	W-028-16.bmp	S
W-028-01.bmp	W-028-17.bmp	S
W-028-01.bmp	W-028-18.bmp	S
W-028-01.bmp	W-028-19.bmp	S
W-028-01.bmp	W-028-20.bmp	S
W-028-01.bmp	W-028-21.bmp	S
W-028-01.bmp	W-028-22.bmp	S
W-028-01.bmp	W-028-23.bmp	S
W-028-01.bmp	W-028-24.bmp	S
W-028-01.bmp	W-028-25.bmp	S
W-028-01.bmp	W-028-26.bmp	S
W-029-01.bmp	W-029-02.bmp	S
W-029-01.bmp	W-029-03.bmp	S
W-029-01.bmp	W-029-04.bmp	S
W-029-01.bmp	W-029-05.bmp	S
W-029-01.bmp	W-029-06.bmp	S
W-029-01.bmp	W-029-07.bmp	S
W-029-01.bmp	W-029-08.bmp	S
W-029-01.bmp	W-029-09.bmp	S
W-029-01.bmp	W-029-10.bmp	S
W-029-01.bmp	W-029-11.bmp	S
W-029-01.bmp	W-029-12.bmp	S
W-029-01.bmp	W-029-13.bmp	S
W-029-01.bmp	W-029-14.bmp	S
W-029-01.bmp	W-029-15.bmp	S
W-029-01.bmp	W-029-16.bmp	S
W-029-01.bmp	W-029-17.bmp	S
W-029-01.bmp	W-029-18.bmp	S
W-029-01.bmp	W-029-19.bmp	S
W-029-01.bmp	W-029-20.bmp	S
W-029-01.bmp	W-029-21.bmp	S
W-029-01.bmp	W-029-22.bmp	S
W-029-01.bmp	W-029-23.bmp	S
W-029-01.bmp	W-029-24.bmp	S
W-029-01.bmp	W-029-25.bmp	S
W-029-01.bmp	W-029-26.bmp	S
W-030-01.bmp	W-030-02.bmp	S
W-030-01.bmp	W-030-03.bmp	S
W-030-01.bmp	W-030-04.bmp	S
W-030-01.bmp	W-030-05.bmp	S
W-030-01.bmp	W-030-06.bmp	S
W-030-01.bmp	W-030-07.bmp	S
W-030-01.bmp	W-030-08.bmp	S
W-030-01.bmp	W-030-09.bmp	S
W-030-01.bmp	W-030-10.bmp	S
W-030-01.bmp	W-030-11.bmp	S
W-030-01.bmp	W-030-12.bmp	S
W-030-01.bmp	W-030-13.bmp	S
W-030-01.bmp	W-030-14.bmp	S
W-030-01.bmp	W-030-15.bmp	S
W-030-01.bmp	W-030-16.bmp	S
W-030-01.bmp	W-030-17.bmp	S
W-030-01.bmp	W-030-18.bmp	S
W-030-01.bmp	W-030-19.bmp	S
W-030-01.bmp	W-030-20.bmp	S
W-030-01.bmp	W-030-21.bmp	S
W-030-01.bmp	W-030-22.bmp	S
W-030-01.bmp	W-030-23.bmp	S
W-030-01.bmp	W-030-24.bmp	S
W-030-01.bmp	W-030-25.bmp	S
W-030-01.bmp	W-030-26.bmp	S
W-031-01.bmp	W-031-02.bmp	S
W-031-01.bmp	W-031-03.bmp	S
W-031-01.bmp	W-031-04.bmp	S
W-031-01.bmp	W-031-05.bmp	S
W-031-01.bmp	W-031-06.bmp	S
W-031-01.bmp	W-031-07.bmp	S
W-031-01.bmp	W-031-08.bmp	S
W-031-01.bmp	W-031-09.bmp	S
W-031-01.bmp	W-031-10.bmp	S
W-031-01.bmp	W-031-11.bmp	S
W-031-01.bmp	W-031-12.bmp	S
W-031-01.bmp	W-031-13.bmp	S
W-031-01.bmp	W-031-14.bmp	S
W-031-01.bmp	W-031-15.bmp	S
W-031-01.bmp	W-031-16.bmp	S
W-031-01.bmp	W-031-17.bmp	S
W-031-01.bmp	W-031-18.bmp	S
W-031-01.bmp	W-031-19.bmp	S
W-031-01.bmp	W-031-20.bmp	S
W-031-01.bmp	W-031-21.bmp	S
W-031-01.bmp	W-031-22.bmp	S
W-031-01.bmp	W-031-23.bmp	S
W-031-01.bmp	W-031-24.bmp	S
W-031-01.bmp	W-031-25.bmp	S
W-031-01.bmp	W-031-26.bmp	S
W-032-01.bmp	W-032-02.bmp	S
W-032-01.bmp	W-032-03.bmp	S
W-032-01.bmp	W-032-04.bmp	S
W-032-01.bmp	W-032-05.bmp	S
W-032-01.bmp	W-032-06.bmp	S
W-032-01.bmp	W-032-07.bmp	S
W-032-01.bmp	W-032-08.bmp	S
W-032-01.bmp	W-032-09.bmp	S
W-032-01.bmp	W-032-10.bmp	S
W-032-01.bmp	W-032-11.bmp	S
W-032-01.bmp	W-032-12.bmp	S
W-032-01.bmp	W-032-13.bmp	S
W-032-01.bmp	W-032-14.bmp	S
W-032-01.bmp	W-032-15.bmp	S
W-032-01.bmp	W-032-16.bmp	S
W-032-01.bmp	W-032-17.bmp	S
W-032-01.bmp	W-032-18.bmp	S
W-032-01.bmp	W-032-19.bmp	S
W-032-01.bmp	W-032-20.bmp	S
W-032-01.bmp	W-032-21.bmp	S
W-032-01.bmp	W-032-22.bmp	S
W-032-01.bmp	W-032-23.bmp	S
W-032-01.bmp	W-032-24.bmp	S
W-032-01.bmp	W-032-25.bmp	S
W-032-01.bmp	W-032-26.bmp	S
W-033-01.bmp	W-033-02.bmp	S
W-033-01.bmp	W-033-03.bmp	S
W-033-01.bmp	W-033-04.bmp	S
W-033-01.bmp	W-033-05.bmp	S
W-033-01.bmp	W-033-06.bmp	S
W-033-01.bmp	W-033-07.bmp	S
W-033-01.bmp	W-033-08.bmp	S
W-033-01.bmp	W-033-09.bmp	S
W-033-01.bmp	W-033-10.bmp	S
W-033-01.bmp	W-033-11.bmp	S
W-033-01.bmp	W-033-12.bmp	S
W-033-01.bmp	W-033-13.bmp	S
W-033-01.bmp	W-033-14.bmp	S
W-033-01.bmp	W-033-15.bmp	S
W-033-01.bmp	W-033-16.bmp	S
W-033-01.bmp	W-033-17.bmp	S
W-033-01.bmp	W-033-18.bmp	S
W-033-01.bmp	W-033-19.bmp	S
W-033-01.bmp	W-033-20.bmp	S
W-033-01.bmp	W-033-21.bmp	S
W-033-01.bmp	W-033-22.bmp	S
W-033-01.bmp	W-033-23.bmp	S
W-033-01.bmp	W-033-24.bmp	S
W-033-01.bmp	W-033-25.bmp	S
W-033-01.bmp	W-033-26.bmp	S
W-034-01.bmp	W-034-02.bmp	S
W-034-01.bmp	W-034-03.bmp	S
W-034-01.bmp	W-034-04.bmp	S
W-034-01.bmp	W-034-05.bmp	S
W-034-01.bmp	W-034-06.bmp	S
W-034-01.bmp	W-034-07.bmp	S
W-034-01.bmp	W-034-08.bmp	S
W-034-01.bmp	W-034-09.bmp	S
W-034-01.bmp	W-034-10.bmp	S
W-034-01.bmp	W-034-11.bmp	S
W-034-01.bmp	W-034-12.bmp	S
W-034-01.bmp	W-034-13.bmp	S
W-034-01.bmp	W-034-14.bmp	S
W-034-01.bmp	W-034-15.bmp	S
W-034-01.bmp	W-034-16.bmp	S
W-034-01.bmp	W-034-17.bmp	S
W-034-01.bmp	W-034-18.bmp	S
W-034-01.bmp	W-034-19.bmp	S
W-034-01.bmp	W-034-20.bmp	S
W-034-01.bmp	W-034-21.bmp	S
W-034-01.bmp	W-034-22.bmp	S
W-034-01.bmp	W-034-23.bmp	S
W-034-01.bmp	W-034-24.bmp	S
W-034-01.bmp	W-034-25.bmp	S
W-034-01.bmp	W-034-26.bmp	S
W-035-01.bmp	W-035-02.bmp	S
W-035-01.bmp	W-035-03.bmp	S
W-035-01.bmp	W-035-04.bmp	S
W-035-01.bmp	W-035-05.bmp	S
W-035-01.bmp	W-035-06.bmp	S
W-035-01.bmp	W-035-07.bmp	S
W-035-01.bmp	W-035-08.bmp	S
W-035-01.bmp	W-035-09.bmp	S
W-035-01.bmp	W-035-10.bmp	S
W-035-01.bmp	W-035-11.bmp	S
W-035-01.bmp	W-035-12.bmp	S
W-035-01.bmp	W-035-13.bmp	S
W-035-01.bmp	W-035-14.bmp	S
W-035-01.bmp	W-035-15.bmp	S
W-035-01.bmp	W-035-16.bmp	S
W-035-01.bmp	W-035-17.bmp	S
W-035-01.bmp	W-035-18.bmp	S
W-035-01.bmp	W-035-19.bmp	S
W-035-01.bmp	W-035-20.bmp	S
W-035-01.bmp	W-035-21.bmp	S
W-035-01.bmp	W-035-22.bmp	S
W-035-01.bmp	W-035-23.bmp	S
W-035-01.bmp	W-035-24.bmp	S
W-035-01.bmp	W-035-25.bmp	S
W-035-01.bmp	W-035-26.bmp	S
W-036-01.bmp	W-036-02.bmp	S
W-036-01.bmp	W-036-03.bmp	S
W-036-01.bmp	W-036-04.bmp	S
W-036-01.bmp	W-036-05.bmp	S
W-036-01.bmp	W-036-06.bmp	S
W-036-01.bmp	W-036-07.bmp	S
W-036-01.bmp	W-036-08.bmp	S
W-036-01.bmp	W-036-09.bmp	S
W-036-01.bmp	W-036-10.bmp	S
W-036-01.bmp	W-036-11.bmp	S
W-036-01.bmp	W-036-12.bmp	S
W-036-01.bmp	W-036-13.bmp	S
W-036-01.bmp	W-036-14.bmp	S
W-036-01.bmp	W-036-15.bmp	S
W-036-01.bmp	W-036-16.bmp	S
W-036-01.bmp	W-036-17.bmp	S
W-036-01.bmp	W-036-18.bmp	S
W-036-01.bmp	W-036-19.bmp	S
W-036-01.bmp	W-036-20.bmp	S
W-036-01.bmp	W-036-21.bmp	S
W-036-01.bmp	W-036-22.bmp	S
W-036-01.bmp	W-036-23.bmp	S
W-036-01.bmp	W-036-24.bmp	S
W-036-01.bmp	W-036-25.bmp	S
W-036-01.bmp	W-036-26.bmp	S
W-037-01.bmp	W-037-02.bmp	S
W-037-01.bmp	W-037-03.bmp	S
W-037-01.bmp	W-037-04.bmp	S
W-037-01.bmp	W-037-05.bmp	S
W-037-01.bmp	W-037-06.bmp	S
W-037-01.bmp	W-037-07.bmp	S
W-037-01.bmp	W-037-08.bmp	S
W-037-01.bmp	W-037-09.bmp	S
W-037-01.bmp	W-037-10.bmp	S
W-037-01.bmp	W-037-11.bmp	S
W-037-01.bmp	W-037-12.bmp	S
W-037-01.bmp	W-037-13.bmp	S
W-037-01.bmp	W-037-14.bmp	S
W-037-01.bmp	W-037-15.bmp	S
W-037-01.bmp	W-037-16.bmp	S
W-037-01.bmp	W-037-17.bmp	S
W-037-01.bmp	W-037-18.bmp	S
W-037-01.bmp	W-037-19.bmp	S
W-037-01.bmp	W-037-20.bmp	S
W-037-01.bmp	W-037-21.bmp	S
W-037-01.bmp	W-037-22.bmp	S
W-037-01.bmp	W-037-23.bmp	S
W-037-01.bmp	W-037-24.bmp	S
W-037-01.bmp	W-037-25.bmp	S
W-037-01.bmp	W-037-26.bmp	S
W-038-01.bmp	W-038-02.bmp	S
W-038-01.bmp	W-038-03.bmp	S
W-038-01.bmp	W-038-04.bmp	S
W-038-01.bmp	W-038-05.bmp	S
W-038-01.bmp	W-038-06.bmp	S
W-038-01.bmp	W-038-07.bmp	S
W-038-01.bmp	W-038-08.bmp	S
W-038-01.bmp	W-038-09.bmp	S
W-038-01.bmp	W-038-10.bmp	S
W-038-01.bmp	W-038-11.bmp	S
W-038-01.bmp	W-038-12.bmp	S
W-038-01.bmp	W-038-13.bmp	S
W-038-01.bmp	W-038-14.bmp	S
W-038-01.bmp	W-038-15.bmp	S
W-038-01.bmp	W-038-16.bmp	S
W-038-01.bmp	W-038-17.bmp	S
W-038-01.bmp	W-038-18.bmp	S
W-038-01.bmp	W-038-19.bmp	S
W-038-01.bmp	W-038-20.bmp	S
W-038-01.bmp	W-038-21.bmp	S
W-038-01.bmp	W-038-22.bmp	S
W-038-01.bmp	W-038-23.bmp	S
W-038-01.bmp	W-038-24.bmp	S
W-038-01.bmp	W-038-25.bmp	S
W-038-01.bmp	W-038-26.bmp	S
W-039-01.bmp	W-039-02.bmp	S
W-039-01.bmp	W-039-03.bmp	S
W-039-01.bmp	W-039-04.bmp	S
W-039-01.bmp	W-039-05.bmp	S
W-039-01.bmp	W-039-06.bmp	S
W-039-01.bmp	W-039-07.bmp	S
W-039-01.bmp	W-039-08.bmp	S
W-039-01.bmp	W-039-09.bmp	S
W-039-01.bmp	W-039-10.bmp	S
W-039-01.bmp	W-039-11.bmp	S
W-039-01.bmp	W-039-12.bmp	S
W-039-01.bmp	W-039-13.bmp	S
W-039-01.bmp	W-039-14.bmp	S
W-039-01.bmp	W-039-15.bmp	S
W-039-01.bmp	W-039-16.bmp	S
W-039-01.bmp	W-039-17.bmp	S
W-039-01.bmp	W-039-18.bmp	S
W-039-01.bmp	W-039-19.bmp	S
W-039-01.bmp	W-039-20.bmp	S
W-039-01.bmp	W-039-21.bmp	S
W-039-01.bmp	W-039-22.bmp	S
W-039-01.bmp	W-039-23.bmp	S
W-039-01.bmp	W-039-24.bmp	S
W-039-01.bmp	W-039-25.bmp	S
W-039-01.bmp	W-039-26.bmp	S
W-040-01.bmp	W-040-02.bmp	S
W-040-01.bmp	W-040-03.bmp	S
W-040-01.bmp	W-040-04.bmp	S
W-040-01.bmp	W-040-05.bmp	S
W-040-01.bmp	W-040-06.bmp	S
W-040-01.bmp	W-040-07.bmp	S
W-040-01.bmp	W-040-08.bmp	S
W-040-01.bmp	W-040-09.bmp	S
W-040-01.bmp	W-040-10.bmp	S
W-040-01.bmp	W-040-11.bmp	S
W-040-01.bmp	W-040-12.bmp	S
W-040-01.bmp	W-040-13.bmp	S
W-040-01.bmp	W-040-14.bmp	S
W-040-01.bmp	W-040-15.bmp	S
W-040-01.bmp	W-040-16.bmp	S
W-040-01.bmp	W-040-17.bmp	S
W-040-01.bmp	W-040-18.bmp	S
W-040-01.bmp	W-040-19.bmp	S
W-040-01.bmp	W-040-20.bmp	S
W-040-01.bmp	W-040-21.bmp	S
W-040-01.bmp	W-040-22.bmp	S
W-040-01.bmp	W-040-23.bmp	S
W-040-01.bmp	W-040-24.bmp	S
W-040-01.bmp	W-040-25.bmp	S
W-040-01.bmp	W-040-26.bmp	S
W-041-01.bmp	W-041-02.bmp	S
W-041-01.bmp	W-041-03.bmp	S
W-041-01.bmp	W-041-04.bmp	S
W-041-01.bmp	W-041-05.bmp	S
W-041-01.bmp	W-041-06.bmp	S
W-041-01.bmp	W-041-07.bmp	S
W-041-01.bmp	W-041-08.bmp	S
W-041-01.bmp	W-041-09.bmp	S
W-041-01.bmp	W-041-10.bmp	S
W-041-01.bmp	W-041-11.bmp	S
W-041-01.bmp	W-041-12.bmp	S
W-041-01.bmp	W-041-13.bmp	S
W-041-01.bmp	W-041-14.bmp	S
W-041-01.bmp	W-041-15.bmp	S
W-041-01.bmp	W-041-16.bmp	S
W-041-01.bmp	W-041-17.bmp	S
W-041-01.bmp	W-041-18.bmp	S
W-041-01.bmp	W-041-19.bmp	S
W-041-01.bmp	W-041-20.bmp	S
W-041-01.bmp	W-041-21.bmp	S
W-041-01.bmp	W-041-22.bmp	S
W-041-01.bmp	W-041-23.bmp	S
W-041-01.bmp	W-041-24.bmp	S
W-041-01.bmp	W-041-25.bmp	S
W-041-01.bmp	W-041-26.bmp	S
W-042-01.bmp	W-042-02.bmp	S
W-042-01.bmp	W-042-03.bmp	S
W-042-01.bmp	W-042-04.bmp	S
W-042-01.bmp	W-042-05.bmp	S
W-042-01.bmp	W-042-06.bmp	S
W-042-01.bmp	W-042-07.bmp	S
W-042-01.bmp	W-042-08.bmp	S
W-042-01.bmp	W-042-09.bmp	S
W-042-01.bmp	W-042-10.bmp	S
W-042-01.bmp	W-042-11.bmp	S
W-042-01.bmp	W-042-12.bmp	S
W-042-01.bmp	W-042-13.bmp	S
W-042-01.bmp	W-042-14.bmp	S
W-042-01.bmp	W-042-15.bmp	S
W-042-01.bmp	W-042-16.bmp	S
W-042-01.bmp	W-042-17.bmp	S
W-042-01.bmp	W-042-18.bmp	S
W-042-01.bmp	W-042-19.bmp	S
W-042-01.bmp	W-042-20.bmp	S
W-042-01.bmp	W-042-21.bmp	S
W-042-01.bmp	W-042-22.bmp	S
W-042-01.bmp	W-042-23.bmp	S
W-042-01.bmp	W-042-24.bmp	S
W-042-01.bmp	W-042-25.bmp	S
W-042-01.bmp	W-042-26.bmp	S
W-043-01.bmp	W-043-02.bmp	S
W-043-01.bmp	W-043-03.bmp	S
W-043-01.bmp	W-043-04.bmp	S
W-043-01.bmp	W-043-05.bmp	S
W-043-01.bmp	W-043-06.bmp	S
W-043-01.bmp	W-043-07.bmp	S
W-043-01.bmp	W-043-08.bmp	S
W-043-01.bmp	W-043-09.bmp	S
W-043-01.bmp	W-043-10.bmp	S
W-043-01.bmp	W-043-11.bmp	S
W-043-01.bmp	W-043-12.bmp	S
W-043-01.bmp	W-043-13.bmp	S
W-043-01.bmp	W-043-14.bmp	S
W-043-01.bmp	W-043-15.bmp	S
W-043-01.bmp	W-043-16.bmp	S
W-043-01.bmp	W-043-17.bmp	S
W-043-01.bmp	W-043-18.bmp	S
W-043-01.bmp	W-043-19.bmp	S
W-043-01.bmp	W-043-20.bmp	S
W-043-01.bmp	W-043-21.bmp	S
W-043-01.bmp	W-043-22.bmp	S
W-043-01.bmp	W-043-23.bmp	S
W-043-01.bmp	W-043-24.bmp	S
W-043-01.bmp	W-043-25.bmp	S
W-043-01.bmp	W-043-26.bmp	S
W-044-01.bmp	W-044-02.bmp	S
W-044-01.bmp	W-044-03.bmp	S
W-044-01.bmp	W-044-04.bmp	S
W-044-01.bmp	W-044-05.bmp	S
W-044-01.bmp	W-044-06.bmp	S
W-044-01.bmp	W-044-07.bmp	S
W-044-01.bmp	W-044-08.bmp	S
W-044-01.bmp	W-044-09.bmp	S
W-044-01.bmp	W-044-10.bmp	S
W-044-01.bmp	W-044-11.bmp	S
W-044-01.bmp	W-044-12.bmp	S
W-044-01.bmp	W-044-13.bmp	S
W-044-01.bmp	W-044-14.bmp	S
W-044-01.bmp	W-044-15.bmp	S
W-044-01.bmp	W-044-16.bmp	S
W-044-01.bmp	W-044-17.bmp	S
W-044-01.bmp	W-044-18.bmp	S
W-044-01.bmp	W-044-19.bmp	S
W-044-01.bmp	W-044-20.bmp	S
W-044-01.bmp	W-044-21.bmp	S
W-044-01.bmp	W-044-22.bmp	S
W-044-01.bmp	W-044-23.bmp	S
W-044-01.bmp	W-044-24.bmp	S
W-044-01.bmp	W-044-25.bmp	S
W-044-01.bmp	W-044-26.bmp	S
W-045-01.bmp	W-045-02.bmp	S
W-045-01.bmp	W-045-03.bmp	S
W-045-01.bmp	W-045-04.bmp	S
W-045-01.bmp	W-045-05.bmp	S
W-045-01.bmp	W-045-06.bmp	S
W-045-01.bmp	W-045-07.bmp	S
W-045-01.bmp	W-045-08.bmp	S
W-045-01.bmp	W-045-09.bmp	S
W-045-01.bmp	W-045-10.bmp	S
W-045-01.bmp	W-045-11.bmp	S
W-045-01.bmp	W-045-12.bmp	S
W-045-01.bmp	W-045-13.bmp	S
W-045-01.bmp	W-045-14.bmp	S
W-045-01.bmp	W-045-15.bmp	S
W-045-01.bmp	W-045-16.bmp	S
W-045-01.bmp	W-045-17.bmp	S
W-045-01.bmp	W-045-18.bmp	S
W-045-01.bmp	W-045-19.bmp	S
W-045-01.bmp	W-045-20.bmp	S
W-045-01.bmp	W-045-21.bmp	S
W-045-01.bmp	W-045-22.bmp	S
W-045-01.bmp	W-045-23.bmp	S
W-045-01.bmp	W-045-24.bmp	S
W-045-01.bmp	W-045-25.bmp	S
W-045-01.bmp	W-045-26.bmp	S
W-046-01.bmp	W-046-02.bmp	S
W-046-01.bmp	W-046-03.bmp	S
W-046-01.bmp	W-046-04.bmp	S
W-046-01.bmp	W-046-05.bmp	S
W-046-01.bmp	W-046-06.bmp	S
W-046-01.bmp	W-046-07.bmp	S
W-046-01.bmp	W-046-08.bmp	S
W-046-01.bmp	W-046-09.bmp	S
W-046-01.bmp	W-046-10.bmp	S
W-046-01.bmp	W-046-11.bmp	S
W-046-01.bmp	W-046-12.bmp	S
W-046-01.bmp	W-046-13.bmp	S
W-046-01.bmp	W-046-14.bmp	S
W-046-01.bmp	W-046-15.bmp	S
W-046-01.bmp	W-046-16.bmp	S
W-046-01.bmp	W-046-17.bmp	S
W-046-01.bmp	W-046-18.bmp	S
W-046-01.bmp	W-046-19.bmp	S
W-046-01.bmp	W-046-20.bmp	S
W-046-01.bmp	W-046-21.bmp	S
W-046-01.bmp	W-046-22.bmp	S
W-046-01.bmp	W-046-23.bmp	S
W-046-01.bmp	W-046-24.bmp	S
W-046-01.bmp	W-046-25.bmp	S
W-046-01.bmp	W-046-26.bmp	S
W-047-01.bmp	W-047-02.bmp	S
W-047-01.bmp	W-047-03.bmp	S
W-047-01.bmp	W-047-04.bmp	S
W-047-01.bmp	W-047-05.bmp	S
W-047-01.bmp	W-047-06.bmp	S
W-047-01.bmp	W-047-07.bmp	S
W-047-01.bmp	W-047-08.bmp	S
W-047-01.bmp	W-047-09.bmp	S
W-047-01.bmp	W-047-10.bmp	S
W-047-01.bmp	W-047-11.bmp	S
W-047-01.bmp	W-047-12.bmp	S
W-047-01.bmp	W-047-13.bmp	S
W-047-01.bmp	W-047-14.bmp	S
W-047-01.bmp	W-047-15.bmp	S
W-047-01.bmp	W-047-16.bmp	S
W-047-01.bmp	W-047-17.bmp	S
W-047-01.bmp	W-047-18.bmp	S
W-047-01.bmp	W-047-19.bmp	S
W-047-01.bmp	W-047-20.bmp	S
W-047-01.bmp	W-047-21.bmp	S
W-047-01.bmp	W-047-22.bmp	S
W-047-01.bmp	W-047-23.bmp	S
W-047-01.bmp	W-047-24.bmp	S
W-047-01.bmp	W-047-25.bmp	S
W-047-01.bmp	W-047-26.bmp	S
W-048-01.bmp	W-048-02.bmp	S
W-048-01.bmp	W-048-03.bmp	S
W-048-01.bmp	W-048-04.bmp	S
W-048-01.bmp	W-048-05.bmp	S
W-048-01.bmp	W-048-06.bmp	S
W-048-01.bmp	W-048-07.bmp	S
W-048-01.bmp	W-048-08.bmp	S
W-048-01.bmp	W-048-09.bmp	S
W-048-01.bmp	W-048-10.bmp	S
W-048-01.bmp	W-048-11.bmp	S
W-048-01.bmp	W-048-12.bmp	S
W-048-01.bmp	W-048-13.bmp	S
W-048-01.bmp	W-048-14.bmp	S
W-048-01.bmp	W-048-15.bmp	S
W-048-01.bmp	W-048-16.bmp	S
W-048-01.bmp	W-048-17.bmp	S
W-048-01.bmp	W-048-18.bmp	S
W-048-01.bmp	W-048-19.bmp	S
W-048-01.bmp	W-048-20.bmp	S
W-048-01.bmp	W-048-21.bmp	S
W-048-01.bmp	W-048-22.bmp	S
W-048-01.bmp	W-048-23.bmp	S
W-048-01.bmp	W-048-24.bmp	S
W-048-01.bmp	W-048-25.bmp	S
W-048-01.bmp	W-048-26.bmp	S
W-049-01.bmp	W-049-02.bmp	S
W-049-01.bmp	W-049-03.bmp	S
W-049-01.bmp	W-049-04.bmp	S
W-049-01.bmp	W-049-05.bmp	S
W-049-01.bmp	W-049-06.bmp	S
W-049-01.bmp	W-049-07.bmp	S
W-049-01.bmp	W-049-08.bmp	S
W-049-01.bmp	W-049-09.bmp	S
W-049-01.bmp	W-049-10.bmp	S
W-049-01.bmp	W-049-11.bmp	S
W-049-01.bmp	W-049-12.bmp	S
W-049-01.bmp	W-049-13.bmp	S
W-049-01.bmp	W-049-14.bmp	S
W-049-01.bmp	W-049-15.bmp	S
W-049-01.bmp	W-049-16.bmp	S
W-049-01.bmp	W-049-17.bmp	S
W-049-01.bmp	W-049-18.bmp	S
W-049-01.bmp	W-049-19.bmp	S
W-049-01.bmp	W-049-20.bmp	S
W-049-01.bmp	W-049-21.bmp	S
W-049-01.bmp	W-049-22.bmp	S
W-049-01.bmp	W-049-23.bmp	S
W-049-01.bmp	W-049-24.bmp	S
W-049-01.bmp	W-049-25.bmp	S
W-049-01.bmp	W-049-26.bmp	S
W-050-01.bmp	W-050-02.bmp	S
W-050-01.bmp	W-050-03.bmp	S
W-050-01.bmp	W-050-04.bmp	S
W-050-01.bmp	W-050-05.bmp	S
W-050-01.bmp	W-050-06.bmp	S
W-050-01.bmp	W-050-07.bmp	S
W-050-01.bmp	W-050-08.bmp	S
W-050-01.bmp	W-050-09.bmp	S
W-050-01.bmp	W-050-10.bmp	S
W-050-01.bmp	W-050-11.bmp	S
W-050-01.bmp	W-050-12.bmp	S
W-050-01.bmp	W-050-13.bmp	S
W-050-01.bmp	W-050-14.bmp	S
W-050-01.bmp	W-050-15.bmp	S
W-050-01.bmp	W-050-16.bmp	S
W-050-01.bmp	W-050-17.bmp	S
W-050-01.bmp	W-050-18.bmp	S
W-050-01.bmp	W-050-19.bmp	S
W-050-01.bmp	W-050-20.bmp	S
W-050-01.bmp	W-050-21.bmp	S
W-050-01.bmp	W-050-22.bmp	S
W-050-01.bmp	W-050-23.bmp	S
W-050-01.bmp	W-050-24.bmp	S
W-050-01.bmp	W-050-25.bmp	S
W-050-01.bmp	W-050-26.bmp	S
W-049-01.bmp	W-021-11.bmp	D
W-007-01.bmp	W-003-25.bmp	D
M-043-01.bmp	M-050-20.bmp	D
M-035-01.bmp	M-034-05.bmp	D
W-045-01.bmp	W-028-03.bmp	D
W-026-01.bmp	W-029-04.bmp	D
W-020-01.bmp	W-013-08.bmp	D
M-004-01.bmp	M-001-12.bmp	D
M-008-01.bmp	M-050-19.bmp	D
M-046-01.bmp	M-007-02.bmp	D
W-014-01.bmp	W-031-08.bmp	D
W-039-01.bmp	W-048-07.bmp	D
W-021-01.bmp	W-024-13.bmp	D
W-042-01.bmp	W-027-11.bmp	D
W-012-01.bmp	W-010-14.bmp	D
M-017-01.bmp	M-050-07.bmp	D
W-050-01.bmp	W-021-14.bmp	D
W-041-01.bmp	W-015-10.bmp	D
W-024-01.bmp	W-017-05.bmp	D
W-016-01.bmp	W-034-17.bmp	D
M-008-01.bmp	M-029-24.bmp	D
W-046-01.bmp	W-040-09.bmp	D
W-005-01.bmp	W-014-21.bmp	D
M-045-01.bmp	M-042-11.bmp	D
W-042-01.bmp	W-001-14.bmp	D
M-033-01.bmp	M-022-13.bmp	D
M-019-01.bmp	M-016-08.bmp	D
W-024-01.bmp	W-002-19.bmp	D
W-021-01.bmp	W-023-25.bmp	D
W-050-01.bmp	W-021-14.bmp	D
M-007-01.bmp	M-025-11.bmp	D
M-006-01.bmp	M-026-12.bmp	D
W-009-01.bmp	W-040-14.bmp	D
M-020-01.bmp	M-036-14.bmp	D
W-044-01.bmp	W-046-06.bmp	D
M-023-01.bmp	M-004-24.bmp	D
W-047-01.bmp	W-031-08.bmp	D
M-005-01.bmp	M-011-25.bmp	D
W-003-01.bmp	W-038-11.bmp	D
W-045-01.bmp	W-033-11.bmp	D
M-049-01.bmp	M-036-24.bmp	D
M-006-01.bmp	M-033-26.bmp	D
W-033-01.bmp	W-043-22.bmp	D
W-030-01.bmp	W-027-10.bmp	D
W-026-01.bmp	W-013-15.bmp	D
M-046-01.bmp	M-013-24.bmp	D
M-018-01.bmp	M-049-13.bmp	D
W-004-01.bmp	W-021-25.bmp	D
W-036-01.bmp	W-042-08.bmp	D
W-042-01.bmp	W-031-16.bmp	D
M-011-01.bmp	M-034-14.bmp	D
M-019-01.bmp	M-015-03.bmp	D
M-047-01.bmp	M-038-06.bmp	D
M-032-01.bmp	M-016-18.bmp	D
M-013-01.bmp	M-022-12.bmp	D
M-048-01.bmp	M-006-07.bmp	D
W-050-01.bmp	W-022-11.bmp	D
M-021-01.bmp	M-027-05.bmp	D
M-040-01.bmp	M-017-14.bmp	D
W-042-01.bmp	W-029-08.bmp	D
W-043-01.bmp	W-002-22.bmp	D
M-032-01.bmp	M-036-05.bmp	D
M-046-01.bmp	M-043-02.bmp	D
M-001-01.bmp	M-015-24.bmp	D
M-020-01.bmp	M-026-22.bmp	D
W-014-01.bmp	W-040-22.bmp	D
W-041-01.bmp	W-038-13.bmp	D
M-018-01.bmp	M-029-21.bmp	D
W-005-01.bmp	W-014-22.bmp	D
M-026-01.bmp	M-022-17.bmp	D
M-008-01.bmp	M-009-13.bmp	D
M-045-01.bmp	M-049-03.bmp	D
M-004-01.bmp	M-014-22.bmp	D
M-038-01.bmp	M-005-16.bmp	D
W-002-01.bmp	W-012-22.bmp	D
W-004-01.bmp	W-009-21.bmp	D
M-049-01.bmp	M-031-24.bmp	D
M-004-01.bmp	M-039-24.bmp	D
W-002-01.bmp	W-001-24.bmp	D
W-041-01.bmp	W-021-26.bmp	D
M-025-01.bmp	M-035-16.bmp	D
M-026-01.bmp	M-045-09.bmp	D
W-049-01.bmp	W-031-19.bmp	D
M-030-01.bmp	M-033-25.bmp	D
M-026-01.bmp	M-032-08.bmp	D
M-030-01.bmp	M-045-04.bmp	D
W-044-01.bmp	W-047-04.bmp	D
W-003-01.bmp	W-024-03.bmp	D
W-022-01.bmp	W-036-02.bmp	D
M-008-01.bmp	M-045-16.bmp	D
W-016-01.bmp	W-048-21.bmp	D
W-008-01.bmp	W-032-22.bmp	D
M-022-01.bmp	M-040-02.bmp	D
M-018-01.bmp	M-041-25.bmp	D
W-039-01.bmp	W-046-21.bmp	D
W-037-01.bmp	W-048-08.bmp	D
M-002-01.bmp	M-012-02.bmp	D
M-032-01.bmp	M-038-26.bmp	D
W-026-01.bmp	W-014-11.bmp	D
W-016-01.bmp	W-022-18.bmp	D
M-006-01.bmp	M-012-15.bmp	D
W-017-01.bmp	W-037-09.bmp	D
W-016-01.bmp	W-049-03.bmp	D
W-011-01.bmp	W-025-17.bmp	D
W-014-01.bmp	W-020-05.bmp	D
M-020-01.bmp	M-023-15.bmp	D
M-042-01.bmp	M-034-19.bmp	D
M-034-01.bmp	M-013-02.bmp	D
W-009-01.bmp	W-006-23.bmp	D
W-042-01.bmp	W-047-18.bmp	D
W-043-01.bmp	W-025-12.bmp	D
W-036-01.bmp	W-039-23.bmp	D
M-036-01.bmp	M-010-07.bmp	D
M-045-01.bmp	M-029-21.bmp	D
W-008-01.bmp	W-012-02.bmp	D
W-043-01.bmp	W-020-10.bmp	D
W-020-01.bmp	W-018-21.bmp	D
W-031-01.bmp	W-007-19.bmp	D
M-016-01.bmp	M-024-12.bmp	D
M-026-01.bmp	M-030-06.bmp	D
W-031-01.bmp	W-018-19.bmp	D
M-042-01.bmp	M-003-18.bmp	D
W-016-01.bmp	W-005-23.bmp	D
W-029-01.bmp	W-024-05.bmp	D
M-042-01.bmp	M-032-04.bmp	D
W-028-01.bmp	W-011-14.bmp	D
M-050-01.bmp	M-001-08.bmp	D
M-032-01.bmp	M-026-26.bmp	D
M-027-01.bmp	M-043-25.bmp	D
W-001-01.bmp	W-014-17.bmp	D
M-002-01.bmp	M-008-15.bmp	D
W-046-01.bmp	W-022-26.bmp	D
W-034-01.bmp	W-015-21.bmp	D
W-032-01.bmp	W-033-20.bmp	D
M-018-01.bmp	M-038-25.bmp	D
W-040-01.bmp	W-039-13.bmp	D
W-006-01.bmp	W-008-07.bmp	D
W-038-01.bmp	W-044-12.bmp	D
W-019-01.bmp	W-047-20.bmp	D
M-026-01.bmp	M-007-21.bmp	D
M-008-01.bmp	M-031-21.bmp	D
M-012-01.bmp	M-004-18.bmp	D
M-007-01.bmp	M-022-14.bmp	D
W-038-01.bmp	W-031-14.bmp	D
W-005-01.bmp	W-018-26.bmp	D
W-047-01.bmp	W-038-16.bmp	D
W-021-01.bmp	W-032-04.bmp	D
W-002-01.bmp	W-029-13.bmp	D
W-026-01.bmp	W-042-02.bmp	D
W-038-01.bmp	W-049-14.bmp	D
M-012-01.bmp	M-028-05.bmp	D
M-042-01.bmp	M-011-17.bmp	D
M-008-01.bmp	M-042-11.bmp	D
W-050-01.bmp	W-043-21.bmp	D
M-012-01.bmp	M-020-19.bmp	D
W-012-01.bmp	W-025-07.bmp	D
W-025-01.bmp	W-047-16.bmp	D
W-025-01.bmp	W-028-05.bmp	D
M-016-01.bmp	M-048-07.bmp	D
M-008-01.bmp	M-005-26.bmp	D
M-007-01.bmp	M-018-25.bmp	D
M-049-01.bmp	M-045-25.bmp	D
W-017-01.bmp	W-028-18.bmp	D
W-015-01.bmp	W-012-11.bmp	D
M-031-01.bmp	M-028-06.bmp	D
M-004-01.bmp	M-037-15.bmp	D
M-041-01.bmp	M-043-24.bmp	D
W-045-01.bmp	W-041-23.bmp	D
W-029-01.bmp	W-016-19.bmp	D
M-046-01.bmp	M-018-04.bmp	D
W-037-01.bmp	W-004-24.bmp	D
M-044-01.bmp	M-021-17.bmp	D
W-015-01.bmp	W-020-14.bmp	D
W-007-01.bmp	W-002-16.bmp	D
W-005-01.bmp	W-034-24.bmp	D
M-011-01.bmp	M-032-16.bmp	D
W-035-01.bmp	W-037-14.bmp	D
M-027-01.bmp	M-001-02.bmp	D
M-002-01.bmp	M-040-02.bmp	D
M-004-01.bmp	M-015-23.bmp	D
W-049-01.bmp	W-029-17.bmp	D
W-040-01.bmp	W-023-22.bmp	D
W-050-01.bmp	W-022-04.bmp	D
W-019-01.bmp	W-010-24.bmp	D
W-017-01.bmp	W-030-20.bmp	D
W-041-01.bmp	W-027-02.bmp	D
W-048-01.bmp	W-039-19.bmp	D
M-045-01.bmp	M-050-02.bmp	D
W-029-01.bmp	W-017-14.bmp	D
M-016-01.bmp	M-002-07.bmp	D
M-010-01.bmp	M-017-13.bmp	D
W-016-01.bmp	W-044-20.bmp	D
M-047-01.bmp	M-005-09.bmp	D
M-026-01.bmp	M-027-22.bmp	D
M-036-01.bmp	M-047-10.bmp	D
W-007-01.bmp	W-024-02.bmp	D
W-015-01.bmp	W-036-12.bmp	D
M-036-01.bmp	M-028-17.bmp	D
W-001-01.bmp	W-011-25.bmp	D
W-036-01.bmp	W-013-18.bmp	D
M-025-01.bmp	M-020-17.bmp	D
W-037-01.bmp	W-014-15.bmp	D
W-027-01.bmp	W-041-24.bmp	D
M-032-01.bmp	M-048-19.bmp	D
W-031-01.bmp	W-045-10.bmp	D
M-025-01.bmp	M-036-23.bmp	D
M-035-01.bmp	M-050-12.bmp	D
M-025-01.bmp	M-043-16.bmp	D
M-039-01.bmp	M-011-08.bmp	D
M-050-01.bmp	M-012-17.bmp	D
M-013-01.bmp	M-005-20.bmp	D
W-038-01.bmp	W-025-21.bmp	D
W-038-01.bmp	W-040-20.bmp	D
W-009-01.bmp	W-040-18.bmp	D
M-030-01.bmp	M-029-10.bmp	D
M-040-01.bmp	M-048-26.bmp	D
M-013-01.bmp	M-022-02.bmp	D
W-023-01.bmp	W-046-23.bmp	D
W-044-01.bmp	W-002-23.bmp	D
W-014-01.bmp	W-002-04.bmp	D
W-011-01.bmp	W-021-10.bmp	D
M-001-01.bmp	M-026-02.bmp	D
W-028-01.bmp	W-008-21.bmp	D
M-011-01.bmp	M-021-23.bmp	D
M-043-01.bmp	M-001-06.bmp	D
W-029-01.bmp	W-012-11.bmp	D
M-009-01.bmp	M-001-23.bmp	D
M-012-01.bmp	M-008-25.bmp	D
M-033-01.bmp	M-001-24.bmp	D
W-019-01.bmp	W-028-21.bmp	D
M-011-01.bmp	M-026-13.bmp	D
W-047-01.bmp	W-028-14.bmp	D
W-035-01.bmp	W-039-06.bmp	D
W-006-01.bmp	W-050-23.bmp	D
M-036-01.bmp	M-045-11.bmp	D
W-032-01.bmp	W-001-19.bmp	D
W-042-01.bmp	W-048-02.bmp	D
W-009-01.bmp	W-015-11.bmp	D
M-032-01.bmp	M-050-15.bmp	D
W-007-01.bmp	W-010-16.bmp	D
W-040-01.bmp	W-032-06.bmp	D
M-035-01.bmp	M-015-23.bmp	D
M-017-01.bmp	M-044-08.bmp	D
W-044-01.bmp	W-041-06.bmp	D
M-002-01.bmp	M-006-13.bmp	D
M-020-01.bmp	M-015-21.bmp	D
M-023-01.bmp	M-034-11.bmp	D
M-033-01.bmp	M-046-24.bmp	D
W-002-01.bmp	W-015-24.bmp	D
M-030-01.bmp	M-014-08.bmp	D
W-037-01.bmp	W-027-14.bmp	D
W-002-01.bmp	W-036-07.bmp	D
M-040-01.bmp	M-012-16.bmp	D
W-040-01.bmp	W-032-06.bmp	D
W-048-01.bmp	W-019-16.bmp	D
W-028-01.bmp	W-022-18.bmp	D
W-007-01.bmp	W-044-12.bmp	D
W-017-01.bmp	W-042-16.bmp	D
M-047-01.bmp	M-037-18.bmp	D
M-001-01.bmp	M-043-05.bmp	D
W-019-01.bmp	W-025-07.bmp	D
M-011-01.bmp	M-044-25.bmp	D
M-043-01.bmp	M-005-23.bmp	D
W-016-01.bmp	W-002-14.bmp	D
W-001-01.bmp	W-028-18.bmp	D
W-049-01.bmp	W-042-26.bmp	D
W-042-01.bmp	W-004-15.bmp	D
W-024-01.bmp	W-026-25.bmp	D
W-016-01.bmp	W-027-21.bmp	D
W-036-01.bmp	W-029-05.bmp	D
W-041-01.bmp	W-033-23.bmp	D
W-027-01.bmp	W-038-15.bmp	D
M-030-01.bmp	M-047-18.bmp	D
M-035-01.bmp	M-023-04.bmp	D
M-027-01.bmp	M-007-03.bmp	D
W-023-01.bmp	W-008-08.bmp	D
M-027-01.bmp	M-008-20.bmp	D
M-040-01.bmp	M-043-18.bmp	D
W-019-01.bmp	W-024-22.bmp	D
W-045-01.bmp	W-004-13.bmp	D
M-003-01.bmp	M-030-11.bmp	D
M-018-01.bmp	M-004-06.bmp	D
W-022-01.bmp	W-032-12.bmp	D
M-001-01.bmp	M-039-20.bmp	D
M-023-01.bmp	M-036-12.bmp	D
M-023-01.bmp	M-033-23.bmp	D
M-024-01.bmp	M-037-18.bmp	D
M-042-01.bmp	M-016-14.bmp	D
W-003-01.bmp	W-010-16.bmp	D
M-030-01.bmp	M-035-17.bmp	D
M-013-01.bmp	M-023-13.bmp	D
M-048-01.bmp	M-013-18.bmp	D
M-041-01.bmp	M-027-11.bmp	D
W-008-01.bmp	W-028-11.bmp	D
M-007-01.bmp	M-003-08.bmp	D
M-040-01.bmp	M-005-07.bmp	D
W-050-01.bmp	W-006-08.bmp	D
W-004-01.bmp	W-047-12.bmp	D
W-015-01.bmp	W-026-22.bmp	D
M-017-01.bmp	M-004-25.bmp	D
M-031-01.bmp	M-012-18.bmp	D
W-026-01.bmp	W-005-09.bmp	D
M-030-01.bmp	M-001-25.bmp	D
W-011-01.bmp	W-034-19.bmp	D
M-039-01.bmp	M-023-25.bmp	D
M-024-01.bmp	M-023-04.bmp	D
M-017-01.bmp	M-008-16.bmp	D
W-024-01.bmp	W-034-19.bmp	D
W-047-01.bmp	W-044-08.bmp	D
W-044-01.bmp	W-034-11.bmp	D
M-018-01.bmp	M-049-15.bmp	D
W-017-01.bmp	W-037-03.bmp	D
M-030-01.bmp	M-047-22.bmp	D
W-015-01.bmp	W-008-09.bmp	D
W-021-01.bmp	W-045-26.bmp	D
W-049-01.bmp	W-028-12.bmp	D
W-014-01.bmp	W-039-08.bmp	D
W-044-01.bmp	W-024-07.bmp	D
W-043-01.bmp	W-029-18.bmp	D
M-030-01.bmp	M-012-22.bmp	D
M-002-01.bmp	M-021-25.bmp	D
W-006-01.bmp	W-016-17.bmp	D
W-047-01.bmp	W-038-18.bmp	D
W-017-01.bmp	W-049-08.bmp	D
W-002-01.bmp	W-026-15.bmp	D
W-039-01.bmp	W-026-16.bmp	D
W-020-01.bmp	W-031-23.bmp	D
M-012-01.bmp	M-036-02.bmp	D
W-019-01.bmp	W-003-09.bmp	D
W-021-01.bmp	W-023-26.bmp	D
W-027-01.bmp	W-006-03.bmp	D
W-005-01.bmp	W-043-05.bmp	D
W-044-01.bmp	W-006-11.bmp	D
W-039-01.bmp	W-022-16.bmp	D
M-037-01.bmp	M-042-16.bmp	D
W-019-01.bmp	W-007-02.bmp	D
W-008-01.bmp	W-016-11.bmp	D
W-019-01.bmp	W-016-15.bmp	D
M-028-01.bmp	M-033-13.bmp	D
W-026-01.bmp	W-048-18.bmp	D
M-049-01.bmp	M-015-04.bmp	D
M-032-01.bmp	M-016-10.bmp	D
M-002-01.bmp	M-033-05.bmp	D
W-002-01.bmp	W-005-23.bmp	D
W-024-01.bmp	W-026-02.bmp	D
M-017-01.bmp	M-046-15.bmp	D
M-019-01.bmp	M-008-17.bmp	D
M-021-01.bmp	M-045-12.bmp	D
M-016-01.bmp	M-008-21.bmp	D
M-009-01.bmp	M-003-20.bmp	D
M-036-01.bmp	M-007-20.bmp	D
W-012-01.bmp	W-014-12.bmp	D
W-024-01.bmp	W-048-26.bmp	D
M-003-01.bmp	M-026-20.bmp	D
M-025-01.bmp	M-031-20.bmp	D
W-005-01.bmp	W-043-03.bmp	D
M-027-01.bmp	M-024-20.bmp	D
W-034-01.bmp	W-050-06.bmp	D
M-013-01.bmp	M-005-16.bmp	D
W-027-01.bmp	W-035-05.bmp	D
M-016-01.bmp	M-050-24.bmp	D
M-030-01.bmp	M-042-22.bmp	D
M-014-01.bmp	M-009-23.bmp	D
M-032-01.bmp	M-017-18.bmp	D
M-025-01.bmp	M-048-25.bmp	D
M-029-01.bmp	M-031-26.bmp	D
M-026-01.bmp	M-042-02.bmp	D
W-033-01.bmp	W-013-07.bmp	D
W-043-01.bmp	W-007-25.bmp	D
W-050-01.bmp	W-003-11.bmp	D
W-042-01.bmp	W-033-25.bmp	D
M-002-01.bmp	M-036-09.bmp	D
W-003-01.bmp	W-038-16.bmp	D
M-012-01.bmp	M-048-12.bmp	D
M-035-01.bmp	M-030-08.bmp	D
M-013-01.bmp	M-046-05.bmp	D
W-014-01.bmp	W-047-22.bmp	D
M-006-01.bmp	M-025-26.bmp	D
W-045-01.bmp	W-014-13.bmp	D
M-010-01.bmp	M-019-08.bmp	D
M-024-01.bmp	M-041-22.bmp	D
M-028-01.bmp	M-050-16.bmp	D
M-009-01.bmp	M-002-24.bmp	D
M-038-01.bmp	M-050-04.bmp	D
W-006-01.bmp	W-047-13.bmp	D
W-027-01.bmp	W-002-20.bmp	D
M-037-01.bmp	M-008-17.bmp	D
W-026-01.bmp	W-011-10.bmp	D
M-041-01.bmp	M-001-15.bmp	D
W-019-01.bmp	W-001-06.bmp	D
W-015-01.bmp	W-043-21.bmp	D
W-046-01.bmp	W-027-12.bmp	D
W-016-01.bmp	W-009-18.bmp	D
M-010-01.bmp	M-006-08.bmp	D
M-018-01.bmp	M-023-13.bmp	D
W-010-01.bmp	W-048-10.bmp	D
M-037-01.bmp	M-023-17.bmp	D
W-034-01.bmp	W-048-13.bmp	D
M-045-01.bmp	M-028-19.bmp	D
W-006-01.bmp	W-037-14.bmp	D
W-050-01.bmp	W-007-07.bmp	D
M-038-01.bmp	M-050-04.bmp	D
W-018-01.bmp	W-019-23.bmp	D
W-041-01.bmp	W-038-13.bmp	D
M-010-01.bmp	M-025-12.bmp	D
W-023-01.bmp	W-047-05.bmp	D
M-028-01.bmp	M-017-19.bmp	D
W-007-01.bmp	W-044-17.bmp	D
W-009-01.bmp	W-047-14.bmp	D
M-030-01.bmp	M-032-12.bmp	D
M-026-01.bmp	M-013-22.bmp	D
M-046-01.bmp	M-036-05.bmp	D
W-015-01.bmp	W-043-10.bmp	D
M-009-01.bmp	M-047-12.bmp	D
W-006-01.bmp	W-005-11.bmp	D
M-001-01.bmp	M-041-11.bmp	D
W-008-01.bmp	W-050-09.bmp	D
W-036-01.bmp	W-034-24.bmp	D
M-006-01.bmp	M-009-04.bmp	D
W-039-01.bmp	W-025-05.bmp	D
W-008-01.bmp	W-045-21.bmp	D
M-010-01.bmp	M-046-08.bmp	D
W-038-01.bmp	W-006-04.bmp	D
M-030-01.bmp	M-039-13.bmp	D
M-024-01.bmp	M-042-17.bmp	D
M-008-01.bmp	M-044-15.bmp	D
M-033-01.bmp	M-001-09.bmp	D
W-028-01.bmp	W-012-13.bmp	D
M-005-01.bmp	M-030-11.bmp	D
M-002-01.bmp	M-040-13.bmp	D
M-025-01.bmp	M-019-05.bmp	D
W-046-01.bmp	W-041-10.bmp	D
M-004-01.bmp	M-020-14.bmp	D
M-014-01.bmp	M-047-22.bmp	D
W-044-01.bmp	W-006-23.bmp	D
W-035-01.bmp	W-002-14.bmp	D
M-003-01.bmp	M-025-21.bmp	D
M-044-01.bmp	M-050-09.bmp	D
M-038-01.bmp	M-019-19.bmp	D
W-014-01.bmp	W-027-04.bmp	D
W-037-01.bmp	W-038-17.bmp	D
M-018-01.bmp	M-019-19.bmp	D
M-049-01.bmp	M-003-08.bmp	D
W-017-01.bmp	W-018-09.bmp	D
M-047-01.bmp	M-022-04.bmp	D
M-046-01.bmp	M-004-17.bmp	D
M-030-01.bmp	M-046-08.bmp	D
M-019-01.bmp	M-022-04.bmp	D
W-035-01.bmp	W-031-02.bmp	D
M-007-01.bmp	M-043-18.bmp	D
W-031-01.bmp	W-046-15.bmp	D
M-017-01.bmp	M-029-03.bmp	D
W-012-01.bmp	W-048-24.bmp	D
W-042-01.bmp	W-030-05.bmp	D
M-023-01.bmp	M-025-16.bmp	D
W-018-01.bmp	W-017-18.bmp	D
W-019-01.bmp	W-016-21.bmp	D
W-045-01.bmp	W-026-09.bmp	D
W-017-01.bmp	W-023-12.bmp	D
M-032-01.bmp	M-004-14.bmp	D
W-003-01.bmp	W-026-08.bmp	D
W-032-01.bmp	W-027-24.bmp	D
W-044-01.bmp	W-035-13.bmp	D
M-044-01.bmp	M-017-11.bmp	D
M-047-01.bmp	M-050-26.bmp	D
M-046-01.bmp	M-023-20.bmp	D
W-034-01.bmp	W-013-14.bmp	D
M-046-01.bmp	M-016-21.bmp	D
W-028-01.bmp	W-046-05.bmp	D
W-010-01.bmp	W-012-06.bmp	D
M-018-01.bmp	M-034-14.bmp	D
M-008-01.bmp	M-047-06.bmp	D
W-014-01.bmp	W-006-07.bmp	D
W-009-01.bmp	W-027-15.bmp	D
W-030-01.bmp	W-002-13.bmp	D
W-026-01.bmp	W-011-19.bmp	D
W-014-01.bmp	W-010-05.bmp	D
W-003-01.bmp	W-036-10.bmp	D
W-015-01.bmp	W-046-24.bmp	D
M-005-01.bmp	M-043-09.bmp	D
M-003-01.bmp	M-035-08.bmp	D
M-012-01.bmp	M-020-11.bmp	D
M-007-01.bmp	M-037-03.bmp	D
W-036-01.bmp	W-009-12.bmp	D
W-047-01.bmp	W-049-10.bmp	D
M-005-01.bmp	M-028-26.bmp	D
M-030-01.bmp	M-038-04.bmp	D
W-010-01.bmp	W-037-23.bmp	D
W-006-01.bmp	W-013-11.bmp	D
W-001-01.bmp	W-007-08.bmp	D
W-049-01.bmp	W-008-04.bmp	D
M-015-01.bmp	M-010-15.bmp	D
M-042-01.bmp	M-007-15.bmp	D
M-035-01.bmp	M-030-06.bmp	D
W-028-01.bmp	W-050-10.bmp	D
M-027-01.bmp	M-050-11.bmp	D
W-050-01.bmp	W-040-11.bmp	D
W-044-01.bmp	W-008-22.bmp	D
M-046-01.bmp	M-002-12.bmp	D
W-013-01.bmp	W-009-18.bmp	D
W-025-01.bmp	W-045-18.bmp	D
W-012-01.bmp	W-001-17.bmp	D
M-025-01.bmp	M-010-05.bmp	D
M-024-01.bmp	M-017-24.bmp	D
M-014-01.bmp	M-027-20.bmp	D
W-015-01.bmp	W-035-06.bmp	D
M-004-01.bmp	M-009-04.bmp	D
M-035-01.bmp	M-027-10.bmp	D
W-001-01.bmp	W-022-17.bmp	D
M-042-01.bmp	M-041-20.bmp	D
W-042-01.bmp	W-016-21.bmp	D
M-020-01.bmp	M-026-02.bmp	D
W-024-01.bmp	W-012-08.bmp	D
W-041-01.bmp	W-005-22.bmp	D
M-044-01.bmp	M-013-14.bmp	D
M-050-01.bmp	M-045-04.bmp	D
M-007-01.bmp	M-026-16.bmp	D
W-013-01.bmp	W-033-02.bmp	D
M-046-01.bmp	M-029-21.bmp	D
M-004-01.bmp	M-032-19.bmp	D
W-046-01.bmp	W-003-11.bmp	D
W-024-01.bmp	W-027-09.bmp	D
M-007-01.bmp	M-039-13.bmp	D
M-012-01.bmp	M-014-16.bmp	D
M-020-01.bmp	M-034-21.bmp	D
W-022-01.bmp	W-044-14.bmp	D
M-009-01.bmp	M-035-15.bmp	D
W-042-01.bmp	W-017-12.bmp	D
M-017-01.bmp	M-044-16.bmp	D
M-004-01.bmp	M-046-22.bmp	D
W-030-01.bmp	W-001-15.bmp	D
M-043-01.bmp	M-010-05.bmp	D
M-028-01.bmp	M-044-23.bmp	D
W-029-01.bmp	W-044-08.bmp	D
M-024-01.bmp	M-032-22.bmp	D
W-042-01.bmp	W-040-16.bmp	D
W-029-01.bmp	W-049-06.bmp	D
W-020-01.bmp	W-046-03.bmp	D
W-004-01.bmp	W-037-24.bmp	D
W-027-01.bmp	W-047-05.bmp	D
M-001-01.bmp	M-027-22.bmp	D
M-013-01.bmp	M-003-07.bmp	D
W-009-01.bmp	W-048-11.bmp	D
M-010-01.bmp	M-042-15.bmp	D
M-033-01.bmp	M-037-20.bmp	D
W-022-01.bmp	W-038-24.bmp	D
M-025-01.bmp	M-040-19.bmp	D
M-026-01.bmp	M-045-20.bmp	D
M-048-01.bmp	M-020-26.bmp	D
W-020-01.bmp	W-039-26.bmp	D
W-032-01.bmp	W-005-13.bmp	D
W-012-01.bmp	W-040-10.bmp	D
W-035-01.bmp	W-045-04.bmp	D
W-025-01.bmp	W-002-19.bmp	D
W-022-01.bmp	W-019-17.bmp	D
M-001-01.bmp	M-031-16.bmp	D
M-012-01.bmp	M-011-20.bmp	D
M-001-01.bmp	M-016-04.bmp	D
M-004-01.bmp	M-011-19.bmp	D
W-032-01.bmp	W-018-09.bmp	D
M-050-01.bmp	M-030-20.bmp	D
M-030-01.bmp	M-046-24.bmp	D
W-028-01.bmp	W-021-05.bmp	D
M-013-01.bmp	M-036-17.bmp	D
W-034-01.bmp	W-049-06.bmp	D
W-028-01.bmp	W-009-07.bmp	D
W-029-01.bmp	W-032-05.bmp	D
W-022-01.bmp	W-043-26.bmp	D
W-009-01.bmp	W-029-02.bmp	D
M-036-01.bmp	M-032-13.bmp	D
W-024-01.bmp	W-029-18.bmp	D
W-035-01.bmp	W-030-23.bmp	D
M-045-01.bmp	M-035-02.bmp	D
M-035-01.bmp	M-017-10.bmp	D
W-045-01.bmp	W-001-08.bmp	D
M-039-01.bmp	M-017-03.bmp	D
M-035-01.bmp	M-033-13.bmp	D
W-019-01.bmp	W-046-16.bmp	D
W-017-01.bmp	W-004-15.bmp	D
W-046-01.bmp	W-032-22.bmp	D
W-048-01.bmp	W-009-03.bmp	D
M-025-01.bmp	M-011-23.bmp	D
W-016-01.bmp	W-044-26.bmp	D
M-024-01.bmp	M-014-18.bmp	D
W-017-01.bmp	W-046-08.bmp	D
M-049-01.bmp	M-011-14.bmp	D
M-013-01.bmp	M-006-03.bmp	D
M-009-01.bmp	M-002-17.bmp	D
M-045-01.bmp	M-044-26.bmp	D
W-014-01.bmp	W-017-23.bmp	D
M-047-01.bmp	M-024-03.bmp	D
M-005-01.bmp	M-031-26.bmp	D
W-026-01.bmp	W-024-25.bmp	D
W-027-01.bmp	W-012-07.bmp	D
M-035-01.bmp	M-025-25.bmp	D
M-017-01.bmp	M-045-02.bmp	D
W-030-01.bmp	W-016-08.bmp	D
W-010-01.bmp	W-016-07.bmp	D
W-026-01.bmp	W-016-22.bmp	D
W-044-01.bmp	W-023-24.bmp	D
W-023-01.bmp	W-016-07.bmp	D
M-014-01.bmp	M-019-22.bmp	D
W-040-01.bmp	W-038-23.bmp	D
M-012-01.bmp	M-008-13.bmp	D
W-024-01.bmp	W-043-13.bmp	D
M-022-01.bmp	M-013-11.bmp	D
W-014-01.bmp	W-002-10.bmp	D
W-022-01.bmp	W-024-17.bmp	D
W-015-01.bmp	W-024-17.bmp	D
W-041-01.bmp	W-010-23.bmp	D
M-016-01.bmp	M-027-16.bmp	D
M-036-01.bmp	M-048-19.bmp	D
W-006-01.bmp	W-045-06.bmp	D
M-002-01.bmp	M-043-03.bmp	D
M-042-01.bmp	M-015-08.bmp	D
M-042-01.bmp	M-029-12.bmp	D
M-025-01.bmp	M-034-13.bmp	D
M-011-01.bmp	M-014-06.bmp	D
M-046-01.bmp	M-037-11.bmp	D
W-016-01.bmp	W-017-19.bmp	D
W-012-01.bmp	W-005-12.bmp	D
M-040-01.bmp	M-023-07.bmp	D
W-014-01.bmp	W-009-10.bmp	D
W-012-01.bmp	W-002-19.bmp	D
W-047-01.bmp	W-022-11.bmp	D
M-033-01.bmp	M-024-10.bmp	D
W-031-01.bmp	W-012-20.bmp	D
W-036-01.bmp	W-003-23.bmp	D
W-046-01.bmp	W-007-18.bmp	D
W-038-01.bmp	W-008-13.bmp	D
M-025-01.bmp	M-013-03.bmp	D
M-020-01.bmp	M-040-23.bmp	D
W-028-01.bmp	W-019-12.bmp	D
W-022-01.bmp	W-013-07.bmp	D
W-007-01.bmp	W-023-21.bmp	D
M-041-01.bmp	M-027-03.bmp	D
W-007-01.bmp	W-047-05.bmp	D
W-023-01.bmp	W-044-18.bmp	D
M-039-01.bmp	M-001-06.bmp	D
W-004-01.bmp	W-025-13.bmp	D
M-034-01.bmp	M-024-13.bmp	D
M-002-01.bmp	M-045-10.bmp	D
W-045-01.bmp	W-019-12.bmp	D
W-039-01.bmp	W-005-20.bmp	D
W-030-01.bmp	W-039-08.bmp	D
W-049-01.bmp	W-028-08.bmp	D
W-006-01.bmp	W-036-05.bmp	D
W-019-01.bmp	W-045-17.bmp	D
M-031-01.bmp	M-026-15.bmp	D
W-022-01.bmp	W-030-22.bmp	D
M-029-01.bmp	M-045-18.bmp	D
M-046-01.bmp	M-042-17.bmp	D
M-031-01.bmp	M-023-05.bmp	D
W-040-01.bmp	W-028-23.bmp	D
M-044-01.bmp	M-021-04.bmp	D
M-042-01.bmp	M-002-06.bmp	D
M-034-01.bmp	M-015-07.bmp	D
M-021-01.bmp	M-011-15.bmp	D
M-023-01.bmp	M-033-24.bmp	D
W-031-01.bmp	W-047-26.bmp	D
M-016-01.bmp	M-032-05.bmp	D
M-004-01.bmp	M-040-19.bmp	D
W-042-01.bmp	W-022-24.bmp	D
W-015-01.bmp	W-026-18.bmp	D
M-039-01.bmp	M-044-20.bmp	D
W-031-01.bmp	W-036-11.bmp	D
M-042-01.bmp	M-012-26.bmp	D
M-032-01.bmp	M-045-09.bmp	D
M-046-01.bmp	M-018-08.bmp	D
M-014-01.bmp	M-018-06.bmp	D
M-020-01.bmp	M-044-26.bmp	D
M-005-01.bmp	M-023-12.bmp	D
W-032-01.bmp	W-022-04.bmp	D
M-008-01.bmp	M-045-04.bmp	D
M-044-01.bmp	M-019-25.bmp	D
W-037-01.bmp	W-004-09.bmp	D
M-012-01.bmp	M-003-17.bmp	D
M-038-01.bmp	M-048-25.bmp	D
W-042-01.bmp	W-038-16.bmp	D
M-048-01.bmp	M-032-25.bmp	D
M-015-01.bmp	M-002-26.bmp	D
W-016-01.bmp	W-036-06.bmp	D
M-016-01.bmp	M-005-15.bmp	D
M-040-01.bmp	M-050-26.bmp	D
M-015-01.bmp	M-027-14.bmp	D
M-015-01.bmp	M-006-22.bmp	D
M-004-01.bmp	M-046-14.bmp	D
M-001-01.bmp	M-036-08.bmp	D
W-028-01.bmp	W-033-15.bmp	D
M-028-01.bmp	M-046-21.bmp	D
M-025-01.bmp	M-049-10.bmp	D
W-038-01.bmp	W-016-24.bmp	D
M-048-01.bmp	M-010-23.bmp	D
M-012-01.bmp	M-028-11.bmp	D
M-003-01.bmp	M-013-13.bmp	D
M-046-01.bmp	M-008-08.bmp	D
M-032-01.bmp	M-028-03.bmp	D
W-046-01.bmp	W-026-16.bmp	D
M-001-01.bmp	M-040-18.bmp	D
M-037-01.bmp	M-009-23.bmp	D
M-015-01.bmp	M-012-13.bmp	D
W-042-01.bmp	W-013-12.bmp	D
M-026-01.bmp	M-047-24.bmp	D
W-049-01.bmp	W-043-13.bmp	D
W-013-01.bmp	W-042-16.bmp	D
W-032-01.bmp	W-008-21.bmp	D
W-016-01.bmp	W-021-17.bmp	D
W-003-01.bmp	W-020-13.bmp	D
M-035-01.bmp	M-026-16.bmp	D
W-038-01.bmp	W-021-05.bmp	D
W-024-01.bmp	W-041-23.bmp	D
W-021-01.bmp	W-045-11.bmp	D
W-031-01.bmp	W-037-25.bmp	D
W-010-01.bmp	W-007-11.bmp	D
W-010-01.bmp	W-044-22.bmp	D
M-006-01.bmp	M-048-12.bmp	D
W-031-01.bmp	W-007-26.bmp	D
M-018-01.bmp	M-015-24.bmp	D
M-005-01.bmp	M-028-18.bmp	D
M-022-01.bmp	M-032-04.bmp	D
M-025-01.bmp	M-044-10.bmp	D
W-041-01.bmp	W-032-21.bmp	D
W-047-01.bmp	W-008-16.bmp	D
M-005-01.bmp	M-039-15.bmp	D
M-015-01.bmp	M-021-18.bmp	D
M-013-01.bmp	M-019-04.bmp	D
W-028-01.bmp	W-010-14.bmp	D
W-043-01.bmp	W-007-23.bmp	D
M-022-01.bmp	M-046-26.bmp	D
W-045-01.bmp	W-002-13.bmp	D
M-016-01.bmp	M-041-12.bmp	D
W-040-01.bmp	W-050-13.bmp	D
W-043-01.bmp	W-038-09.bmp	D
W-047-01.bmp	W-025-13.bmp	D
M-015-01.bmp	M-036-08.bmp	D
M-046-01.bmp	M-009-16.bmp	D
W-026-01.bmp	W-044-24.bmp	D
M-046-01.bmp	M-030-21.bmp	D
W-006-01.bmp	W-026-10.bmp	D
M-015-01.bmp	M-049-04.bmp	D
M-035-01.bmp	M-046-05.bmp	D
M-033-01.bmp	M-041-15.bmp	D
M-046-01.bmp	M-029-06.bmp	D
M-023-01.bmp	M-048-14.bmp	D
W-037-01.bmp	W-045-13.bmp	D
W-048-01.bmp	W-008-25.bmp	D
M-043-01.bmp	M-016-06.bmp	D
M-010-01.bmp	M-004-03.bmp	D
W-045-01.bmp	W-022-09.bmp	D
W-008-01.bmp	W-036-02.bmp	D
M-019-01.bmp	M-021-12.bmp	D
W-015-01.bmp	W-024-24.bmp	D
W-028-01.bmp	W-026-12.bmp	D
W-021-01.bmp	W-047-25.bmp	D
M-011-01.bmp	M-007-26.bmp	D
W-007-01.bmp	W-021-07.bmp	D
W-038-01.bmp	W-023-08.bmp	D
M-025-01.bmp	M-001-17.bmp	D
M-017-01.bmp	M-022-22.bmp	D
W-037-01.bmp	W-003-18.bmp	D
M-021-01.bmp	M-039-06.bmp	D
M-005-01.bmp	M-042-25.bmp	D
M-025-01.bmp	M-036-10.bmp	D
W-047-01.bmp	W-003-13.bmp	D
W-031-01.bmp	W-042-14.bmp	D
M-014-01.bmp	M-003-17.bmp	D
W-004-01.bmp	W-007-15.bmp	D
W-009-01.bmp	W-028-23.bmp	D
W-004-01.bmp	W-027-12.bmp	D
W-032-01.bmp	W-009-17.bmp	D
M-003-01.bmp	M-023-16.bmp	D
W-005-01.bmp	W-043-04.bmp	D
M-010-01.bmp	M-014-05.bmp	D
W-025-01.bmp	W-047-12.bmp	D
W-034-01.bmp	W-031-13.bmp	D
W-017-01.bmp	W-050-07.bmp	D
W-047-01.bmp	W-032-16.bmp	D
M-021-01.bmp	M-025-04.bmp	D
M-046-01.bmp	M-018-18.bmp	D
M-021-01.bmp	M-031-11.bmp	D
W-024-01.bmp	W-010-05.bmp	D
W-008-01.bmp	W-010-03.bmp	D
W-030-01.bmp	W-048-06.bmp	D
M-046-01.bmp	M-041-15.bmp	D
W-036-01.bmp	W-003-09.bmp	D
M-020-01.bmp	M-050-26.bmp	D
M-038-01.bmp	M-025-22.bmp	D
W-012-01.bmp	W-006-07.bmp	D
M-001-01.bmp	M-021-20.bmp	D
W-009-01.bmp	W-021-16.bmp	D
W-025-01.bmp	W-030-19.bmp	D
W-041-01.bmp	W-045-22.bmp	D
M-043-01.bmp	M-032-20.bmp	D
M-001-01.bmp	M-050-03.bmp	D
W-020-01.bmp	W-009-11.bmp	D
M-046-01.bmp	M-047-06.bmp	D
M-013-01.bmp	M-050-18.bmp	D
W-032-01.bmp	W-043-03.bmp	D
M-036-01.bmp	M-033-17.bmp	D
W-033-01.bmp	W-024-19.bmp	D
M-026-01.bmp	M-045-10.bmp	D
M-006-01.bmp	M-042-14.bmp	D
W-034-01.bmp	W-009-10.bmp	D
W-010-01.bmp	W-047-05.bmp	D
M-024-01.bmp	M-023-13.bmp	D
W-038-01.bmp	W-050-26.bmp	D
M-035-01.bmp	M-028-24.bmp	D
M-030-01.bmp	M-042-19.bmp	D
M-014-01.bmp	M-023-24.bmp	D
M-045-01.bmp	M-050-07.bmp	D
M-048-01.bmp	M-038-06.bmp	D
M-035-01.bmp	M-043-13.bmp	D
M-007-01.bmp	M-043-11.bmp	D
W-023-01.bmp	W-030-14.bmp	D
M-039-01.bmp	M-008-07.bmp	D
W-019-01.bmp	W-037-04.bmp	D
M-008-01.bmp	M-033-13.bmp	D
W-039-01.bmp	W-014-15.bmp	D
M-050-01.bmp	M-001-25.bmp	D
M-043-01.bmp	M-025-13.bmp	D
W-021-01.bmp	W-048-18.bmp	D
M-043-01.bmp	M-050-15.bmp	D
M-006-01.bmp	M-039-20.bmp	D
M-042-01.bmp	M-007-06.bmp	D
M-022-01.bmp	M-043-02.bmp	D
M-013-01.bmp	M-041-26.bmp	D
M-025-01.bmp	M-043-21.bmp	D
M-039-01.bmp	M-047-02.bmp	D
W-002-01.bmp	W-011-15.bmp	D
M-022-01.bmp	M-048-15.bmp	D
M-008-01.bmp	M-010-11.bmp	D
W-001-01.bmp	W-007-16.bmp	D
M-016-01.bmp	M-014-11.bmp	D
M-025-01.bmp	M-023-12.bmp	D
M-030-01.bmp	M-007-09.bmp	D
M-022-01.bmp	M-039-08.bmp	D
M-044-01.bmp	M-046-18.bmp	D
W-021-01.bmp	W-004-20.bmp	D
M-008-01.bmp	M-040-06.bmp	D
W-043-01.bmp	W-050-14.bmp	D
M-034-01.bmp	M-037-11.bmp	D
M-015-01.bmp	M-049-16.bmp	D
W-050-01.bmp	W-021-11.bmp	D
M-006-01.bmp	M-020-03.bmp	D
W-028-01.bmp	W-022-23.bmp	D
W-037-01.bmp	W-048-11.bmp	D
M-034-01.bmp	M-046-08.bmp	D
M-011-01.bmp	M-021-06.bmp	D
M-029-01.bmp	M-036-11.bmp	D
W-026-01.bmp	W-037-14.bmp	D
W-015-01.bmp	W-028-13.bmp	D
M-036-01.bmp	M-021-09.bmp	D
M-040-01.bmp	M-003-21.bmp	D
W-041-01.bmp	W-034-17.bmp	D
M-049-01.bmp	M-015-10.bmp	D
W-002-01.bmp	W-032-24.bmp	D
W-048-01.bmp	W-023-09.bmp	D
W-006-01.bmp	W-025-07.bmp	D
M-002-01.bmp	M-005-19.bmp	D
W-029-01.bmp	W-037-22.bmp	D
M-018-01.bmp	M-016-13.bmp	D
W-023-01.bmp	W-039-10.bmp	D
W-044-01.bmp	W-047-21.bmp	D
M-011-01.bmp	M-043-07.bmp	D
W-039-01.bmp	W-050-14.bmp	D
W-047-01.bmp	W-017-20.bmp	D
M-015-01.bmp	M-040-08.bmp	D
M-043-01.bmp	M-005-24.bmp	D
W-026-01.bmp	W-017-23.bmp	D
W-009-01.bmp	W-033-21.bmp	D
M-023-01.bmp	M-019-24.bmp	D
M-050-01.bmp	M-034-12.bmp	D
M-044-01.bmp	M-040-09.bmp	D
W-003-01.bmp	W-009-23.bmp	D
M-004-01.bmp	M-010-04.bmp	D
W-037-01.bmp	W-029-10.bmp	D
M-023-01.bmp	M-006-06.bmp	D
M-048-01.bmp	M-006-07.bmp	D
M-047-01.bmp	M-031-23.bmp	D
W-015-01.bmp	W-021-04.bmp	D
M-012-01.bmp	M-010-15.bmp	D
W-014-01.bmp	W-019-15.bmp	D
W-045-01.bmp	W-031-16.bmp	D
M-041-01.bmp	M-004-04.bmp	D
W-043-01.bmp	W-048-12.bmp	D
W-028-01.bmp	W-035-20.bmp	D
M-050-01.bmp	M-005-12.bmp	D
M-041-01.bmp	M-049-12.bmp	D
W-012-01.bmp	W-019-23.bmp	D
M-012-01.bmp	M-010-20.bmp	D
M-040-01.bmp	M-039-14.bmp	D
M-023-01.bmp	M-011-05.bmp	D
W-046-01.bmp	W-003-11.bmp	D
W-029-01.bmp	W-028-17.bmp	D
M-007-01.bmp	M-049-17.bmp	D
M-015-01.bmp	M-017-22.bmp	D
M-037-01.bmp	M-015-08.bmp	D
M-017-01.bmp	M-013-11.bmp	D
W-037-01.bmp	W-046-15.bmp	D
W-040-01.bmp	W-003-12.bmp	D
M-020-01.bmp	M-025-09.bmp	D
W-033-01.bmp	W-043-20.bmp	D
M-044-01.bmp	M-048-20.bmp	D
W-006-01.bmp	W-009-04.bmp	D
M-005-01.bmp	M-011-21.bmp	D
M-042-01.bmp	M-037-07.bmp	D
M-025-01.bmp	M-010-04.bmp	D
W-036-01.bmp	W-042-17.bmp	D
M-031-01.bmp	M-006-10.bmp	D
W-042-01.bmp	W-017-06.bmp	D
M-007-01.bmp	M-046-26.bmp	D
W-042-01.bmp	W-025-14.bmp	D
M-050-01.bmp	M-004-13.bmp	D
W-033-01.bmp	W-025-16.bmp	D
M-005-01.bmp	M-034-19.bmp	D
W-035-01.bmp	W-028-07.bmp	D
M-027-01.bmp	M-026-25.bmp	D
W-013-01.bmp	W-008-21.bmp	D
W-020-01.bmp	W-011-02.bmp	D
M-013-01.bmp	M-035-13.bmp	D
W-010-01.bmp	W-007-20.bmp	D
M-045-01.bmp	M-014-14.bmp	D
W-024-01.bmp	W-011-03.bmp	D
M-033-01.bmp	M-005-03.bmp	D
W-046-01.bmp	W-020-16.bmp	D
M-050-01.bmp	M-025-26.bmp	D
M-030-01.bmp	M-029-24.bmp	D
M-039-01.bmp	M-002-06.bmp	D
M-016-01.bmp	M-015-22.bmp	D
W-030-01.bmp	W-026-10.bmp	D
W-019-01.bmp	W-001-08.bmp	D
W-046-01.bmp	W-044-10.bmp	D
M-033-01.bmp	M-034-22.bmp	D
W-002-01.bmp	W-038-22.bmp	D
M-015-01.bmp	M-024-20.bmp	D
W-042-01.bmp	W-037-06.bmp	D
M-030-01.bmp	M-035-09.bmp	D
M-019-01.bmp	M-024-23.bmp	D
W-009-01.bmp	W-033-10.bmp	D
W-022-01.bmp	W-021-26.bmp	D
M-033-01.bmp	M-017-18.bmp	D
M-014-01.bmp	M-007-21.bmp	D
M-018-01.bmp	M-022-24.bmp	D
W-019-01.bmp	W-036-02.bmp	D
M-033-01.bmp	M-008-15.bmp	D
W-037-01.bmp	W-007-05.bmp	D
W-039-01.bmp	W-030-18.bmp	D
M-017-01.bmp	M-024-04.bmp	D
W-046-01.bmp	W-003-13.bmp	D
M-048-01.bmp	M-033-05.bmp	D
W-048-01.bmp	W-029-16.bmp	D
W-041-01.bmp	W-043-22.bmp	D
W-049-01.bmp	W-039-02.bmp	D
W-015-01.bmp	W-023-24.bmp	D
W-014-01.bmp	W-006-22.bmp	D
W-002-01.bmp	W-040-19.bmp	D
W-014-01.bmp	W-038-18.bmp	D
W-024-01.bmp	W-032-03.bmp	D
W-043-01.bmp	W-033-25.bmp	D
M-002-01.bmp	M-019-15.bmp	D
W-037-01.bmp	W-035-10.bmp	D
M-005-01.bmp	M-018-07.bmp	D
M-040-01.bmp	M-042-26.bmp	D
W-050-01.bmp	W-022-18.bmp	D
M-001-01.bmp	M-012-26.bmp	D
W-013-01.bmp	W-002-12.bmp	D
W-023-01.bmp	W-004-16.bmp	D
M-001-01.bmp	M-017-05.bmp	D
W-039-01.bmp	W-016-04.bmp	D
M-041-01.bmp	M-033-05.bmp	D
M-037-01.bmp	M-050-20.bmp	D
W-006-01.bmp	W-022-09.bmp	D
W-012-01.bmp	W-013-12.bmp	D
W-001-01.bmp	W-038-16.bmp	D
W-010-01.bmp	W-011-04.bmp	D
W-004-01.bmp	W-007-25.bmp	D
M-029-01.bmp	M-006-09.bmp	D
W-029-01.bmp	W-016-07.bmp	D
M-042-01.bmp	M-041-19.bmp	D
M-015-01.bmp	M-035-25.bmp	D
M-008-01.bmp	M-005-05.bmp	D
W-029-01.bmp	W-024-25.bmp	D
M-028-01.bmp	M-043-04.bmp	D
M-025-01.bmp	M-019-14.bmp	D
M-002-01.bmp	M-049-09.bmp	D
W-025-01.bmp	W-026-06.bmp	D
M-021-01.bmp	M-006-24.bmp	D
M-046-01.bmp	M-041-14.bmp	D
M-004-01.bmp	M-027-22.bmp	D
M-012-01.bmp	M-049-05.bmp	D
W-026-01.bmp	W-014-04.bmp	D
M-027-01.bmp	M-016-26.bmp	D
M-029-01.bmp	M-045-16.bmp	D
W-017-01.bmp	W-033-20.bmp	D
W-050-01.bmp	W-015-26.bmp	D
M-013-01.bmp	M-049-23.bmp	D
M-017-01.bmp	M-023-14.bmp	D
M-044-01.bmp	M-029-21.bmp	D
M-015-01.bmp	M-008-03.bmp	D
M-025-01.bmp	M-038-06.bmp	D
W-022-01.bmp	W-042-21.bmp	D
M-033-01.bmp	M-034-10.bmp	D
M-034-01.bmp	M-049-07.bmp	D
M-007-01.bmp	M-023-05.bmp	D
W-006-01.bmp	W-044-12.bmp	D
W-014-01.bmp	W-044-06.bmp	D
M-024-01.bmp	M-023-11.bmp	D
M-025-01.bmp	M-032-15.bmp	D
W-009-01.bmp	W-041-19.bmp	D
W-004-01.bmp	W-050-02.bmp	D
M-029-01.bmp	M-022-23.bmp	D
W-026-01.bmp	W-010-09.bmp	D
W-010-01.bmp	W-040-06.bmp	D
M-036-01.bmp	M-001-20.bmp	D
W-011-01.bmp	W-010-13.bmp	D
W-027-01.bmp	W-023-26.bmp	D
W-046-01.bmp	W-011-26.bmp	D
W-004-01.bmp	W-005-04.bmp	D
M-023-01.bmp	M-002-09.bmp	D
W-032-01.bmp	W-021-09.bmp	D
W-040-01.bmp	W-043-06.bmp	D
M-025-01.bmp	M-032-16.bmp	D
W-016-01.bmp	W-032-23.bmp	D
W-007-01.bmp	W-021-08.bmp	D
W-020-01.bmp	W-021-14.bmp	D
M-016-01.bmp	M-011-23.bmp	D
W-011-01.bmp	W-035-20.bmp	D
W-010-01.bmp	W-008-10.bmp	D
M-018-01.bmp	M-011-05.bmp	D
W-039-01.bmp	W-012-05.bmp	D
M-025-01.bmp	M-004-23.bmp	D
M-016-01.bmp	M-044-07.bmp	D
M-041-01.bmp	M-043-08.bmp	D
W-016-01.bmp	W-005-14.bmp	D
M-023-01.bmp	M-032-12.bmp	D
M-048-01.bmp	M-003-08.bmp	D
W-005-01.bmp	W-026-03.bmp	D
M-042-01.bmp	M-032-16.bmp	D
M-023-01.bmp	M-016-07.bmp	D
M-015-01.bmp	M-025-22.bmp	D
W-032-01.bmp	W-020-07.bmp	D
W-036-01.bmp	W-026-02.bmp	D
M-014-01.bmp	M-008-18.bmp	D
W-033-01.bmp	W-049-26.bmp	D
M-029-01.bmp	M-042-25.bmp	D
M-022-01.bmp	M-015-26.bmp	D
W-027-01.bmp	W-022-23.bmp	D
M-022-01.bmp	M-047-25.bmp	D
M-014-01.bmp	M-040-23.bmp	D
W-035-01.bmp	W-006-26.bmp	D
W-041-01.bmp	W-012-14.bmp	D
W-046-01.bmp	W-050-09.bmp	D
M-025-01.bmp	M-027-18.bmp	D
W-024-01.bmp	W-035-19.bmp	D
W-029-01.bmp	W-044-18.bmp	D
M-046-01.bmp	M-039-17.bmp	D
M-022-01.bmp	M-035-21.bmp	D
M-001-01.bmp	M-017-20.bmp	D
M-045-01.bmp	M-024-12.bmp	D
W-020-01.bmp	W-038-18.bmp	D
M-011-01.bmp	M-022-10.bmp	D
W-042-01.bmp	W-050-10.bmp	D
W-027-01.bmp	W-033-04.bmp	D
W-012-01.bmp	W-050-02.bmp	D
W-016-01.bmp	W-030-06.bmp	D
M-003-01.bmp	M-004-15.bmp	D
W-038-01.bmp	W-026-12.bmp	D
M-046-01.bmp	M-005-04.bmp	D
W-016-01.bmp	W-030-16.bmp	D
M-030-01.bmp	M-022-16.bmp	D
W-027-01.bmp	W-044-16.bmp	D
M-042-01.bmp	M-024-06.bmp	D
W-022-01.bmp	W-049-14.bmp	D
W-018-01.bmp	W-017-25.bmp	D
W-040-01.bmp	W-021-03.bmp	D
W-023-01.bmp	W-041-19.bmp	D
W-043-01.bmp	W-017-12.bmp	D
M-042-01.bmp	M-039-09.bmp	D
W-045-01.bmp	W-044-05.bmp	D
M-046-01.bmp	M-039-20.bmp	D
W-041-01.bmp	W-030-15.bmp	D
M-016-01.bmp	M-018-18.bmp	D
W-038-01.bmp	W-050-12.bmp	D
M-016-01.bmp	M-020-20.bmp	D
M-045-01.bmp	M-029-17.bmp	D
M-003-01.bmp	M-036-09.bmp	D
M-050-01.bmp	M-003-11.bmp	D
W-038-01.bmp	W-033-14.bmp	D
W-028-01.bmp	W-037-12.bmp	D
W-007-01.bmp	W-003-19.bmp	D
W-035-01.bmp	W-011-11.bmp	D
M-049-01.bmp	M-041-17.bmp	D
W-038-01.bmp	W-032-13.bmp	D
W-010-01.bmp	W-049-02.bmp	D
M-026-01.bmp	M-021-26.bmp	D
W-046-01.bmp	W-011-17.bmp	D
M-021-01.bmp	M-033-22.bmp	D
M-048-01.bmp	M-004-11.bmp	D
W-028-01.bmp	W-026-21.bmp	D
W-020-01.bmp	W-042-02.bmp	D
M-028-01.bmp	M-023-23.bmp	D
W-011-01.bmp	W-047-13.bmp	D
M-021-01.bmp	M-038-09.bmp	D
W-018-01.bmp	W-011-17.bmp	D
M-029-01.bmp	M-017-20.bmp	D
W-050-01.bmp	W-003-14.bmp	D
M-049-01.bmp	M-005-11.bmp	D
M-027-01.bmp	M-011-14.bmp	D
W-003-01.bmp	W-050-10.bmp	D
W-012-01.bmp	W-045-15.bmp	D
W-027-01.bmp	W-049-11.bmp	D
M-006-01.bmp	M-036-07.bmp	D
M-027-01.bmp	M-021-09.bmp	D
M-019-01.bmp	M-016-12.bmp	D
M-004-01.bmp	M-023-14.bmp	D
M-048-01.bmp	M-042-20.bmp	D
M-001-01.bmp	M-048-20.bmp	D
M-039-01.bmp	M-006-09.bmp	D
M-012-01.bmp	M-046-17.bmp	D
M-016-01.bmp	M-007-14.bmp	D
W-019-01.bmp	W-034-20.bmp	D
W-011-01.bmp	W-034-17.bmp	D
W-042-01.bmp	W-043-02.bmp	D
M-021-01.bmp	M-015-06.bmp	D
M-017-01.bmp	M-008-23.bmp	D
M-011-01.bmp	M-013-03.bmp	D
M-042-01.bmp	M-010-03.bmp	D
W-049-01.bmp	W-025-07.bmp	D
W-010-01.bmp	W-047-10.bmp	D
W-005-01.bmp	W-006-09.bmp	D
M-012-01.bmp	M-018-12.bmp	D
M-042-01.bmp	M-012-03.bmp	D
M-046-01.bmp	M-022-02.bmp	D
W-049-01.bmp	W-029-17.bmp	D
W-032-01.bmp	W-004-08.bmp	D
W-033-01.bmp	W-047-05.bmp	D
W-009-01.bmp	W-020-11.bmp	D
W-012-01.bmp	W-030-24.bmp	D
M-020-01.bmp	M-047-26.bmp	D
W-010-01.bmp	W-038-17.bmp	D
M-009-01.bmp	M-040-12.bmp	D
W-046-01.bmp	W-040-09.bmp	D
M-022-01.bmp	M-047-17.bmp	D
M-005-01.bmp	M-027-05.bmp	D
M-019-01.bmp	M-016-04.bmp	D
W-023-01.bmp	W-003-25.bmp	D
M-037-01.bmp	M-050-05.bmp	D
M-031-01.bmp	M-030-19.bmp	D
W-013-01.bmp	W-046-06.bmp	D
W-017-01.bmp	W-043-08.bmp	D
M-044-01.bmp	M-018-17.bmp	D
W-013-01.bmp	W-021-20.bmp	D
M-033-01.bmp	M-013-18.bmp	D
W-026-01.bmp	W-001-19.bmp	D
M-037-01.bmp	M-004-19.bmp	D
M-040-01.bmp	M-036-08.bmp	D
M-049-01.bmp	M-044-23.bmp	D
M-008-01.bmp	M-026-22.bmp	D
M-040-01.bmp	M-010-14.bmp	D
W-032-01.bmp	W-047-17.bmp	D
W-007-01.bmp	W-023-24.bmp	D
W-013-01.bmp	W-006-26.bmp	D
W-027-01.bmp	W-010-08.bmp	D
W-034-01.bmp	W-010-12.bmp	D
W-004-01.bmp	W-014-18.bmp	D
M-005-01.bmp	M-003-18.bmp	D
W-041-01.bmp	W-020-22.bmp	D
W-009-01.bmp	W-032-23.bmp	D
W-019-01.bmp	W-021-18.bmp	D
W-050-01.bmp	W-006-15.bmp	D
W-045-01.bmp	W-014-19.bmp	D
W-033-01.bmp	W-045-10.bmp	D
M-042-01.bmp	M-007-02.bmp	D
M-044-01.bmp	M-016-05.bmp	D
W-020-01.bmp	W-013-12.bmp	D
W-044-01.bmp	W-024-06.bmp	D
M-006-01.bmp	M-013-19.bmp	D
W-007-01.bmp	W-022-09.bmp	D
M-031-01.bmp	M-033-12.bmp	D
M-038-01.bmp	M-010-15.bmp	D
M-016-01.bmp	M-030-13.bmp	D
W-035-01.bmp	W-001-23.bmp	D
W-003-01.bmp	W-044-06.bmp	D
W-027-01.bmp	W-042-20.bmp	D
W-045-01.bmp	W-050-17.bmp	D
W-046-01.bmp	W-004-07.bmp	D
M-041-01.bmp	M-049-26.bmp	D
M-026-01.bmp	M-041-24.bmp	D
W-002-01.bmp	W-046-12.bmp	D
M-047-01.bmp	M-024-24.bmp	D
W-041-01.bmp	W-043-11.bmp	D
M-024-01.bmp	M-005-06.bmp	D
M-005-01.bmp	M-011-18.bmp	D
W-050-01.bmp	W-011-02.bmp	D
M-027-01.bmp	M-045-11.bmp	D
W-028-01.bmp	W-024-13.bmp	D
W-030-01.bmp	W-033-14.bmp	D
M-018-01.bmp	M-028-16.bmp	D
M-030-01.bmp	M-033-20.bmp	D
W-045-01.bmp	W-050-06.bmp	D
W-050-01.bmp	W-043-08.bmp	D
M-037-01.bmp	M-049-16.bmp	D
W-036-01.bmp	W-041-23.bmp	D
M-039-01.bmp	M-034-02.bmp	D
W-049-01.bmp	W-011-23.bmp	D
W-020-01.bmp	W-025-24.bmp	D
W-023-01.bmp	W-021-03.bmp	D
M-020-01.bmp	M-024-13.bmp	D
M-047-01.bmp	M-018-24.bmp	D
M-018-01.bmp	M-016-05.bmp	D
M-017-01.bmp	M-003-02.bmp	D
M-007-01.bmp	M-035-23.bmp	D
M-001-01.bmp	M-029-17.bmp	D
M-003-01.bmp	M-039-18.bmp	D
M-032-01.bmp	M-012-23.bmp	D
M-049-01.bmp	M-006-10.bmp	D
M-047-01.bmp	M-046-09.bmp	D
M-045-01.bmp	M-021-02.bmp	D
M-009-01.bmp	M-034-16.bmp	D
W-020-01.bmp	W-037-21.bmp	D
M-009-01.bmp	M-015-18.bmp	D
W-017-01.bmp	W-025-23.bmp	D
M-016-01.bmp	M-001-09.bmp	D
M-005-01.bmp	M-004-22.bmp	D
M-002-01.bmp	M-006-23.bmp	D
W-026-01.bmp	W-032-23.bmp	D
W-015-01.bmp	W-038-06.bmp	D
M-027-01.bmp	M-002-04.bmp	D
W-001-01.bmp	W-004-08.bmp	D
W-026-01.bmp	W-036-23.bmp	D
W-002-01.bmp	W-021-13.bmp	D
M-020-01.bmp	M-006-19.bmp	D
W-048-01.bmp	W-031-07.bmp	D
W-013-01.bmp	W-016-04.bmp	D
W-040-01.bmp	W-047-25.bmp	D
W-046-01.bmp	W-044-20.bmp	D
W-049-01.bmp	W-034-09.bmp	D
M-021-01.bmp	M-048-26.bmp	D
M-027-01.bmp	M-042-04.bmp	D
W-012-01.bmp	W-025-16.bmp	D
W-003-01.bmp	W-019-19.bmp	D
M-045-01.bmp	M-039-14.bmp	D
W-012-01.bmp	W-050-24.bmp	D
W-021-01.bmp	W-009-08.bmp	D
W-041-01.bmp	W-005-04.bmp	D
M-050-01.bmp	M-009-06.bmp	D
M-031-01.bmp	M-025-03.bmp	D
W-019-01.bmp	W-005-12.bmp	D
W-033-01.bmp	W-040-26.bmp	D
W-014-01.bmp	W-038-14.bmp	D
W-033-01.bmp	W-025-19.bmp	D
W-050-01.bmp	W-043-22.bmp	D
W-015-01.bmp	W-011-24.bmp	D
W-025-01.bmp	W-049-23.bmp	D
M-022-01.bmp	M-033-23.bmp	D
W-006-01.bmp	W-016-08.bmp	D
W-016-01.bmp	W-004-25.bmp	D
M-002-01.bmp	M-022-10.bmp	D
W-050-01.bmp	W-006-08.bmp	D
W-046-01.bmp	W-017-08.bmp	D
M-034-01.bmp	M-049-22.bmp	D
W-002-01.bmp	W-025-13.bmp	D
W-004-01.bmp	W-026-21.bmp	D
M-036-01.bmp	M-015-11.bmp	D
M-032-01.bmp	M-045-17.bmp	D
M-023-01.bmp	M-015-02.bmp	D
M-018-01.bmp	M-043-23.bmp	D
W-039-01.bmp	W-035-03.bmp	D
W-022-01.bmp	W-049-24.bmp	D
M-005-01.bmp	M-046-20.bmp	D
M-019-01.bmp	M-048-08.bmp	D
M-040-01.bmp	M-031-23.bmp	D
W-025-01.bmp	W-003-26.bmp	D
W-034-01.bmp	W-023-15.bmp	D
W-038-01.bmp	W-035-24.bmp	D
M-020-01.bmp	M-032-06.bmp	D
M-022-01.bmp	M-030-09.bmp	D
M-024-01.bmp	M-031-16.bmp	D
W-003-01.bmp	W-038-02.bmp	D
M-017-01.bmp	M-029-18.bmp	D
W-007-01.bmp	W-042-07.bmp	D
M-048-01.bmp	M-008-25.bmp	D
M-037-01.bmp	M-027-23.bmp	D
W-041-01.bmp	W-050-07.bmp	D
W-008-01.bmp	W-037-24.bmp	D
M-010-01.bmp	M-049-23.bmp	D
M-025-01.bmp	M-034-20.bmp	D
W-008-01.bmp	W-043-03.bmp	D
W-046-01.bmp	W-027-10.bmp	D
W-004-01.bmp	W-025-18.bmp	D
W-005-01.bmp	W-050-09.bmp	D
W-012-01.bmp	W-043-22.bmp	D
M-008-01.bmp	M-011-14.bmp	D
M-022-01.bmp	M-006-11.bmp	D
M-021-01.bmp	M-008-04.bmp	D
M-047-01.bmp	M-028-21.bmp	D
M-005-01.bmp	M-045-25.bmp	D
M-002-01.bmp	M-024-10.bmp	D
M-039-01.bmp	M-018-20.bmp	D
M-033-01.bmp	M-012-15.bmp	D
W-045-01.bmp	W-043-12.bmp	D
W-050-01.bmp	W-006-25.bmp	D
M-010-01.bmp	M-030-22.bmp	D
W-039-01.bmp	W-028-24.bmp	D
W-026-01.bmp	W-041-26.bmp	D
M-036-01.bmp	M-040-06.bmp	D
M-008-01.bmp	M-038-06.bmp	D
W-005-01.bmp	W-019-20.bmp	D
M-012-01.bmp	M-011-15.bmp	D
M-008-01.bmp	M-020-26.bmp	D
M-046-01.bmp	M-036-11.bmp	D
W-012-01.bmp	W-032-02.bmp	D
W-026-01.bmp	W-004-25.bmp	D
W-005-01.bmp	W-014-15.bmp	D
W-034-01.bmp	W-020-04.bmp	D
M-036-01.bmp	M-014-21.bmp	D
M-007-01.bmp	M-011-02.bmp	D
W-007-01.bmp	W-047-18.bmp	D
M-026-01.bmp	M-016-05.bmp	D
M-041-01.bmp	M-035-19.bmp	D
M-036-01.bmp	M-028-08.bmp	D
M-001-01.bmp	M-045-22.bmp	D
W-012-01.bmp	W-031-13.bmp	D
W-041-01.bmp	W-043-15.bmp	D
W-033-01.bmp	W-034-06.bmp	D
M-045-01.bmp	M-036-26.bmp	D
M-038-01.bmp	M-035-11.bmp	D
M-022-01.bmp	M-037-14.bmp	D
W-041-01.bmp	W-018-05.bmp	D
M-013-01.bmp	M-019-10.bmp	D
W-018-01.bmp	W-006-12.bmp	D
W-008-01.bmp	W-016-21.bmp	D
M-041-01.bmp	M-040-06.bmp	D
W-007-01.bmp	W-005-07.bmp	D
M-022-01.bmp	M-008-09.bmp	D
W-048-01.bmp	W-026-10.bmp	D
W-035-01.bmp	W-013-05.bmp	D
M-005-01.bmp	M-034-02.bmp	D
W-009-01.bmp	W-043-13.bmp	D
W-042-01.bmp	W-004-06.bmp	D
M-045-01.bmp	M-003-10.bmp	D
M-021-01.bmp	M-002-26.bmp	D
W-031-01.bmp	W-019-22.bmp	D
W-012-01.bmp	W-031-20.bmp	D
W-014-01.bmp	W-047-02.bmp	D
W-003-01.bmp	W-024-18.bmp	D
M-033-01.bmp	M-027-13.bmp	D
W-009-01.bmp	W-033-22.bmp	D
W-008-01.bmp	W-045-09.bmp	D
W-015-01.bmp	W-010-19.bmp	D
M-001-01.bmp	M-008-10.bmp	D
W-037-01.bmp	W-033-26.bmp	D
W-016-01.bmp	W-027-12.bmp	D
W-032-01.bmp	W-041-04.bmp	D
W-049-01.bmp	W-037-26.bmp	D
W-039-01.bmp	W-036-02.bmp	D
W-021-01.bmp	W-042-12.bmp	D
M-012-01.bmp	M-020-17.bmp	D
M-048-01.bmp	M-031-03.bmp	D
M-042-01.bmp	M-031-14.bmp	D
W-014-01.bmp	W-011-14.bmp	D
M-009-01.bmp	M-028-15.bmp	D
M-011-01.bmp	M-029-07.bmp	D
M-039-01.bmp	M-048-10.bmp	D
W-016-01.bmp	W-033-16.bmp	D
W-038-01.bmp	W-041-04.bmp	D
M-027-01.bmp	M-026-12.bmp	D
M-010-01.bmp	M-026-22.bmp	D
M-019-01.bmp	M-030-04.bmp	D
M-008-01.bmp	M-007-23.bmp	D
M-033-01.bmp	M-045-20.bmp	D
M-043-01.bmp	M-031-26.bmp	D
M-021-01.bmp	M-022-05.bmp	D
W-010-01.bmp	W-004-05.bmp	D
W-023-01.bmp	W-036-16.bmp	D
W-004-01.bmp	W-013-23.bmp	D
W-048-01.bmp	W-033-17.bmp	D
W-021-01.bmp	W-032-20.bmp	D
M-043-01.bmp	M-020-05.bmp	D
W-039-01.bmp	W-025-20.bmp	D
W-049-01.bmp	W-009-21.bmp	D
W-004-01.bmp	W-028-14.bmp	D
W-038-01.bmp	W-044-09.bmp	D
W-027-01.bmp	W-034-19.bmp	D
W-041-01.bmp	W-017-07.bmp	D
M-040-01.bmp	M-044-06.bmp	D
W-009-01.bmp	W-008-18.bmp	D
M-027-01.bmp	M-001-09.bmp	D
M-011-01.bmp	M-025-14.bmp	D
W-030-01.bmp	W-012-11.bmp	D
M-021-01.bmp	M-040-06.bmp	D
W-027-01.bmp	W-004-26.bmp	D
M-035-01.bmp	M-013-11.bmp	D
W-001-01.bmp	W-016-06.bmp	D
W-022-01.bmp	W-027-23.bmp	D
M-010-01.bmp	M-016-06.bmp	D
M-013-01.bmp	M-045-13.bmp	D
M-014-01.bmp	M-027-19.bmp	D
W-004-01.bmp	W-038-04.bmp	D
W-001-01.bmp	W-043-20.bmp	D
W-014-01.bmp	W-017-09.bmp	D
M-004-01.bmp	M-021-10.bmp	D
M-036-01.bmp	M-020-11.bmp	D
W-040-01.bmp	W-010-08.bmp	D
M-050-01.bmp	M-025-02.bmp	D
W-025-01.bmp	W-043-12.bmp	D
W-039-01.bmp	W-021-17.bmp	D
M-019-01.bmp	M-016-13.bmp	D
M-023-01.bmp	M-025-03.bmp	D
W-027-01.bmp	W-038-22.bmp	D
W-035-01.bmp	W-027-15.bmp	D
W-028-01.bmp	W-012-17.bmp	D
W-007-01.bmp	W-026-15.bmp	D
W-045-01.bmp	W-021-09.bmp	D
M-049-01.bmp	M-036-20.bmp	D
M-039-01.bmp	M-005-25.bmp	D
M-021-01.bmp	M-043-19.bmp	D
W-046-01.bmp	W-028-13.bmp	D
M-011-01.bmp	M-024-26.bmp	D
M-014-01.bmp	M-040-08.bmp	D
W-015-01.bmp	W-004-17.bmp	D
M-011-01.bmp	M-044-10.bmp	D
W-029-01.bmp	W-022-23.bmp	D
W-017-01.bmp	W-044-04.bmp	D
M-049-01.bmp	M-021-10.bmp	D
W-029-01.bmp	W-004-23.bmp	D
M-035-01.bmp	M-018-07.bmp	D
W-001-01.bmp	W-015-13.bmp	D
W-028-01.bmp	W-049-05.bmp	D
M-035-01.bmp	M-036-12.bmp	D
W-029-01.bmp	W-033-17.bmp	D
M-044-01.bmp	M-043-24.bmp	D
M-010-01.bmp	M-030-06.bmp	D
M-030-01.bmp	M-008-12.bmp	D
M-003-01.bmp	M-021-14.bmp	D
M-039-01.bmp	M-017-03.bmp	D
W-045-01.bmp	W-014-09.bmp	D
W-047-01.bmp	W-002-20.bmp	D
M-009-01.bmp	M-032-02.bmp	D
M-048-01.bmp	M-011-24.bmp	D
M-026-01.bmp	M-023-19.bmp	D
W-046-01.bmp	W-038-18.bmp	D
W-034-01.bmp	W-003-16.bmp	D
M-042-01.bmp	M-033-18.bmp	D
M-036-01.bmp	M-005-11.bmp	D
W-006-01.bmp	W-003-12.bmp	D
W-028-01.bmp	W-012-05.bmp	D
M-048-01.bmp	M-044-16.bmp	D
M-021-01.bmp	M-001-02.bmp	D
W-006-01.bmp	W-008-09.bmp	D
W-032-01.bmp	W-042-08.bmp	D
W-049-01.bmp	W-011-08.bmp	D
M-048-01.bmp	M-038-03.bmp	D
W-043-01.bmp	W-028-06.bmp	D
W-035-01.bmp	W-027-04.bmp	D
M-027-01.bmp	M-011-24.bmp	D
W-031-01.bmp	W-012-02.bmp	D
W-002-01.bmp	W-005-11.bmp	D
M-019-01.bmp	M-005-17.bmp	D
M-043-01.bmp	M-028-03.bmp	D
W-046-01.bmp	W-039-05.bmp	D
W-043-01.bmp	W-006-24.bmp	D
W-026-01.bmp	W-025-18.bmp	D
W-018-01.bmp	W-047-24.bmp	D
M-026-01.bmp	M-045-26.bmp	D
M-039-01.bmp	M-009-13.bmp	D
W-005-01.bmp	W-040-05.bmp	D
M-010-01.bmp	M-004-09.bmp	D
W-032-01.bmp	W-045-06.bmp	D
M-016-01.bmp	M-034-22.bmp	D
W-043-01.bmp	W-050-08.bmp	D
M-042-01.bmp	M-045-23.bmp	D
M-035-01.bmp	M-021-04.bmp	D
M-005-01.bmp	M-004-04.bmp	D
W-010-01.bmp	W-024-12.bmp	D
M-043-01.bmp	M-011-10.bmp	D
W-028-01.bmp	W-017-16.bmp	D
W-035-01.bmp	W-004-03.bmp	D
W-038-01.bmp	W-037-15.bmp	D
W-049-01.bmp	W-031-22.bmp	D
W-047-01.bmp	W-042-20.bmp	D
W-004-01.bmp	W-025-16.bmp	D
W-041-01.bmp	W-017-22.bmp	D
M-038-01.bmp	M-035-22.bmp	D
M-022-01.bmp	M-045-13.bmp	D
W-018-01.bmp	W-015-04.bmp	D
W-032-01.bmp	W-013-12.bmp	D
W-040-01.bmp	W-015-04.bmp	D
W-028-01.bmp	W-041-18.bmp	D
W-003-01.bmp	W-028-03.bmp	D
M-036-01.bmp	M-041-10.bmp	D
W-025-01.bmp	W-019-25.bmp	D
M-010-01.bmp	M-018-08.bmp	D
M-040-01.bmp	M-047-13.bmp	D
M-012-01.bmp	M-011-25.bmp	D
M-036-01.bmp	M-021-14.bmp	D
M-018-01.bmp	M-031-11.bmp	D
W-045-01.bmp	W-043-11.bmp	D
W-027-01.bmp	W-009-23.bmp	D
W-020-01.bmp	W-037-16.bmp	D
M-027-01.bmp	M-044-23.bmp	D
W-032-01.bmp	W-027-04.bmp	D
W-012-01.bmp	W-017-13.bmp	D
W-040-01.bmp	W-011-18.bmp	D
W-040-01.bmp	W-031-25.bmp	D
W-039-01.bmp	W-024-03.bmp	D
W-002-01.bmp	W-042-05.bmp	D
W-032-01.bmp	W-038-04.bmp	D
M-034-01.bmp	M-003-13.bmp	D
M-009-01.bmp	M-010-19.bmp	D
W-009-01.bmp	W-005-18.bmp	D
W-021-01.bmp	W-007-15.bmp	D
M-032-01.bmp	M-006-25.bmp	D
W-048-01.bmp	W-034-10.bmp	D
W-049-01.bmp	W-045-03.bmp	D
W-007-01.bmp	W-041-19.bmp	D
W-017-01.bmp	W-031-15.bmp	D
M-015-01.bmp	M-026-18.bmp	D
M-042-01.bmp	M-031-19.bmp	D
W-045-01.bmp	W-035-23.bmp	D
W-037-01.bmp	W-008-05.bmp	D
M-017-01.bmp	M-045-08.bmp	D
M-015-01.bmp	M-041-17.bmp	D
M-013-01.bmp	M-004-06.bmp	D
W-036-01.bmp	W-043-10.bmp	D
W-047-01.bmp	W-019-07.bmp	D
M-024-01.bmp	M-020-11.bmp	D
M-017-01.bmp	M-021-08.bmp	D
W-012-01.bmp	W-003-05.bmp	D
W-029-01.bmp	W-025-17.bmp	D
W-023-01.bmp	W-048-16.bmp	D
M-038-01.bmp	M-040-14.bmp	D
M-033-01.bmp	M-021-04.bmp	D
M-014-01.bmp	M-019-10.bmp	D
M-041-01.bmp	M-029-09.bmp	D
W-015-01.bmp	W-007-19.bmp	D
W-045-01.bmp	W-027-24.bmp	D
W-038-01.bmp	W-018-13.bmp	D
W-023-01.bmp	W-037-19.bmp	D
W-003-01.bmp	W-030-06.bmp	D
M-030-01.bmp	M-047-18.bmp	D
M-019-01.bmp	M-039-07.bmp	D
W-049-01.bmp	W-040-04.bmp	D
M-015-01.bmp	M-028-21.bmp	D
W-009-01.bmp	W-007-23.bmp	D
W-013-01.bmp	W-021-09.bmp	D
W-033-01.bmp	W-041-19.bmp	D
W-021-01.bmp	W-048-02.bmp	D
M-007-01.bmp	M-020-16.bmp	D
M-010-01.bmp	M-034-14.bmp	D
W-044-01.bmp	W-010-22.bmp	D
M-001-01.bmp	M-029-22.bmp	D
W-012-01.bmp	W-024-07.bmp	D
M-031-01.bmp	M-008-15.bmp	D
M-031-01.bmp	M-047-15.bmp	D
M-035-01.bmp	M-022-19.bmp	D
W-042-01.bmp	W-036-10.bmp	D
W-022-01.bmp	W-001-10.bmp	D
M-035-01.bmp	M-048-20.bmp	D
M-044-01.bmp	M-035-13.bmp	D
W-003-01.bmp	W-041-13.bmp	D
W-008-01.bmp	W-029-18.bmp	D
W-024-01.bmp	W-015-26.bmp	D
M-011-01.bmp	M-010-12.bmp	D
M-007-01.bmp	M-021-16.bmp	D
W-016-01.bmp	W-030-09.bmp	D
M-002-01.bmp	M-037-24.bmp	D
M-042-01.bmp	M-034-08.bmp	D
W-042-01.bmp	W-005-04.bmp	D
M-027-01.bmp	M-050-07.bmp	D
W-030-01.bmp	W-041-24.bmp	D
W-022-01.bmp	W-005-10.bmp	D
M-015-01.bmp	M-043-06.bmp	D
W-040-01.bmp	W-028-24.bmp	D
W-009-01.bmp	W-033-20.bmp	D
M-033-01.bmp	M-025-13.bmp	D
W-017-01.bmp	W-016-07.bmp	D
M-049-01.bmp	M-018-06.bmp	D
W-015-01.bmp	W-021-17.bmp	D
W-023-01.bmp	W-031-10.bmp	D
W-040-01.bmp	W-027-23.bmp	D
M-047-01.bmp	M-043-20.bmp	D
W-035-01.bmp	W-003-09.bmp	D
W-014-01.bmp	W-049-05.bmp	D
M-009-01.bmp	M-002-15.bmp	D
W-036-01.bmp	W-019-09.bmp	D
W-048-01.bmp	W-034-24.bmp	D
M-034-01.bmp	M-027-22.bmp	D
W-010-01.bmp	W-008-10.bmp	D
W-017-01.bmp	W-039-15.bmp	D
W-030-01.bmp	W-041-24.bmp	D
W-029-01.bmp	W-027-04.bmp	D
M-004-01.bmp	M-049-06.bmp	D
M-025-01.bmp	M-001-17.bmp	D
M-041-01.bmp	M-046-21.bmp	D
W-027-01.bmp	W-004-10.bmp	D
M-030-01.bmp	M-004-21.bmp	D
M-029-01.bmp	M-035-23.bmp	D
W-043-01.bmp	W-045-15.bmp	D
W-041-01.bmp	W-047-07.bmp	D
W-043-01.bmp	W-026-16.bmp	D
M-040-01.bmp	M-007-12.bmp	D
M-012-01.bmp	M-001-12.bmp	D
M-038-01.bmp	M-044-20.bmp	D
M-029-01.bmp	M-030-04.bmp	D
M-003-01.bmp	M-045-12.bmp	D
M-003-01.bmp	M-010-04.bmp	D
W-048-01.bmp	W-022-20.bmp	D
M-037-01.bmp	M-005-08.bmp	D
M-013-01.bmp	M-038-03.bmp	D
W-036-01.bmp	W-026-07.bmp	D
W-038-01.bmp	W-007-15.bmp	D
W-047-01.bmp	W-014-17.bmp	D
W-022-01.bmp	W-038-02.bmp	D
M-027-01.bmp	M-031-09.bmp	D
M-026-01.bmp	M-021-15.bmp	D
M-031-01.bmp	M-024-18.bmp	D
M-036-01.bmp	M-042-03.bmp	D
W-007-01.bmp	W-027-22.bmp	D
W-004-01.bmp	W-041-04.bmp	D
M-005-01.bmp	M-016-22.bmp	D
W-033-01.bmp	W-044-20.bmp	D
W-004-01.bmp	W-027-19.bmp	D
M-006-01.bmp	M-043-03.bmp	D
M-025-01.bmp	M-005-11.bmp	D
W-038-01.bmp	W-041-21.bmp	D
W-005-01.bmp	W-022-06.bmp	D
M-005-01.bmp	M-039-11.bmp	D
W-025-01.bmp	W-048-03.bmp	D
M-012-01.bmp	M-033-23.bmp	D
M-009-01.bmp	M-048-11.bmp	D
M-023-01.bmp	M-007-26.bmp	D
W-041-01.bmp	W-006-25.bmp	D
W-023-01.bmp	W-008-14.bmp	D
M-011-01.bmp	M-033-21.bmp	D
W-022-01.bmp	W-011-02.bmp	D
M-023-01.bmp	M-044-22.bmp	D
M-031-01.bmp	M-001-08.bmp	D
W-015-01.bmp	W-050-21.bmp	D
W-006-01.bmp	W-039-20.bmp	D
M-031-01.bmp	M-001-17.bmp	D
W-047-01.bmp	W-002-10.bmp	D
M-041-01.bmp	M-038-08.bmp	D
M-008-01.bmp	M-010-18.bmp	D
M-020-01.bmp	M-012-19.bmp	D
M-043-01.bmp	M-007-02.bmp	D
W-035-01.bmp	W-008-25.bmp	D
W-017-01.bmp	W-002-19.bmp	D
M-037-01.bmp	M-047-23.bmp	D
M-045-01.bmp	M-013-15.bmp	D
W-021-01.bmp	W-015-11.bmp	D
W-024-01.bmp	W-001-06.bmp	D
W-035-01.bmp	W-029-17.bmp	D
W-026-01.bmp	W-024-13.bmp	D
M-009-01.bmp	M-006-10.bmp	D
W-033-01.bmp	W-050-04.bmp	D
W-032-01.bmp	W-010-26.bmp	D
W-050-01.bmp	W-043-14.bmp	D
M-020-01.bmp	M-040-15.bmp	D
M-050-01.bmp	M-023-10.bmp	D
M-034-01.bmp	M-033-17.bmp	D
W-018-01.bmp	W-033-19.bmp	D
W-036-01.bmp	W-047-12.bmp	D
W-014-01.bmp	W-019-12.bmp	D
M-048-01.bmp	M-022-21.bmp	D
M-037-01.bmp	M-026-02.bmp	D
M-023-01.bmp	M-027-10.bmp	D
M-040-01.bmp	M-020-07.bmp	D
W-001-01.bmp	W-050-04.bmp	D
M-018-01.bmp	M-045-14.bmp	D
M-005-01.bmp	M-008-18.bmp	D
M-022-01.bmp	M-045-25.bmp	D
W-046-01.bmp	W-007-18.bmp	D
M-030-01.bmp	M-027-26.bmp	D
M-048-01.bmp	M-014-18.bmp	D
M-045-01.bmp	M-025-04.bmp	D
W-043-01.bmp	W-008-24.bmp	D
M-024-01.bmp	M-022-18.bmp	D
M-050-01.bmp	M-035-26.bmp	D
M-022-01.bmp	M-003-16.bmp	D
M-046-01.bmp	M-048-22.bmp	D
W-033-01.bmp	W-017-07.bmp	D
M-012-01.bmp	M-041-09.bmp	D
M-015-01.bmp	M-008-08.bmp	D
M-044-01.bmp	M-039-05.bmp	D
W-036-01.bmp	W-050-05.bmp	D
M-038-01.bmp	M-029-24.bmp	D
W-038-01.bmp	W-050-21.bmp	D
M-021-01.bmp	M-023-04.bmp	D
W-023-01.bmp	W-011-18.bmp	D
W-039-01.bmp	W-045-17.bmp	D
W-008-01.bmp	W-042-02.bmp	D
M-025-01.bmp	M-040-08.bmp	D
W-029-01.bmp	W-045-16.bmp	D
W-018-01.bmp	W-028-20.bmp	D
W-035-01.bmp	W-048-05.bmp	D
W-003-01.bmp	W-029-17.bmp	D
M-010-01.bmp	M-049-23.bmp	D
W-013-01.bmp	W-005-22.bmp	D
W-040-01.bmp	W-032-22.bmp	D
W-043-01.bmp	W-049-24.bmp	D
M-014-01.bmp	M-028-04.bmp	D
M-005-01.bmp	M-044-04.bmp	D
W-034-01.bmp	W-014-21.bmp	D
M-032-01.bmp	M-014-07.bmp	D
M-045-01.bmp	M-015-15.bmp	D
M-025-01.bmp	M-050-10.bmp	D
W-048-01.bmp	W-047-09.bmp	D
M-017-01.bmp	M-010-16.bmp	D
M-014-01.bmp	M-024-23.bmp	D
M-042-01.bmp	M-027-22.bmp	D
M-020-01.bmp	M-042-25.bmp	D
W-025-01.bmp	W-034-12.bmp	D
M-007-01.bmp	M-039-10.bmp	D
W-037-01.bmp	W-003-22.bmp	D
W-041-01.bmp	W-001-06.bmp	D
M-050-01.bmp	M-011-24.bmp	D
W-005-01.bmp	W-045-11.bmp	D
M-030-01.bmp	M-022-24.bmp	D
M-045-01.bmp	M-034-10.bmp	D
W-007-01.bmp	W-030-07.bmp	D
M-045-01.bmp	M-020-22.bmp	D
W-041-01.bmp	W-037-15.bmp	D
M-004-01.bmp	M-005-11.bmp	D
M-049-01.bmp	M-018-22.bmp	D
M-014-01.bmp	M-024-21.bmp	D
W-043-01.bmp	W-034-17.bmp	D
W-012-01.bmp	W-049-25.bmp	D
W-047-01.bmp	W-028-14.bmp	D
W-041-01.bmp	W-018-03.bmp	D
M-027-01.bmp	M-019-12.bmp	D
W-043-01.bmp	W-009-21.bmp	D
M-001-01.bmp	M-045-19.bmp	D
W-013-01.bmp	W-044-09.bmp	D
M-012-01.bmp	M-045-06.bmp	D
M-023-01.bmp	M-029-17.bmp	D
W-046-01.bmp	W-004-17.bmp	D
M-036-01.bmp	M-018-19.bmp	D
W-029-01.bmp	W-010-20.bmp	D
M-041-01.bmp	M-038-10.bmp	D
W-028-01.bmp	W-026-26.bmp	D
W-017-01.bmp	W-016-23.bmp	D
W-017-01.bmp	W-047-18.bmp	D
M-040-01.bmp	M-050-21.bmp	D
W-008-01.bmp	W-017-20.bmp	D
W-050-01.bmp	W-049-24.bmp	D
M-027-01.bmp	M-022-24.bmp	D
M-036-01.bmp	M-050-02.bmp	D
W-011-01.bmp	W-003-24.bmp	D
W-022-01.bmp	W-019-23.bmp	D
M-005-01.bmp	M-025-16.bmp	D
W-018-01.bmp	W-010-19.bmp	D
M-047-01.bmp	M-031-18.bmp	D
M-036-01.bmp	M-047-02.bmp	D
W-003-01.bmp	W-021-12.bmp	D
M-050-01.bmp	M-013-18.bmp	D
W-012-01.bmp	W-041-25.bmp	D
M-035-01.bmp	M-041-19.bmp	D
W-048-01.bmp	W-025-22.bmp	D
M-015-01.bmp	M-039-21.bmp	D
M-034-01.bmp	M-027-02.bmp	D
W-026-01.bmp	W-008-15.bmp	D
M-036-01.bmp	M-034-08.bmp	D
W-001-01.bmp	W-044-26.bmp	D
M-036-01.bmp	M-008-10.bmp	D
W-038-01.bmp	W-019-23.bmp	D
M-035-01.bmp	M-013-15.bmp	D
M-025-01.bmp	M-027-03.bmp	D
M-044-01.bmp	M-049-12.bmp	D
W-032-01.bmp	W-050-17.bmp	D
M-037-01.bmp	M-030-22.bmp	D
M-013-01.bmp	M-001-18.bmp	D
M-018-01.bmp	M-044-03.bmp	D
M-048-01.bmp	M-030-08.bmp	D
M-031-01.bmp	M-046-20.bmp	D
M-047-01.bmp	M-022-10.bmp	D
M-044-01.bmp	M-020-26.bmp	D
W-048-01.bmp	W-042-23.bmp	D
M-019-01.bmp	M-036-14.bmp	D
W-016-01.bmp	W-023-03.bmp	D
M-034-01.bmp	M-005-25.bmp	D
W-050-01.bmp	W-042-11.bmp	D
W-014-01.bmp	W-001-03.bmp	D
W-010-01.bmp	W-009-02.bmp	D
W-011-01.bmp	W-006-17.bmp	D
M-025-01.bmp	M-035-25.bmp	D
M-025-01.bmp	M-044-24.bmp	D
W-002-01.bmp	W-031-02.bmp	D
M-049-01.bmp	M-026-26.bmp	D
M-028-01.bmp	M-035-10.bmp	D
M-036-01.bmp	M-008-05.bmp	D
W-036-01.bmp	W-016-12.bmp	D
W-041-01.bmp	W-045-09.bmp	D
W-012-01.bmp	W-042-04.bmp	D
W-001-01.bmp	W-015-23.bmp	D
W-050-01.bmp	W-031-17.bmp	D
M-042-01.bmp	M-031-23.bmp	D
M-006-01.bmp	M-043-05.bmp	D
W-020-01.bmp	W-040-09.bmp	D
W-027-01.bmp	W-050-09.bmp	D
M-027-01.bmp	M-020-11.bmp	D
M-007-01.bmp	M-041-17.bmp	D
M-014-01.bmp	M-043-13.bmp	D
W-047-01.bmp	W-042-05.bmp	D
M-001-01.bmp	M-014-17.bmp	D
W-014-01.bmp	W-037-04.bmp	D
W-025-01.bmp	W-007-17.bmp	D
W-006-01.bmp	W-001-18.bmp	D
M-036-01.bmp	M-003-03.bmp	D
W-027-01.bmp	W-006-07.bmp	D
W-033-01.bmp	W-050-13.bmp	D
W-041-01.bmp	W-018-06.bmp	D
W-021-01.bmp	W-031-09.bmp	D
M-035-01.bmp	M-015-25.bmp	D
W-035-01.bmp	W-049-05.bmp	D
W-005-01.bmp	W-022-15.bmp	D
W-048-01.bmp	W-009-21.bmp	D
M-010-01.bmp	M-008-19.bmp	D
W-033-01.bmp	W-032-22.bmp	D
M-020-01.bmp	M-032-10.bmp	D
M-002-01.bmp	M-010-07.bmp	D
M-017-01.bmp	M-016-05.bmp	D
M-012-01.bmp	M-049-14.bmp	D
W-048-01.bmp	W-032-10.bmp	D
W-050-01.bmp	W-006-20.bmp	D
M-028-01.bmp	M-003-18.bmp	D
M-003-01.bmp	M-017-06.bmp	D
W-048-01.bmp	W-003-13.bmp	D
W-018-01.bmp	W-024-24.bmp	D
W-034-01.bmp	W-036-19.bmp	D
M-011-01.bmp	M-032-08.bmp	D
W-009-01.bmp	W-010-08.bmp	D
W-002-01.bmp	W-014-24.bmp	D
W-025-01.bmp	W-016-07.bmp	D
M-025-01.bmp	M-009-10.bmp	D
W-038-01.bmp	W-047-10.bmp	D
W-031-01.bmp	W-009-14.bmp	D
M-020-01.bmp	M-003-19.bmp	D
W-013-01.bmp	W-025-13.bmp	D
M-023-01.bmp	M-027-21.bmp	D
M-034-01.bmp	M-050-24.bmp	D
M-032-01.bmp	M-036-08.bmp	D
M-003-01.bmp	M-048-17.bmp	D
W-014-01.bmp	W-048-15.bmp	D
W-030-01.bmp	W-004-14.bmp	D
W-001-01.bmp	W-024-23.bmp	D
W-019-01.bmp	W-027-20.bmp	D
W-049-01.bmp	W-017-10.bmp	D
M-044-01.bmp	M-002-07.bmp	D
M-041-01.bmp	M-047-16.bmp	D
W-027-01.bmp	W-001-11.bmp	D
M-004-01.bmp	M-027-09.bmp	D
M-042-01.bmp	M-020-17.bmp	D
M-017-01.bmp	M-046-17.bmp	D
M-018-01.bmp	M-045-25.bmp	D
W-046-01.bmp	W-020-10.bmp	D
W-033-01.bmp	W-009-19.bmp	D
W-019-01.bmp	W-001-19.bmp	D
M-028-01.bmp	M-041-12.bmp	D
W-045-01.bmp	W-035-25.bmp	D
W-030-01.bmp	W-026-10.bmp	D
W-025-01.bmp	W-042-18.bmp	D
M-010-01.bmp	M-022-25.bmp	D
W-040-01.bmp	W-050-22.bmp	D
W-025-01.bmp	W-005-10.bmp	D
M-007-01.bmp	M-011-08.bmp	D
W-005-01.bmp	W-032-06.bmp	D
W-015-01.bmp	W-018-24.bmp	D
M-030-01.bmp	M-029-04.bmp	D
M-008-01.bmp	M-002-03.bmp	D
M-030-01.bmp	M-049-09.bmp	D
M-037-01.bmp	M-021-13.bmp	D
M-026-01.bmp	M-031-07.bmp	D
M-017-01.bmp	M-025-04.bmp	D
M-047-01.bmp	M-016-04.bmp	D
W-005-01.bmp	W-025-11.bmp	D
W-046-01.bmp	W-026-17.bmp	D
W-044-01.bmp	W-043-26.bmp	D
W-048-01.bmp	W-022-12.bmp	D
M-024-01.bmp	M-004-07.bmp	D
W-029-01.bmp	W-030-25.bmp	D
W-032-01.bmp	W-021-10.bmp	D
M-035-01.bmp	M-041-10.bmp	D
M-028-01.bmp	M-013-14.bmp	D
W-035-01.bmp	W-048-05.bmp	D
M-018-01.bmp	M-023-07.bmp	D
W-012-01.bmp	W-042-09.bmp	D
M-033-01.bmp	M-038-03.bmp	D
W-010-01.bmp	W-028-08.bmp	D
W-050-01.bmp	W-022-10.bmp	D
W-006-01.bmp	W-043-04.bmp	D
M-044-01.bmp	M-028-05.bmp	D
W-031-01.bmp	W-016-16.bmp	D
M-045-01.bmp	M-044-08.bmp	D
W-010-01.bmp	W-012-10.bmp	D
W-021-01.bmp	W-048-16.bmp	D
M-035-01.bmp	M-036-05.bmp	D
M-039-01.bmp	M-009-05.bmp	D
W-050-01.bmp	W-048-14.bmp	D
W-044-01.bmp	W-047-15.bmp	D
W-040-01.bmp	W-006-08.bmp	D
W-019-01.bmp	W-020-04.bmp	D
M-019-01.bmp	M-046-06.bmp	D
M-002-01.bmp	M-016-22.bmp	D
M-040-01.bmp	M-002-02.bmp	D
W-037-01.bmp	W-047-19.bmp	D
W-013-01.bmp	W-006-02.bmp	D
M-029-01.bmp	M-004-02.bmp	D
W-042-01.bmp	W-012-21.bmp	D
M-036-01.bmp	M-024-17.bmp	D
M-029-01.bmp	M-011-11.bmp	D
M-012-01.bmp	M-048-24.bmp	D
M-022-01.bmp	M-033-09.bmp	D
W-034-01.bmp	W-049-19.bmp	D
W-023-01.bmp	W-027-13.bmp	D
M-039-01.bmp	M-020-19.bmp	D
M-004-01.bmp	M-018-23.bmp	D
W-035-01.bmp	W-020-11.bmp	D
W-048-01.bmp	W-029-18.bmp	D
M-047-01.bmp	M-023-07.bmp	D
W-001-01.bmp	W-026-14.bmp	D
M-032-01.bmp	M-050-12.bmp	D
M-006-01.bmp	M-003-24.bmp	D
M-036-01.bmp	M-042-25.bmp	D
M-033-01.bmp	M-039-21.bmp	D
M-008-01.bmp	M-040-02.bmp	D
M-026-01.bmp	M-011-10.bmp	D
W-037-01.bmp	W-001-09.bmp	D
M-034-01.bmp	M-025-16.bmp	D
W-024-01.bmp	W-033-12.bmp	D
M-026-01.bmp	M-046-16.bmp	D
W-043-01.bmp	W-004-10.bmp	D
M-032-01.bmp	M-023-24.bmp	D
M-033-01.bmp	M-045-11.bmp	D
W-021-01.bmp	W-002-07.bmp	D
W-036-01.bmp	W-012-22.bmp	D
M-020-01.bmp	M-048-12.bmp	D
M-039-01.bmp	M-044-10.bmp	D
W-016-01.bmp	W-022-16.bmp	D
W-047-01.bmp	W-010-11.bmp	D
M-040-01.bmp	M-029-22.bmp	D
M-026-01.bmp	M-037-24.bmp	D
W-040-01.bmp	W-023-21.bmp	D
M-025-01.bmp	M-037-06.bmp	D
M-031-01.bmp	M-027-09.bmp	D
M-003-01.bmp	M-018-07.bmp	D
W-022-01.bmp	W-048-12.bmp	D
M-039-01.bmp	M-011-22.bmp	D
W-020-01.bmp	W-019-23.bmp	D
W-033-01.bmp	W-002-21.bmp	D
M-022-01.bmp	M-018-25.bmp	D
M-016-01.bmp	M-020-17.bmp	D
W-046-01.bmp	W-022-09.bmp	D
M-034-01.bmp	M-044-11.bmp	D
W-011-01.bmp	W-001-07.bmp	D
W-039-01.bmp	W-032-08.bmp	D
W-024-01.bmp	W-022-08.bmp	D
M-019-01.bmp	M-042-03.bmp	D
M-040-01.bmp	M-003-18.bmp	D
M-035-01.bmp	M-004-23.bmp	D
W-042-01.bmp	W-004-20.bmp	D
M-032-01.bmp	M-037-04.bmp	D
W-042-01.bmp	W-008-11.bmp	D
W-019-01.bmp	W-037-07.bmp	D
M-044-01.bmp	M-037-10.bmp	D
M-037-01.bmp	M-011-16.bmp	D
M-006-01.bmp	M-042-23.bmp	D
W-015-01.bmp	W-025-06.bmp	D
W-031-01.bmp	W-025-04.bmp	D
W-020-01.bmp	W-008-21.bmp	D
W-004-01.bmp	W-041-19.bmp	D
W-013-01.bmp	W-027-09.bmp	D
W-009-01.bmp	W-048-16.bmp	D
W-047-01.bmp	W-015-10.bmp	D
M-032-01.bmp	M-024-24.bmp	D
W-033-01.bmp	W-008-03.bmp	D
M-042-01.bmp	M-043-18.bmp	D
M-021-01.bmp	M-041-04.bmp	D
M-036-01.bmp	M-046-16.bmp	D
W-044-01.bmp	W-003-04.bmp	D
M-037-01.bmp	M-020-11.bmp	D
M-013-01.bmp	M-034-19.bmp	D
M-046-01.bmp	M-045-04.bmp	D
W-029-01.bmp	W-009-08.bmp	D
W-044-01.bmp	W-020-21.bmp	D
M-022-01.bmp	M-039-26.bmp	D
M-014-01.bmp	M-035-06.bmp	D
M-032-01.bmp	M-001-17.bmp	D
W-047-01.bmp	W-046-15.bmp	D
M-049-01.bmp	M-026-06.bmp	D
M-046-01.bmp	M-025-22.bmp	D
W-031-01.bmp	W-037-26.bmp	D
W-010-01.bmp	W-027-14.bmp	D
M-005-01.bmp	M-032-06.bmp	D
W-025-01.bmp	W-023-04.bmp	D
W-025-01.bmp	W-043-17.bmp	D
W-032-01.bmp	W-026-11.bmp	D
M-002-01.bmp	M-021-17.bmp	D
M-042-01.bmp	M-027-20.bmp	D
W-024-01.bmp	W-003-10.bmp	D
M-044-01.bmp	M-018-06.bmp	D
M-019-01.bmp	M-020-02.bmp	D
W-029-01.bmp	W-021-03.bmp	D
M-014-01.bmp	M-022-08.bmp	D
W-028-01.bmp	W-005-24.bmp	D
W-008-01.bmp	W-041-24.bmp	D
W-035-01.bmp	W-001-16.bmp	D
M-048-01.bmp	M-021-18.bmp	D
W-022-01.bmp	W-014-04.bmp	D
M-049-01.bmp	M-039-03.bmp	D
W-040-01.bmp	W-039-25.bmp	D
W-036-01.bmp	W-026-17.bmp	D
M-017-01.bmp	M-020-05.bmp	D
M-001-01.bmp	M-004-18.bmp	D
M-048-01.bmp	M-037-02.bmp	D
W-046-01.bmp	W-006-07.bmp	D
W-006-01.bmp	W-008-15.bmp	D
M-046-01.bmp	M-042-06.bmp	D
M-039-01.bmp	M-015-05.bmp	D
M-048-01.bmp	M-007-16.bmp	D
W-024-01.bmp	W-047-23.bmp	D
M-047-01.bmp	M-027-11.bmp	D
W-040-01.bmp	W-046-24.bmp	D
W-029-01.bmp	W-042-22.bmp	D
W-011-01.bmp	W-005-03.bmp	D
M-006-01.bmp	M-037-13.bmp	D
W-036-01.bmp	W-014-26.bmp	D
W-027-01.bmp	W-003-24.bmp	D
W-026-01.bmp	W-046-04.bmp	D
M-016-01.bmp	M-006-03.bmp	D
W-030-01.bmp	W-001-07.bmp	D
W-028-01.bmp	W-042-05.bmp	D
M-035-01.bmp	M-022-11.bmp	D
W-006-01.bmp	W-018-02.bmp	D
W-004-01.bmp	W-029-03.bmp	D
M-015-01.bmp	M-014-25.bmp	D
W-041-01.bmp	W-031-06.bmp	D
M-043-01.bmp	M-018-12.bmp	D
W-044-01.bmp	W-033-15.bmp	D
W-035-01.bmp	W-001-09.bmp	D
M-026-01.bmp	M-015-13.bmp	D
W-032-01.bmp	W-040-21.bmp	D
M-008-01.bmp	M-012-22.bmp	D
W-022-01.bmp	W-048-10.bmp	D
W-029-01.bmp	W-034-11.bmp	D
M-031-01.bmp	M-046-10.bmp	D
W-031-01.bmp	W-040-23.bmp	D
M-039-01.bmp	M-044-04.bmp	D
W-038-01.bmp	W-010-06.bmp	D
M-028-01.bmp	M-027-09.bmp	D
W-048-01.bmp	W-044-05.bmp	D
W-004-01.bmp	W-023-12.bmp	D
W-002-01.bmp	W-007-15.bmp	D
M-036-01.bmp	M-034-05.bmp	D
M-015-01.bmp	M-017-15.bmp	D
W-026-01.bmp	W-014-26.bmp	D
M-027-01.bmp	M-005-02.bmp	D
W-026-01.bmp	W-031-09.bmp	D
M-008-01.bmp	M-046-12.bmp	D
M-002-01.bmp	M-040-12.bmp	D
M-039-01.bmp	M-036-04.bmp	D
M-040-01.bmp	M-032-20.bmp	D
W-038-01.bmp	W-041-12.bmp	D
W-016-01.bmp	W-024-18.bmp	D
W-015-01.bmp	W-026-24.bmp	D
M-024-01.bmp	M-026-08.bmp	D
W-041-01.bmp	W-004-11.bmp	D
M-042-01.bmp	M-046-17.bmp	D
M-014-01.bmp	M-037-02.bmp	D
W-033-01.bmp	W-048-12.bmp	D
W-016-01.bmp	W-047-25.bmp	D
W-033-01.bmp	W-005-12.bmp	D
M-026-01.bmp	M-022-13.bmp	D
W-048-01.bmp	W-017-23.bmp	D
M-020-01.bmp	M-046-17.bmp	D
W-034-01.bmp	W-029-22.bmp	D
W-002-01.bmp	W-047-23.bmp	D
W-027-01.bmp	W-009-24.bmp	D
W-013-01.bmp	W-022-06.bmp	D
W-006-01.bmp	W-048-21.bmp	D
M-007-01.bmp	M-018-07.bmp	D
M-026-01.bmp	M-013-12.bmp	D
M-016-01.bmp	M-006-09.bmp	D
W-024-01.bmp	W-013-10.bmp	D
M-021-01.bmp	M-006-06.bmp	D
M-049-01.bmp	M-041-24.bmp	D
M-016-01.bmp	M-017-07.bmp	D
M-044-01.bmp	M-028-15.bmp	D
M-004-01.bmp	M-047-10.bmp	D
W-040-01.bmp	W-033-12.bmp	D
W-015-01.bmp	W-010-11.bmp	D
W-047-01.bmp	W-023-20.bmp	D
M-036-01.bmp	M-041-14.bmp	D
W-045-01.bmp	W-010-23.bmp	D
M-026-01.bmp	M-036-22.bmp	D
W-006-01.bmp	W-027-11.bmp	D
M-048-01.bmp	M-015-04.bmp	D
M-002-01.bmp	M-026-05.bmp	D
W-014-01.bmp	W-029-23.bmp	D
M-005-01.bmp	M-007-02.bmp	D
M-027-01.bmp	M-035-05.bmp	D
M-002-01.bmp	M-008-20.bmp	D
M-013-01.bmp	M-007-11.bmp	D
W-009-01.bmp	W-029-02.bmp	D
M-006-01.bmp	M-021-08.bmp	D
M-045-01.bmp	M-008-14.bmp	D
W-046-01.bmp	W-050-11.bmp	D
M-038-01.bmp	M-044-07.bmp	D
W-005-01.bmp	W-048-11.bmp	D
M-031-01.bmp	M-041-23.bmp	D
W-004-01.bmp	W-045-12.bmp	D
W-039-01.bmp	W-030-10.bmp	D
M-038-01.bmp	M-002-08.bmp	D
W-039-01.bmp	W-027-05.bmp	D
M-026-01.bmp	M-028-23.bmp	D
W-024-01.bmp	W-016-04.bmp	D
W-050-01.bmp	W-018-20.bmp	D
W-044-01.bmp	W-018-05.bmp	D
W-050-01.bmp	W-035-12.bmp	D
M-033-01.bmp	M-021-17.bmp	D
W-011-01.bmp	W-016-22.bmp	D
W-006-01.bmp	W-026-09.bmp	D
W-038-01.bmp	W-033-21.bmp	D
M-026-01.bmp	M-018-20.bmp	D
M-003-01.bmp	M-016-03.bmp	D
W-032-01.bmp	W-047-08.bmp	D
W-026-01.bmp	W-047-07.bmp	D
W-011-01.bmp	W-033-23.bmp	D
M-049-01.bmp	M-028-22.bmp	D
M-042-01.bmp	M-015-08.bmp	D
M-037-01.bmp	M-048-09.bmp	D
W-010-01.bmp	W-015-05.bmp	D
M-046-01.bmp	M-020-26.bmp	D
M-040-01.bmp	M-041-11.bmp	D
M-006-01.bmp	M-025-11.bmp	D
M-037-01.bmp	M-013-08.bmp	D
W-022-01.bmp	W-032-22.bmp	D
W-041-01.bmp	W-026-03.bmp	D
W-023-01.bmp	W-034-05.bmp	D
W-015-01.bmp	W-009-07.bmp	D
W-019-01.bmp	W-037-21.bmp	D
W-011-01.bmp	W-025-17.bmp	D
M-034-01.bmp	M-003-14.bmp	D
M-037-01.bmp	M-041-12.bmp	D
W-045-01.bmp	W-003-19.bmp	D
M-028-01.bmp	M-026-14.bmp	D
M-036-01.bmp	M-045-22.bmp	D
W-004-01.bmp	W-014-10.bmp	D
M-037-01.bmp	M-010-05.bmp	D
M-017-01.bmp	M-027-23.bmp	D
W-028-01.bmp	W-027-19.bmp	D
W-025-01.bmp	W-014-13.bmp	D
W-043-01.bmp	W-044-05.bmp	D
M-030-01.bmp	M-006-07.bmp	D
M-050-01.bmp	M-022-13.bmp	D
M-030-01.bmp	M-038-15.bmp	D
W-042-01.bmp	W-022-07.bmp	D
W-022-01.bmp	W-018-23.bmp	D
M-004-01.bmp	M-024-22.bmp	D
M-010-01.bmp	M-038-07.bmp	D
W-021-01.bmp	W-036-24.bmp	D
M-006-01.bmp	M-022-03.bmp	D
M-019-01.bmp	M-023-07.bmp	D
W-009-01.bmp	W-050-25.bmp	D
W-033-01.bmp	W-004-10.bmp	D
W-032-01.bmp	W-014-20.bmp	D
W-018-01.bmp	W-040-04.bmp	D
W-047-01.bmp	W-049-21.bmp	D
W-032-01.bmp	W-030-17.bmp	D
W-012-01.bmp	W-037-24.bmp	D
M-027-01.bmp	M-013-25.bmp	D
M-029-01.bmp	M-017-11.bmp	D
W-012-01.bmp	W-046-14.bmp	D
M-040-01.bmp	M-014-12.bmp	D
M-004-01.bmp	M-050-05.bmp	D
M-018-01.bmp	M-044-05.bmp	D
W-048-01.bmp	W-019-13.bmp	D
M-044-01.bmp	M-026-07.bmp	D
M-043-01.bmp	M-007-23.bmp	D
M-032-01.bmp	M-024-06.bmp	D
W-019-01.bmp	W-004-17.bmp	D
M-025-01.bmp	M-018-23.bmp	D
M-029-01.bmp	M-026-16.bmp	D
M-025-01.bmp	M-002-02.bmp	D
W-023-01.bmp	W-021-19.bmp	D
M-036-01.bmp	M-009-22.bmp	D
M-009-01.bmp	M-018-03.bmp	D
M-003-01.bmp	M-017-20.bmp	D
W-012-01.bmp	W-005-03.bmp	D
M-027-01.bmp	M-023-08.bmp	D
W-047-01.bmp	W-009-13.bmp	D
W-037-01.bmp	W-023-22.bmp	D
M-027-01.bmp	M-048-16.bmp	D
W-007-01.bmp	W-040-19.bmp	D
M-043-01.bmp	M-018-03.bmp	D
M-011-01.bmp	M-025-05.bmp	D
M-025-01.bmp	M-003-20.bmp	D
W-045-01.bmp	W-028-10.bmp	D
M-020-01.bmp	M-028-12.bmp	D
W-020-01.bmp	W-040-20.bmp	D
W-027-01.bmp	W-037-12.bmp	D
W-013-01.bmp	W-034-18.bmp	D
W-009-01.bmp	W-003-17.bmp	D
M-034-01.bmp	M-040-18.bmp	D
W-008-01.bmp	W-028-02.bmp	D
W-006-01.bmp	W-004-18.bmp	D
M-050-01.bmp	M-016-18.bmp	D
M-014-01.bmp	M-005-18.bmp	D
W-022-01.bmp	W-043-19.bmp	D
M-038-01.bmp	M-006-17.bmp	D
W-039-01.bmp	W-048-08.bmp	D
W-002-01.bmp	W-018-24.bmp	D
M-024-01.bmp	M-012-20.bmp	D
W-009-01.bmp	W-008-13.bmp	D
M-044-01.bmp	M-027-24.bmp	D
M-031-01.bmp	M-037-17.bmp	D
W-013-01.bmp	W-006-13.bmp	D
M-015-01.bmp	M-026-05.bmp	D
M-019-01.bmp	M-042-04.bmp	D
M-049-01.bmp	M-014-17.bmp	D
M-012-01.bmp	M-046-19.bmp	D
W-047-01.bmp	W-008-14.bmp	D
W-023-01.bmp	W-045-04.bmp	D
M-040-01.bmp	M-006-02.bmp	D
W-036-01.bmp	W-004-12.bmp	D
M-003-01.bmp	M-042-12.bmp	D
M-021-01.bmp	M-034-05.bmp	D
W-006-01.bmp	W-033-18.bmp	D
W-009-01.bmp	W-002-19.bmp	D
M-040-01.bmp	M-007-24.bmp	D
M-007-01.bmp	M-048-26.bmp	D
W-043-01.bmp	W-025-13.bmp	D
W-009-01.bmp	W-029-20.bmp	D
M-019-01.bmp	M-007-16.bmp	D
W-034-01.bmp	W-004-10.bmp	D
W-038-01.bmp	W-016-10.bmp	D
W-026-01.bmp	W-030-11.bmp	D
W-010-01.bmp	W-043-05.bmp	D
W-010-01.bmp	W-021-20.bmp	D
M-049-01.bmp	M-030-18.bmp	D
M-016-01.bmp	M-002-19.bmp	D
M-033-01.bmp	M-049-06.bmp	D
M-030-01.bmp	M-006-25.bmp	D
W-037-01.bmp	W-018-17.bmp	D
M-034-01.bmp	M-030-10.bmp	D
M-010-01.bmp	M-047-20.bmp	D
W-037-01.bmp	W-006-09.bmp	D
W-001-01.bmp	W-050-04.bmp	D
W-011-01.bmp	W-028-23.bmp	D
M-041-01.bmp	M-001-02.bmp	D
W-034-01.bmp	W-042-05.bmp	D
W-045-01.bmp	W-035-12.bmp	D
M-017-01.bmp	M-008-02.bmp	D
W-039-01.bmp	W-037-22.bmp	D
W-005-01.bmp	W-008-02.bmp	D
M-010-01.bmp	M-003-23.bmp	D
M-008-01.bmp	M-007-07.bmp	D
W-009-01.bmp	W-045-04.bmp	D
W-027-01.bmp	W-034-15.bmp	D
W-035-01.bmp	W-043-07.bmp	D
W-023-01.bmp	W-037-03.bmp	D
W-021-01.bmp	W-009-07.bmp	D
M-001-01.bmp	M-045-04.bmp	D
M-018-01.bmp	M-025-02.bmp	D
W-033-01.bmp	W-012-09.bmp	D
W-013-01.bmp	W-018-15.bmp	D
W-020-01.bmp	W-048-12.bmp	D
M-045-01.bmp	M-001-06.bmp	D
M-015-01.bmp	M-013-12.bmp	D
M-031-01.bmp	M-002-11.bmp	D
M-032-01.bmp	M-037-18.bmp	D
W-009-01.bmp	W-002-10.bmp	D
W-050-01.bmp	W-028-25.bmp	D
W-050-01.bmp	W-019-24.bmp	D
W-018-01.bmp	W-009-24.bmp	D
W-034-01.bmp	W-010-16.bmp	D
W-041-01.bmp	W-018-23.bmp	D
M-026-01.bmp	M-029-20.bmp	D
M-011-01.bmp	M-026-23.bmp	D
W-019-01.bmp	W-011-07.bmp	D
M-023-01.bmp	M-030-14.bmp	D
W-018-01.bmp	W-010-06.bmp	D
W-014-01.bmp	W-012-15.bmp	D
M-012-01.bmp	M-027-14.bmp	D
W-009-01.bmp	W-024-19.bmp	D
W-029-01.bmp	W-026-05.bmp	D
M-041-01.bmp	M-007-09.bmp	D
W-035-01.bmp	W-004-22.bmp	D
W-048-01.bmp	W-045-19.bmp	D
W-040-01.bmp	W-003-17.bmp	D
M-027-01.bmp	M-039-02.bmp	D
M-024-01.bmp	M-032-05.bmp	D
W-048-01.bmp	W-039-23.bmp	D
W-045-01.bmp	W-016-12.bmp	D
M-035-01.bmp	M-041-17.bmp	D
W-005-01.bmp	W-013-08.bmp	D
W-022-01.bmp	W-002-25.bmp	D
W-039-01.bmp	W-035-17.bmp	D
M-044-01.bmp	M-032-20.bmp	D
W-048-01.bmp	W-038-06.bmp	D
W-049-01.bmp	W-044-22.bmp	D
W-021-01.bmp	W-047-19.bmp	D
W-044-01.bmp	W-030-13.bmp	D
W-043-01.bmp	W-018-12.bmp	D
M-006-01.bmp	M-044-03.bmp	D
W-016-01.bmp	W-024-15.bmp	D
M-016-01.bmp	M-036-02.bmp	D
W-048-01.bmp	W-036-04.bmp	D
W-041-01.bmp	W-017-10.bmp	D
M-042-01.bmp	M-028-21.bmp	D
W-006-01.bmp	W-018-26.bmp	D
W-025-01.bmp	W-050-21.bmp	D
W-021-01.bmp	W-042-14.bmp	D
W-041-01.bmp	W-029-18.bmp	D
M-040-01.bmp	M-018-23.bmp	D
W-007-01.bmp	W-037-16.bmp	D
M-038-01.bmp	M-047-14.bmp	D
W-050-01.bmp	W-047-15.bmp	D
M-046-01.bmp	M-027-05.bmp	D
W-025-01.bmp	W-030-06.bmp	D
W-008-01.bmp	W-023-10.bmp	D
M-026-01.bmp	M-045-08.bmp	D
W-029-01.bmp	W-020-23.bmp	D
W-049-01.bmp	W-044-22.bmp	D
W-040-01.bmp	W-031-22.bmp	D
W-026-01.bmp	W-002-22.bmp	D
W-008-01.bmp	W-030-05.bmp	D
M-046-01.bmp	M-033-10.bmp	D
M-048-01.bmp	M-001-11.bmp	D
W-039-01.bmp	W-024-14.bmp	D
W-031-01.bmp	W-027-13.bmp	D
W-042-01.bmp	W-016-02.bmp	D
W-008-01.bmp	W-046-11.bmp	D
W-046-01.bmp	W-014-19.bmp	D
W-001-01.bmp	W-017-10.bmp	D
M-042-01.bmp	M-037-04.bmp	D
W-033-01.bmp	W-041-07.bmp	D
M-038-01.bmp	M-043-25.bmp	D
M-032-01.bmp	M-050-06.bmp	D
W-031-01.bmp	W-041-19.bmp	D
W-044-01.bmp	W-043-08.bmp	D
W-046-01.bmp	W-027-10.bmp	D
W-011-01.bmp	W-003-11.bmp	D
M-043-01.bmp	M-012-10.bmp	D
M-006-01.bmp	M-019-26.bmp	D
W-034-01.bmp	W-030-17.bmp	D
W-042-01.bmp	W-013-24.bmp	D
M-024-01.bmp	M-010-10.bmp	D
W-028-01.bmp	W-010-23.bmp	D
M-003-01.bmp	M-030-19.bmp	D
W-003-01.bmp	W-020-15.bmp	D
M-010-01.bmp	M-033-04.bmp	D
W-003-01.bmp	W-038-04.bmp	D
M-038-01.bmp	M-031-26.bmp	D
W-011-01.bmp	W-031-24.bmp	D
W-023-01.bmp	W-021-04.bmp	D
M-007-01.bmp	M-026-21.bmp	D
M-048-01.bmp	M-019-03.bmp	D
M-032-01.bmp	M-001-18.bmp	D
W-003-01.bmp	W-029-16.bmp	D
M-047-01.bmp	M-020-24.bmp	D
W-034-01.bmp	W-031-21.bmp	D
W-026-01.bmp	W-024-06.bmp	D
W-003-01.bmp	W-027-22.bmp	D
W-018-01.bmp	W-043-26.bmp	D
W-047-01.bmp	W-008-26.bmp	D
W-030-01.bmp	W-039-25.bmp	D
W-047-01.bmp	W-002-09.bmp	D
W-030-01.bmp	W-013-07.bmp	D
M-040-01.bmp	M-042-05.bmp	D
W-029-01.bmp	W-037-21.bmp	D
M-047-01.bmp	M-009-25.bmp	D
M-043-01.bmp	M-001-23.bmp	D
W-025-01.bmp	W-012-03.bmp	D
W-010-01.bmp	W-044-17.bmp	D
M-045-01.bmp	M-013-04.bmp	D
M-006-01.bmp	M-014-24.bmp	D
W-042-01.bmp	W-009-17.bmp	D
M-026-01.bmp	M-003-04.bmp	D
M-048-01.bmp	M-030-04.bmp	D
W-045-01.bmp	W-019-15.bmp	D
W-019-01.bmp	W-031-11.bmp	D
M-032-01.bmp	M-039-05.bmp	D
M-020-01.bmp	M-045-21.bmp	D
M-033-01.bmp	M-050-23.bmp	D
W-009-01.bmp	W-028-16.bmp	D
W-009-01.bmp	W-022-14.bmp	D
M-019-01.bmp	M-039-19.bmp	D
W-041-01.bmp	W-038-06.bmp	D
W-016-01.bmp	W-050-02.bmp	D
M-041-01.bmp	M-040-11.bmp	D
M-023-01.bmp	M-036-07.bmp	D
W-046-01.bmp	W-002-10.bmp	D
M-033-01.bmp	M-048-08.bmp	D
W-025-01.bmp	W-008-14.bmp	D
W-021-01.bmp	W-046-05.bmp	D
W-046-01.bmp	W-040-24.bmp	D
M-038-01.bmp	M-019-17.bmp	D
W-034-01.bmp	W-044-16.bmp	D
W-026-01.bmp	W-036-05.bmp	D
M-050-01.bmp	M-048-05.bmp	D
M-045-01.bmp	M-020-23.bmp	D
W-048-01.bmp	W-001-06.bmp	D
M-020-01.bmp	M-048-12.bmp	D
M-015-01.bmp	M-024-26.bmp	D
M-013-01.bmp	M-041-14.bmp	D
W-020-01.bmp	W-045-20.bmp	D
M-005-01.bmp	M-048-11.bmp	D
M-041-01.bmp	M-031-05.bmp	D
W-019-01.bmp	W-045-03.bmp	D
W-024-01.bmp	W-019-19.bmp	D
M-030-01.bmp	M-045-26.bmp	D
W-018-01.bmp	W-022-21.bmp	D
M-010-01.bmp	M-025-21.bmp	D
M-013-01.bmp	M-035-10.bmp	D
M-048-01.bmp	M-022-25.bmp	D
M-039-01.bmp	M-041-20.bmp	D
W-004-01.bmp	W-008-18.bmp	D
W-035-01.bmp	W-044-15.bmp	D
M-031-01.bmp	M-022-15.bmp	D
M-038-01.bmp	M-004-05.bmp	D
M-018-01.bmp	M-029-06.bmp	D
W-010-01.bmp	W-029-08.bmp	D
M-020-01.bmp	M-030-17.bmp	D
M-004-01.bmp	M-035-17.bmp	D
M-026-01.bmp	M-002-12.bmp	D
M-014-01.bmp	M-037-04.bmp	D
M-013-01.bmp	M-041-09.bmp	D
M-025-01.bmp	M-003-06.bmp	D
M-039-01.bmp	M-001-11.bmp	D
W-015-01.bmp	W-049-16.bmp	D
M-026-01.bmp	M-048-07.bmp	D
W-042-01.bmp	W-004-12.bmp	D
M-015-01.bmp	M-034-25.bmp	D
W-042-01.bmp	W-001-09.bmp	D
M-047-01.bmp	M-042-18.bmp	D
W-020-01.bmp	W-002-20.bmp	D
W-038-01.bmp	W-020-23.bmp	D
W-017-01.bmp	W-042-17.bmp	D
W-044-01.bmp	W-004-08.bmp	D
M-047-01.bmp	M-043-15.bmp	D
M-042-01.bmp	M-033-25.bmp	D
W-025-01.bmp	W-036-20.bmp	D
W-047-01.bmp	W-031-17.bmp	D
M-026-01.bmp	M-042-11.bmp	D
M-034-01.bmp	M-041-15.bmp	D
M-025-01.bmp	M-033-12.bmp	D
W-048-01.bmp	W-008-14.bmp	D
M-047-01.bmp	M-042-05.bmp	D
W-004-01.bmp	W-001-14.bmp	D
M-014-01.bmp	M-015-18.bmp	D
M-046-01.bmp	M-048-21.bmp	D
M-011-01.bmp	M-028-16.bmp	D
W-028-01.bmp	W-048-25.bmp	D
W-035-01.bmp	W-016-10.bmp	D
W-023-01.bmp	W-025-11.bmp	D
M-001-01.bmp	M-041-08.bmp	D
W-038-01.bmp	W-032-14.bmp	D
W-003-01.bmp	W-008-19.bmp	D
W-016-01.bmp	W-048-26.bmp	D
M-050-01.bmp	M-011-09.bmp	D
W-024-01.bmp	W-026-02.bmp	D
W-017-01.bmp	W-045-21.bmp	D
W-038-01.bmp	W-049-04.bmp	D
W-034-01.bmp	W-029-13.bmp	D
M-047-01.bmp	M-016-26.bmp	D
M-028-01.bmp	M-009-24.bmp	D
W-049-01.bmp	W-023-14.bmp	D
M-004-01.bmp	M-030-08.bmp	D
W-049-01.bmp	W-016-06.bmp	D
M-017-01.bmp	M-001-19.bmp	D
W-038-01.bmp	W-018-09.bmp	D
M-041-01.bmp	M-045-22.bmp	D
W-042-01.bmp	W-047-10.bmp	D
M-020-01.bmp	M-024-04.bmp	D
W-008-01.bmp	W-002-07.bmp	D
W-039-01.bmp	W-050-23.bmp	D
W-031-01.bmp	W-039-12.bmp	D
M-007-01.bmp	M-038-20.bmp	D
M-038-01.bmp	M-035-03.bmp	D
W-042-01.bmp	W-041-20.bmp	D
W-035-01.bmp	W-033-06.bmp	D
W-033-01.bmp	W-008-15.bmp	D
M-003-01.bmp	M-027-07.bmp	D
W-027-01.bmp	W-021-24.bmp	D
W-016-01.bmp	W-039-20.bmp	D
M-019-01.bmp	M-045-02.bmp	D
W-016-01.bmp	W-012-19.bmp	D
W-031-01.bmp	W-006-14.bmp	D
M-013-01.bmp	M-024-03.bmp	D
M-036-01.bmp	M-033-16.bmp	D
M-049-01.bmp	M-020-22.bmp	D
W-019-01.bmp	W-013-18.bmp	D
W-041-01.bmp	W-048-22.bmp	D
W-048-01.bmp	W-025-25.bmp	D
M-029-01.bmp	M-044-07.bmp	D
M-015-01.bmp	M-007-15.bmp	D
W-001-01.bmp	W-020-22.bmp	D
M-038-01.bmp	M-044-06.bmp	D
M-023-01.bmp	M-037-08.bmp	D


================================================
FILE: TestCases/verification_text_files/ARFace/validation_test_gen.py
================================================
import numpy as np
import pandas as pd

filename = 'validation.txt'
suffix = 'bmp'

def CreateName(sex, personID, imageID):
    name = sex + '-' + '%03d'%personID + '-' + '%02d'%imageID
    return name + '.' + suffix

def GenPos():
    list_first = []
    list_second = []
    for idx_sex in ['M','W']:
        for idx_person in range(1, 51):
            for idx_img in range(2, 27):
                name_first = CreateName(idx_sex, idx_person, 1)
                name_second = CreateName(idx_sex, idx_person, idx_img)
                list_first.append(name_first)
                list_second.append(name_second)
    df = pd.DataFrame([])
    df['img1'] = pd.Series(list_first)
    df['img2'] = pd.Series(list_second)
    df['class'] = 'S'
    return df
    
def GenNeg():
    list_first = []
    list_second = []
    np.random.seed(231)
    for _ in range(2500):
        sex = 'M' if np.random.randint(low=0, high=2, size=1)[0]==0 else 'W'
        person_a = np.random.randint(low=1, high=51, size=1)[0]
        while True:
            person_b = np.random.randint(low=1, high=51, size=1)[0]
            if person_a != person_b:
                break
            
        img = np.random.randint(low=2, high=27, size=1)[0]
        name_first = CreateName(sex, person_a, 1)
        name_second = CreateName(sex, person_b, img)
        list_first.append(name_first)
        list_second.append(name_second)
        assert person_a>=1 and person_a<=50
        assert person_b>=1 and person_b<=50
        assert person_a!=person_b
        assert img>=2 and img<=26

    df = pd.DataFrame([])
    df['img1'] = pd.Series(list_first)
    df['img2'] = pd.Series(list_second)
    df['class'] = 'D'
    return df

if __name__=='__main__':
    df1 = GenPos()
    df2 = GenNeg()
    df = pd.concat([df1, df2], ignore_index=True)
    df.to_csv(filename, sep='\t', index=False, header=True)

    
                


================================================
FILE: TestCases/verification_text_files/LFW/pairsDevTest.txt
================================================
Abdullah_Gul	13	14
Abdullah_Gul	13	16
Abdullatif_Sener	1	2
Adel_Al-Jubeir	1	3
Al_Pacino	1	2
Alan_Greenspan	1	5
Albert_Costa	2	6
Albert_Costa	4	6
Albert_Costa	5	6
Alejandro_Atchugarry	1	2
Alex_Penelas	1	2
Ali_Naimi	1	3
Ali_Naimi	3	4
Allison_Janney	1	2
Allyson_Felix	2	5
Alvaro_Uribe	7	10
Alvaro_Uribe	17	26
Alvaro_Uribe	28	29
Amanda_Bynes	1	2
Amanda_Bynes	1	3
Amanda_Bynes	1	4
Amanda_Bynes	3	4
Amelie_Mauresmo	1	21
Amelie_Mauresmo	4	11
Amelie_Mauresmo	16	21
Ana_Palacio	1	6
Andrei_Mikhnevich	1	2
Andy_Hebb	1	2
Angelo_Reyes	1	2
Angelo_Reyes	2	3
Ann_Veneman	1	2
Ann_Veneman	5	11
Ann_Veneman	8	9
Anna_Nicole_Smith	1	2
Anne_Krueger	1	2
Anne_Krueger	2	3
Annette_Lu	1	2
Annette_Lu	1	3
Annette_Lu	2	3
Antonio_Palocci	3	8
Antonio_Trillanes	1	2
Antonio_Trillanes	2	3
Arlen_Specter	1	3
Augustin_Calleri	1	3
Augustin_Calleri	1	4
Barbara_Brezigar	1	2
Begum_Khaleda_Zia	1	2
Ben_Affleck	1	3
Ben_Affleck	2	6
Ben_Affleck	3	6
Bertie_Ahern	2	3
Bill_Frist	1	3
Bill_Frist	2	7
Bill_Frist	3	8
Bill_McBride	2	6
Bill_McBride	2	10
Bill_McBride	3	9
Bill_Sizemore	1	2
Bono	1	2
Bono	1	3
Bono	2	3
Brian_Cowen	1	2
Bridget_Fonda	1	3
Bridgette_Wilson-Sampras	1	2
Butch_Davis	1	2
Calista_Flockhart	2	6
Candice_Bergen	1	3
Carla_Del_Ponte	2	4
Carla_Del_Ponte	4	5
Carlos_Manuel_Pruneda	1	2
Carlos_Manuel_Pruneda	1	3
Carlos_Manuel_Pruneda	2	3
Carlos_Moya	7	11
Carlos_Ortega	1	3
Carolyn_Dawn_Johnson	2	3
Carrie-Anne_Moss	2	5
Carson_Daly	1	2
Cathy_Freeman	1	2
Chanda_Rubin	2	4
Chang_Dae-whan	1	2
Charles_Taylor	3	9
Chen_Shui-bian	3	5
Chita_Rivera	1	2
Chok_Tong_Goh	1	2
Chris_Bell	1	2
Chris_Byrd	1	2
Christian_Longo	1	3
Christian_Longo	2	3
Christian_Wulff	1	2
Christine_Ebersole	1	2
Christine_Todd_Whitman	5	6
Christopher_Reeve	1	4
Claire_Leger	1	2
Condoleezza_Rice	2	5
Condoleezza_Rice	7	10
Cristina_Fernandez	1	2
Dai_Bachtiar	1	2
Daisy_Fuentes	3	4
Dave_Campo	1	2
Dave_Campo	2	3
David_Stern	1	4
David_Stern	3	4
Denise_Johnson	1	2
Dennis_Powell	1	2
Denzel_Washington	1	3
Denzel_Washington	2	4
Denzel_Washington	2	5
Derek_Jeter	2	3
Diane_Green	1	2
Dick_Clark	1	2
Dick_Clark	1	3
Dick_Clark	2	3
Dick_Vermeil	1	2
Dominique_de_Villepin	3	5
Dominique_de_Villepin	7	11
Dominique_de_Villepin	14	15
Donald_Pettit	1	2
Donald_Pettit	2	3
Donald_Rumsfeld	22	36
Donald_Rumsfeld	28	108
Donald_Rumsfeld	41	48
Doug_Collins	1	2
Edward_Lu	2	4
Edward_Norton	1	2
Edwin_Edwards	1	2
Edwin_Edwards	2	3
Eliane_Karp	1	4
Eliane_Karp	2	3
Elin_Nordegren	1	2
Elinor_Caplan	1	2
Elisabeth_Schumacher	1	2
Elizabeth_Smart	1	5
Elizabeth_Smart	3	4
Elsa_Zylberstein	1	2
Elsa_Zylberstein	1	5
Elsa_Zylberstein	3	6
Emma_Watson	1	4
Emma_Watson	2	3
Emma_Watson	3	5
Erik_Morales	1	3
Erika_Christensen	1	2
Erin_Runnion	3	4
Ernie_Fletcher	1	2
Fabiola_Zuluaga	1	2
Felipe_Perez_Roque	1	4
Felipe_Perez_Roque	2	4
Fernando_Vargas	2	4
Flor_Montulo	1	2
Frank_Cassell	1	2
Frank_Dunham_Jr	1	2
Gao_Qiang	1	2
Garry_Trudeau	1	2
Gary_Doer	1	2
Gary_Doer	1	3
Gary_Doer	2	3
Gary_Winnick	1	2
Gene_Robinson	2	4
George_Foreman	1	2
George_Karl	1	2
George_Robertson	5	20
George_Robertson	12	19
George_Robertson	15	22
Georgi_Parvanov	1	2
Geraldine_Chaplin	1	3
Gerhard_Schroeder	3	26
Gerry_Adams	3	7
Gerry_Adams	5	8
Gilberto_Rodriguez_Orejuela	1	3
Gilberto_Rodriguez_Orejuela	2	4
Gilberto_Rodriguez_Orejuela	3	4
Giuseppe_Gibilisco	2	4
Giuseppe_Gibilisco	3	4
Glafcos_Clerides	1	4
Gordon_Brown	4	11
Gordon_Campbell	1	2
Gray_Davis	6	23
Gray_Davis	13	23
Greg_Gilbert	1	2
Greg_Ostertag	1	2
Gregory_Hines	1	2
Gus_Van_Sant	1	2
Gwendal_Peizerat	1	2
Gwyneth_Paltrow	4	5
Harry_Kalas	1	2
Hassan_Wirajuda	1	2
Heather_Mills	3	4
Heidi_Fleiss	1	3
Heidi_Fleiss	1	4
Hermann_Maier	1	2
Horst_Koehler	1	3
Ian_Thorpe	2	7
Ian_Thorpe	3	10
Ian_Thorpe	6	8
Isabella_Rossellini	1	2
Isabelle_Huppert	1	2
Ismail_Merchant	1	2
Jack_Grubman	1	2
Jack_Nicholson	2	3
Jacques_Chirac	22	44
Jacques_Chirac	30	33
Jacques_Chirac	31	52
Jacques_Rogge	4	6
Jake_Gyllenhaal	2	4
Jake_Gyllenhaal	3	4
James_Butts	1	2
James_Franco	1	2
James_Kelly	4	11
James_Kelly	9	11
James_Kopp	1	3
James_Kopp	2	3
James_Maguire	1	2
James_Smith	1	2
Jan_Ullrich	2	3
Jan_Ullrich	2	5
Janica_Kostelic	1	2
Javier_Weber	1	2
Javier_Weber	1	3
Jean-Claude_Juncker	1	2
Jean-Claude_Trichet	1	2
Jean-Marc_de_La_Sabliere	1	2
Jean-Pierre_Raffarin	2	6
Jean_Carnahan	1	2
Jefferson_Perez	1	2
Jennifer_Capriati	3	13
Jennifer_Capriati	24	29
Jennifer_Connelly	1	4
Jennifer_Connelly	3	4
Jennifer_Keller	2	4
Jennifer_Keller	3	4
Jeong_Se-hyun	4	5
Jeremy_Shockey	1	2
Jesse_Ventura	1	3
Jessica_Lange	1	2
Jiang_Zemin	2	17
Jiang_Zemin	12	15
Jim_Harrick	1	2
Jimmy_Carter	1	9
Jimmy_Carter	4	8
Jimmy_Carter	8	9
Joe_Mantello	1	2
Joe_Nichols	1	3
Joe_Nichols	3	4
John_Bolton	3	10
John_Bolton	4	14
John_Bolton	5	13
John_Bolton	11	14
John_Garamendi	1	2
John_McCallum	1	2
John_Negroponte	4	17
John_Rowland	1	2
John_Stallworth	1	2
John_Travolta	4	5
John_Walsh	1	2
Johnny_Carson	1	2
Jorge_Castaneda	1	2
Jose_Dirceu	1	2
Joseph_Deiss	1	2
Judi_Dench	1	2
Julie_Gerberding	7	12
Julie_Gerberding	8	12
Justin_Leonard	1	3
Justine_Henin	1	3
Justine_Henin	2	3
Kamal_Kharrazi	3	5
Keith_Bogans	2	3
Kenneth_Evans	1	2
Kim_Yong-il	1	2
King_Abdullah_II	1	2
King_Abdullah_II	1	3
King_Abdullah_II	1	4
King_Abdullah_II	2	3
Kjell_Magne_Bondevik	1	2
Kosuke_Kitajima	1	2
Kristen_Breitweiser	1	2
Kristin_Davis	1	2
Kristin_Davis	2	3
Kurt_Warner	1	5
LK_Advani	1	2
LK_Advani	1	3
LK_Advani	2	3
Larry_Coker	2	4
Latrell_Sprewell	1	2
Laura_Linney	1	3
Lauren_Killian	1	2
Laurent_Jalabert	1	2
Leonardo_DiCaprio	1	8
Leonardo_DiCaprio	3	7
Leonid_Kuchma	1	6
Leonid_Kuchma	2	3
Leonid_Kuchma	2	4
Leonid_Kuchma	4	6
Leslie_Moonves	1	2
Leszek_Miller	2	3
Lino_Oviedo	1	2
Lisa_Raymond	1	2
Liza_Minnelli	1	3
Lloyd_Ward	1	2
Luciano_Pavarotti	1	3
Lucy_Liu	2	4
Luis_Figo	1	2
Luis_Horna	1	3
Luis_Horna	2	5
Lynn_Abraham	1	2
Mack_Brown	1	2
Mahmoud_Abbas	19	26
Marcelo_Rios	1	4
Marcelo_Rios	2	4
Marcelo_Rios	4	5
Marieta_Chrousala	1	2
Marieta_Chrousala	1	3
Mario_Cipollini	1	2
Mark_Dacey	1	2
Mark_Richt	1	3
Mark_Richt	2	3
Martha_Burk	2	4
Martha_Stewart	1	2
Martha_Stewart	2	5
Martha_Stewart	3	5
Martin_Cauchon	1	2
Martin_Sheen	1	2
Mary_Landrieu	1	3
Masum_Turker	1	2
Masum_Turker	1	3
Matt_Doherty	1	2
Matt_Doherty	1	3
Matthew_Broderick	1	4
Matthew_Broderick	2	3
Matthew_Broderick	3	4
Melissa_Etheridge	1	2
Michael_Jackson	2	8
Michael_Phelps	1	3
Michael_Sullivan	1	2
Michel_Duclos	1	2
Michelle_Yeoh	3	4
Miguel_Contreras	1	2
Mike_Price	1	2
Mikhail_Youzhny	1	2
Mikhail_Youzhny	1	3
Mikhail_Youzhny	2	3
Mikulas_Dzurinda	1	2
Mireya_Moscoso	1	3
Mireya_Moscoso	2	3
Mohamed_ElBaradei	3	6
Mohamed_ElBaradei	4	5
Mohamed_ElBaradei	5	8
Monica_Lewinsky	2	3
Muhammad_Ali	4	7
Muhammad_Ali	6	9
Nancy_Pelosi	2	5
Nancy_Pelosi	6	13
Nancy_Pelosi	13	14
Naomi_Campbell	1	2
Naoto_Kan	2	3
Nasser_al-Kidwa	1	2
Nastassia_Kinski	1	2
Natalie_Coughlin	1	2
Natalie_Coughlin	3	5
Natalie_Maines	2	4
Nicanor_Duarte_Frutos	8	10
Noah_Wyle	1	2
Norm_Coleman	2	7
Orrin_Hatch	1	2
Osama_bin_Laden	2	4
Owen_Wilson	1	2
Ozzy_Osbourne	1	2
Ozzy_Osbourne	2	3
Padraig_Harrington	1	3
Paris_Hilton	1	2
Patrick_Leahy	1	2
Patti_Labelle	1	2
Patti_Labelle	2	3
Patty_Schnyder	1	3
Patty_Schnyder	1	4
Paul-Henri_Mathieu	1	2
Paul_Burrell	4	10
Paul_Burrell	5	11
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Paul_Martin	2	4
Paul_Martin	3	6
Paul_Patton	1	2
Paul_Sarbanes	2	3
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Pedro_Malan	1	4
Pedro_Malan	2	3
Penelope_Cruz	1	2
Peter_Greenaway	1	2
Pierce_Brosnan	4	12
Pierce_Brosnan	7	8
Pierre_Boulanger	1	2
Priscilla_Presley	1	2
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Rachel_Hunter	2	3
Ralf_Schumacher	1	6
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Rebecca_Romijn-Stamos	3	4
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Reese_Witherspoon	1	4
Ricardo_Maduro	1	2
Rich_Gannon	1	2
Richard_Gere	1	10
Richard_Gere	6	10
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Richard_Shelby	1	2
Richie_Adubato	1	2
Rick_Dinse	1	3
Rick_Perry	1	2
Rick_Perry	2	6
Rick_Pitino	1	2
Rick_Romley	1	2
Rick_Wagoner	1	2
Rob_Schneider	1	2
Robbie_Fowler	1	2
Robby_Ginepri	1	2
Robert_Horan	1	2
Robert_Mueller	1	3
Robert_Redford	2	3
Robert_Redford	2	5
Robert_Redford	4	7
Robert_Redford	7	8
Rod_Blagojevich	1	2
Rod_Stewart	1	3
Ronaldo_Luis_Nazario_de_Lima	1	4
Roy_Moore	2	3
Rupert_Grint	2	3
Russell_Coutts	1	2
Russell_Crowe	1	2
Salma_Hayek	1	7
Salma_Hayek	8	10
Sarah_Jessica_Parker	5	6
Scott_McNealy	1	2
Sean_Astin	1	2
Sean_OKeefe	4	5
Sean_Patrick_OMalley	1	2
Sean_Patrick_OMalley	1	3
Sean_Patrick_OMalley	2	3
Sean_Penn	2	3
Sergey_Lavrov	1	10
Shane_Mosley	1	2
Shannon_OBrien	1	2
Sheila_Wellstone	1	2
Silvio_Berlusconi	14	23
Spencer_Abraham	12	13
Stan_Heath	1	2
Stefano_Accorsi	1	2
Steve_Lavin	1	4
Steven_Hatfill	1	2
Surakait_Sathirathai	1	2
Susan_Collins	1	2
Susie_Castillo	1	2
Svetlana_Koroleva	1	2
Tammy_Lynn_Michaels	1	2
Tang_Jiaxuan	1	6
Tang_Jiaxuan	1	9
Tang_Jiaxuan	1	10
Tang_Jiaxuan	1	11
Tassos_Papadopoulos	1	2
Terry_McAuliffe	1	2
Terry_McAuliffe	1	3
Thabo_Mbeki	4	5
Thaksin_Shinawatra	1	6
Thaksin_Shinawatra	3	6
Theodore_Tweed_Roosevelt	2	3
Thomas_OBrien	8	9
Tim_Allen	1	2
Tim_Allen	2	4
Tim_Curry	1	2
Tippi_Hedren	1	2
Todd_Haynes	1	3
Todd_Haynes	1	4
Tom_Coverdale	1	2
Tom_Cruise	1	7
Tom_Cruise	2	4
Tom_Cruise	4	9
Tommy_Haas	2	3
Tomoko_Hagiwara	1	2
Tony_Shalhoub	1	3
Tony_Shalhoub	1	4
Tracee_Ellis_Ross	1	2
Tyler_Hamilton	1	2
Vaclav_Havel	1	6
Vaclav_Havel	1	9
Vicente_Fernandez	2	5
Vicente_Fernandez	4	5
Victoria_Beckham	2	3
Vincent_Brooks	1	2
Vincent_Brooks	2	6
Warren_Beatty	1	2
Warren_Buffett	1	3
Wesley_Clark	1	2
Will_Smith	1	2
William_Burns	1	2
William_Macy	1	4
William_Macy	2	3
William_Macy	3	5
William_Rehnquist	1	2
Winona_Ryder	6	15
Winona_Ryder	19	21
Yevgeny_Kafelnikov	3	4
Yoriko_Kawaguchi	3	10
Zoran_Djindjic	3	4
AJ_Lamas	1	Zach_Safrin	1
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Abdullah_Gul	16	Steve_Cox	1
Abid_Hamid_Mahmud_Al-Tikriti	1	Eli_Broad	1
Adam_Kennedy	1	Amelie_Mauresmo	19
Adel_Al-Jubeir	1	Elisabeth_Welch	1
Adrian_Murrell	1	Tommy_Franks	15
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Alex_Corretja	1	Tippi_Hedren	2
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Ali_Fallahian	1	Mohammed_Abulhasan	1
Ali_Naimi	8	Vanessa_Laine	1
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Allison_Searing	1	Phillip_Fulmer	1
Allison_Searing	1	Warren_Beatty	1
Amanda_Marsh	1	Howard_Smith	2
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Amelie_Mauresmo	6	Terri_Clark	1
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Amporn_Falise	1	Liza_Minnelli	2
Amporn_Falise	1	Zhang_Yimou	1
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Ana_Palacio	5	Erika_Christensen	2
Ana_Palacio	6	Robert_Gordon_Card	1
Andrew_Caldecott	1	Joe_Strummer	1
Andrew_Shutley	1	Charles_Taylor	7
Andrew_Wetzler	1	Cristina_Torrens_Valero	1
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Ann_Godbehere	1	Paul_Newman	1
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Arthur_Johnson	1	Steve_Pagliuca	1
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Augustin_Calleri	4	Brad_Miller	1
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Bill_Frist	4	Donald_Pettit	2
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Bono	2	Se_Hyuk_Joo	1
Brad_Miller	1	Chris_Noth	1
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Buddy_Ryan	1	Roy_Romanow	1
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Candice_Bergen	2	Jake_Gyllenhaal	2
Candice_Bergen	2	Prospero_Pichay	1
Carey_Lowell	1	Helio_Castroneves	1
Carey_Lowell	1	Joshua_Harapko	1
Carlo_Ancelotti	1	Hugh_Miller	1
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Carlos_Ghosn	1	Renee_Zellweger	11
Carlos_Iturgaitz	1	Francisco_Maturana	1
Carlos_Manuel_Pruneda	1	Claudia_Coslovich	1
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Carson_Daly	1	Matthew_During	1
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Chen_Shui-bian	2	Simon_Cowell	1
Chen_Shui-bian	2	William_Nessen	1
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Chris_Andrews	1	Elinor_Caplan	2
Chris_Byrd	1	David_Alpay	1
Chris_Byrd	1	Lawrence_Di_Rita	1
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Coleen_Rowley	1	Courtney_Love	1
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Courtney_Love	1	Tsutomu_Takebe	1
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Dan_Ackroyd	1	Nikki_Teasley	1
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Dan_Bylsma	1	Scott_Yates	1
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Daniel_Montgomery	1	Hassan_Wirajuda	1
Daniel_Zelman	1	David_Surrett	1
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Darvis_Patton	1	Gordon_Lightfoot	1
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Dave_Johnson	1	Hank_Aaron	1
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David_Surrett	1	Oracene_Williams	1
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Denise_van_Outen	1	Kevin_Satterfield	1
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Derrick_Battie	1	Lisa_Leslie	1
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Dick_Armey	1	Tom_Glavine	2
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Don_Carcieri	1	Jane_Rooney	1
Don_King	1	Philip_Zalewski	1
Don_King	1	Tab_Baldwin	1
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Donald_Rumsfeld	40	Tamika_Catchings	1
Donna_Walker	1	Phil_Bredesen	1
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Eric_Snow	1	Robert_McKee	1
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Farouk_Kaddoumi	1	Will_Smith	2
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Filip_De_Winter	1	Sue_Grafton	1
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Flor_Montulo	1	Steve_Blankenship	1
Floyd_Mayweather	1	Lou_Lang	1
Fran_Drescher	2	William_Martin	1
Francis_Ricciardone	1	Gene_Sauers	1
Franco_Frattini	1	Gholamreza_Aghazadeh	1
Frank_Sinatra	1	Vicente_Fox	23
Frank_Van_Ecke	1	Gary_Gero	1
Fred_Durst	1	Patricia_Phillips	1
Fred_Durst	1	Rose_Linkins	1
Fred_Durst	1	Tara_Reid	1
Frederick_Madden	1	Luis_Ernesto_Derbez_Bautista	3
Gary_Leon_Ridgway	1	Lisa_Raymond	1
Gary_Leon_Ridgway	1	Phillip_Seymor_Hoffmann	1
Gary_Sayler	1	Nila_Ferran	1
George_Foreman	1	George_Lucas	1
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Gerard_Tronche	1	Jana_Pittman	1
Gerhard_Schroeder	3	Izzat_Ibrahim	1
Ghassan_Elashi	1	Jesse_Ventura	2
Ghassan_Elashi	1	Peter_Rasch	1
Gideon_Yago	1	Robert_Gordon_Card	1
Gina_Gershon	1	Stacey_Dales-Schuman	1
Glenn_Tilton	1	Victor_Hanescu	1
Gordon_Brown	12	Monica_Gabrielle	1
Gordon_Campbell	1	Pierre_Boulanger	2
Gordon_Lightfoot	1	Janez_Drnovsek	1
Grace_Kelly	1	Leslie_Moonves	1
Greg_Kinnear	1	Tim_Salmon	1
Gregory_Geoffroy	2	Paul_Burrell	11
Gregory_Hines	1	Mary_Frances_Seiter	1
Gregory_Peck	1	John_Lawrence	1
Gregory_Peck	1	John_Lynch	1
Guillaume_Cannet	1	Mark_Mulder	1
Guillaume_Cannet	1	Mohammad_Khatami	5
Gunilla_Backman	1	Jennifer_Granholm	1
Gunilla_Backman	1	Ray_Sherman	1
Gustavo_Franco	1	Melissa_Joan_Hart	1
Gwendal_Peizerat	2	Joe_Nichols	2
Gwyneth_Paltrow	5	Mike_Richter	1
Halbert_Fillinger	1	Rachel_Hunter	1
Hank_Aaron	1	Ron_Howard	2
Harland_Braun	1	Lisa_Leslie	1
Harvey_Fierstein	1	Mike_Slive	1
Helene_Eksterowicz	1	Mario_Lemieux	1
Helio_Castroneves	1	Joxel_Garcia	1
Hermann_Maier	1	Robin_Williams	1
Howard_Smith	2	Tim_Pawlenty	1
Hubie_Brown	1	Yoon_Jeong_Cho	1
Hunter_Bates	1	James_Williams	1
Hussam_Mohammed_Amin	1	Mike_Smith	1
Hussam_Mohammed_Amin	1	Princess_Hisako	1
Hutomo_Mandala_Putra	1	Thomas_Mesereau_Jr	1
Iban_Mayo	2	Yves_Brodeur	1
Imad_Moustapha	1	Will_Ofenheusle	1
Ion_Tiriac	1	Lawrence_Roberts	1
Irina_Yatchenko	1	Pedro_Solbes	4
Isabelle_Huppert	1	Pedro_Solbes	1
Isaiah_Washington	2	Lee_Baca	1
Islam_Karimov	1	Shireen_Amir_Begum	1
Ismail_Cem	1	Seth_Gorney	1
Ismail_Merchant	1	Joseph_Deiss	1
Ivan_Lee	1	Paul-Henri_Mathieu	3
Izzat_Ibrahim	1	Tina_Sinatra	1
Jack_Welch	1	Rick_Dinse	2
Jack_Welch	1	William_Umbach	1
Jalal_Talabani	1	Jean-Marc_Olive	1
James_Franco	2	Lokendra_Bahadur_Chand	1
James_Ivory	1	Paul_Martin	7
James_Lockhart	1	Lisa_Girman	1
Jan_Paul_Miller	1	Lynne_Slepian	1
Jan_Ullrich	1	William_Rehnquist	1
Janet_Chandler	1	Zoe_Ball	1
Janis_Ruth_Coulter	1	Laurent_Woulzy	1
Jason_Clermont	1	Vladimir_Ustinov	1
Jason_Kapono	1	Patricia_Medina	1
Jason_Mewes	1	Will_Smith	1
Jason_White	1	Wolfgang_Clement	1
Jean-Pierre_Raffarin	2	Robert_Horan	2
Jean-Pierre_Raffarin	6	Paul_Kariya	1
Jeane_Kirkpatrick	1	Richard_Carl	1
Jeane_Kirkpatrick	1	Tamika_Catchings	1
Jeanne_Anne_Schroeder	1	Yoriko_Kawaguchi	13
Jeannette_Biedermann	1	Roy_Moore	6
Jeffrey_Pfeffer	1	Terry_Lynn_Barton	1
Jen_Bice	1	Lily_Tomlin	2
Jen_Bice	1	Martha_Burk	2
Jenna_Elfman	1	Mack_Brown	1
Jenna_Elfman	1	Steffi_Graf	5
Jenna_Elfman	1	Willie_Wilson	1
Jennifer_Keller	4	Paula_Abdul	1
Jennifer_Thompson	1	Serge_Melac	1
Jeremy_Greenstock	7	Jim_Flaherty	1
Jerry_Bruckheimer	1	John_Blaney	1
Jerry_Jones	1	Robert_Woody_Johnson	1
Jesse_Ventura	1	Reggie_Lewis	1
Jesse_Ventura	3	Roy_Romanow	1
Jessica_Biel	1	Jim_Freudenberg	1
Jim_Calhoun	1	Perry_Farrell	1
Jim_Cantalupo	1	Joe_Pantoliano	1
Jim_Hahn	4	Vaclav_Havel	3
Jim_Hahn	4	Vicente_Fernandez	2
Jim_Letten	1	Victor_Hanescu	1
Joaquin_Phoenix	1	Kajsa_Bergqvist	1
Joe_Pantoliano	1	Robin_Tunney	1
John_Belushi	1	Mahima_Chaudhari	1
John_Blaney	2	Sam_Brownback	1
John_Franco	1	Teri_Files	1
John_Garamendi	2	Peter_Goldmark	1
John_Kerr	1	Susan_Whelan	1
John_Lynch	1	Stefano_Gabbana	1
John_Mayer	3	Miguel_Jimenez	1
John_McCallum	1	Mark_Andrew	1
John_Rowland	2	Robert_Lee_Yates_Jr	1
John_Walsh	2	Paul_Hogan	2
Johnny_Depp	2	Scott_Dickson	1
Jorge_Arce	1	Samuel_Waksal	3
Jorge_Quiroga	1	Ramona_Rispton	1
Jorge_Quiroga	1	Surakait_Sathirathai	1
Jose_Bove	1	Michalis_Chrisohoides	1
Jose_Bove	1	Princess_Diana	1
Jose_Luis_Chilavert	1	Sofyan_Dawood	1
Juan_Carlos	1	Patricia_Phillips	1
Judy_Dean	1	Kristanna_Loken	1
Julia_Ormond	1	Randy_Dryer	1
Julio_Cesar_Chavez	1	Marc_Racicot	1
Kaoru_Hasuike	1	Tom_Foy	1
Karen_Allen	1	LeRoy_Millette_Jr	1
Karen_Allen	1	Rick_Bragg	1
Karl-Heinz_Rummenigge	1	Wayne_Newton	1
Katie_Boone	1	Terri_Clark	1
Keith_Osik	1	Robert_Nardelli	1
Kent_Robinson	1	Marquier_Montano_Contreras	1
Kevin_Gil	1	Mary_Bono	1
Kevin_Hearn	1	Todd_Haynes	3
Khader_Rashid_Rahim	1	Martha_Burk	1
Khader_Rashid_Rahim	1	Michael_Arif	1
Kim_Yong-il	2	Terri_Clark	1
Koichi_Tanaka	1	Sterling_Hitchcock	1
Kosuke_Kitajima	2	Qazi_Hussain_Ahmed	1
Kristin_Davis	3	Steven_Van_Zandt	1
Kurt_Hellstrom	1	Manuel_Pellegrini	1
Laszlo_Kovacs	1	Michael_Arif	1
Laura_Elena_Harring	1	Rowan_Williams	1
Laurel_Clark	1	Rahul_Dravid	1
Lawrence_Di_Rita	1	Tim_Allen	2
Lawrence_Roberts	1	Malik_Mahmud	1
Lea_Fastow	1	Todd_Parrott	1
Lee_Baca	1	Pat_Summerall	1
Leisel_Jones	1	Steven_Hatfill	1
Lena_Katina	1	Queen_Noor	1
Leonard_Glick	1	Terrence_Trammell	1
Leonard_Schrank	1	Ozzy_Osbourne	1
Leslie_Wiser_Jr	1	Mireya_Moscoso	1
Lisa_Murkowski	1	Svetlana_Belousova	1
Lisa_Raymond	2	Robert_Redford	7
Ludwig_Ovalle	1	Mauricio_Macri	1
Luis_Pujols	1	Rohman_al-Ghozi	1
Makhdoom_Amin_Fahim	1	Tang_Jiaxuan	5
Malcolm_Wild	1	Owen_Wilson	2
Mamdouh_Habib	1	Polona_Bas	1
Manijeh_Hekmat	1	Richard_Carl	1
Manijeh_Hekmat	1	Se_Hyuk_Joo	1
Marc_Anthony	1	Vince_Vaughan	1
Margie_Puente	1	Rafiq_Hariri	1
Maria_Callas	1	Melchor_Cob_Castro	1
Mario_Lemieux	1	Pedro_Solbes	4
Marissa_Jaret_Winokur	1	Vincent_Sombrotto	1
Mark_Dacey	2	Russ_Ortiz	1
Mark_Martin	1	Vladimir_Spidla	2
Mark_Mishkin	1	Nick_Reilly	1
Mark_Mishkin	1	Shawn_Marion	1
Marricia_Tate	1	Rita_Moreno	2
Mary_Landrieu	1	Robert_Gordon_Card	1
Maryn_McKenna	1	Shawn_Marion	1
Maryn_McKenna	1	Tim_Pawlenty	1
Masum_Turker	1	Norman_Mineta	1
Matt_Dillon	1	Regina_Ip	1
Matthias_Sammer	1	Robbie_Naish	1
Melissa_Etheridge	2	Teri_Files	1
Michael_J_Sheehan	1	Michael_Smith_Foster	1
Michael_Linscott	1	Robin_Tunney	1
Michael_Phelps	5	Pat_Burns	2
Michael_Sheehan	1	Vincent_Cianci_Jr	1
Michael_Smith_Foster	1	Rupert_Murdoch	1
Michelle_Yeoh	5	Shoshannah_Stern	1
Miguel_Aldana_Ibarra	1	Mikhail_Gorbachev	1
Miguel_Jimenez	1	Paris_Hilton	1
Mike_Helton	2	Reggie_Lewis	1
Mike_Leach	1	Thomas_Haeggstroem	1
Mike_Maroth	1	Stefan_Holm	1
Mike_Slive	1	Paul_Sarbanes	3
Mikhail_Youzhny	2	Vince_Dooley	1
Mikulas_Dzurinda	2	Shirley_Jones	1
Miles_Stewart	1	Yasushi_Akashi	1
Mirela_Manjani	1	Robert_Woody_Johnson	1
Mitchell_McLaughlin	1	Timothy_Goebel	1
Mohammed_Baqir_al-Hakim	3	Neil_Goldman	1
Mona_Ayoub	1	Todd_Parrott	1
Mufti_Mohammad_Syed	1	Ralf_Schumacher	4
Nathalie_Gagnon	1	Rupert_Grint	2
Neil_Goldman	1	Niall_Connolly	1
Nick_Reilly	1	Tassos_Papadopoulos	1
Nicolas_Sarkozy	1	Shanna_Zolman	1
Norm_Coleman	2	Osmond_Smith	1
Norman_Mailer	1	Steven_Curtis_Chapman	1
Oliver_Neuville	1	Shawn_Marion	1
Park_Jie-won	1	Steve_Patterson	1
Patty_Sheehan	1	William_Nessen	1
Paul_Hogan	1	Thomas_Watjen	1
Paul_Hogan	1	William_Martin	1
Paul_Kariya	1	Shannon_OBrien	2
Paul_Martin	1	Stephanie_Cohen_Aloro	1
Paul_Michael_Daniels	1	Simon_Chalk	1
Paul_Schrader	1	Teri_Files	1
Paula_Prentiss	1	Thomas_Mesereau_Jr	1
Pedro_Martinez	1	Stephen_Glassroth	1
Peter_Fitzgerald	1	Zelma_Novelo	1
Phil_Jackson	1	Richard_Penniman	1
Phillipe_Comtois	1	Richard_Carl	1
Pierre_Boulanger	1	Shania_Twain	1
Princess_Diana	1	Steffi_Graf	2
Priscilla_Presley	1	Sergey_Lavrov	5
Priscilla_Presley	1	Victoria_Beckham	3
Richard_Butler	1	Victoria_Beckham	1
Richard_Pennington	1	Stacy_Nelson	1
Rick_Caruso	1	Steve_Wariner	1
Rick_Perry	6	Svetlana_Koroleva	1
Ricky_Cottrill	1	Sananda_Maitreya	1
Robert_Flodquist	1	Winona_Ryder	11
Rod_Stewart	1	Tom_Scully	1
Rod_Stewart	3	Se_Hyuk_Joo	1
Rod_Thorn	1	Yves_Brodeur	1
Ron_Howard	1	Tim_Pawlenty	1
Ronaldo_Luis_Nazario_de_Lima	1	Samuel_Waksal	2
Sami_Al-Arian	1	Tommy_Lasorda	1
Sarah_Canale	1	Steven_Curtis_Chapman	1
Sasha_Cohen	1	Valery_Giscard_dEstaing	5
Scott_Dalton	1	Tamara_Mowry	1
Sergio_Castellitto	1	Steve_Lavin	5
Seth_Gorney	1	Wilton_Gregory	1
Shane_Mosley	1	Stacey_Dales-Schuman	1
Sheila_Taormina	1	Stephan_Eberharter	1
Stefano_Gabbana	1	Tang_Jiaxuan	3
Steve_Wariner	1	Toshi_Izawa	1
Steve_Zahn	1	Tab_Baldwin	1
Susan_Whelan	1	Wolfgang_Schneiderhan	1
Takeo_Fukui	1	Will_Ofenheusle	1
Tamara_Mowry	1	Zach_Parise	1
Tatiana_Kennedy_Schlossberg	1	Thomas_Watjen	1
Todd_Petit	1	Vicente_Fernandez	3

================================================
FILE: TestCases/verification_text_files/LFW/validation.txt
================================================
img1	img2	class
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Abdullah_Gul\Abdullah_Gul_0013.jpg	Abdullah_Gul\Abdullah_Gul_0016.jpg	S
Abdullatif_Sener\Abdullatif_Sener_0001.jpg	Abdullatif_Sener\Abdullatif_Sener_0002.jpg	S
Adel_Al-Jubeir\Adel_Al-Jubeir_0001.jpg	Adel_Al-Jubeir\Adel_Al-Jubeir_0003.jpg	S
Al_Pacino\Al_Pacino_0001.jpg	Al_Pacino\Al_Pacino_0002.jpg	S
Alan_Greenspan\Alan_Greenspan_0001.jpg	Alan_Greenspan\Alan_Greenspan_0005.jpg	S
Albert_Costa\Albert_Costa_0002.jpg	Albert_Costa\Albert_Costa_0006.jpg	S
Albert_Costa\Albert_Costa_0004.jpg	Albert_Costa\Albert_Costa_0006.jpg	S
Albert_Costa\Albert_Costa_0005.jpg	Albert_Costa\Albert_Costa_0006.jpg	S
Alejandro_Atchugarry\Alejandro_Atchugarry_0001.jpg	Alejandro_Atchugarry\Alejandro_Atchugarry_0002.jpg	S
Alex_Penelas\Alex_Penelas_0001.jpg	Alex_Penelas\Alex_Penelas_0002.jpg	S
Ali_Naimi\Ali_Naimi_0001.jpg	Ali_Naimi\Ali_Naimi_0003.jpg	S
Ali_Naimi\Ali_Naimi_0003.jpg	Ali_Naimi\Ali_Naimi_0004.jpg	S
Allison_Janney\Allison_Janney_0001.jpg	Allison_Janney\Allison_Janney_0002.jpg	S
Allyson_Felix\Allyson_Felix_0002.jpg	Allyson_Felix\Allyson_Felix_0005.jpg	S
Alvaro_Uribe\Alvaro_Uribe_0007.jpg	Alvaro_Uribe\Alvaro_Uribe_0010.jpg	S
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Amelie_Mauresmo\Amelie_Mauresmo_0004.jpg	Amelie_Mauresmo\Amelie_Mauresmo_0011.jpg	S
Amelie_Mauresmo\Amelie_Mauresmo_0016.jpg	Amelie_Mauresmo\Amelie_Mauresmo_0021.jpg	S
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Andy_Hebb\Andy_Hebb_0001.jpg	Andy_Hebb\Andy_Hebb_0002.jpg	S
Angelo_Reyes\Angelo_Reyes_0001.jpg	Angelo_Reyes\Angelo_Reyes_0002.jpg	S
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Ann_Veneman\Ann_Veneman_0001.jpg	Ann_Veneman\Ann_Veneman_0002.jpg	S
Ann_Veneman\Ann_Veneman_0005.jpg	Ann_Veneman\Ann_Veneman_0011.jpg	S
Ann_Veneman\Ann_Veneman_0008.jpg	Ann_Veneman\Ann_Veneman_0009.jpg	S
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Anne_Krueger\Anne_Krueger_0001.jpg	Anne_Krueger\Anne_Krueger_0002.jpg	S
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Annette_Lu\Annette_Lu_0001.jpg	Annette_Lu\Annette_Lu_0002.jpg	S
Annette_Lu\Annette_Lu_0001.jpg	Annette_Lu\Annette_Lu_0003.jpg	S
Annette_Lu\Annette_Lu_0002.jpg	Annette_Lu\Annette_Lu_0003.jpg	S
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Antonio_Trillanes\Antonio_Trillanes_0002.jpg	Antonio_Trillanes\Antonio_Trillanes_0003.jpg	S
Arlen_Specter\Arlen_Specter_0001.jpg	Arlen_Specter\Arlen_Specter_0003.jpg	S
Augustin_Calleri\Augustin_Calleri_0001.jpg	Augustin_Calleri\Augustin_Calleri_0003.jpg	S
Augustin_Calleri\Augustin_Calleri_0001.jpg	Augustin_Calleri\Augustin_Calleri_0004.jpg	S
Barbara_Brezigar\Barbara_Brezigar_0001.jpg	Barbara_Brezigar\Barbara_Brezigar_0002.jpg	S
Begum_Khaleda_Zia\Begum_Khaleda_Zia_0001.jpg	Begum_Khaleda_Zia\Begum_Khaleda_Zia_0002.jpg	S
Ben_Affleck\Ben_Affleck_0001.jpg	Ben_Affleck\Ben_Affleck_0003.jpg	S
Ben_Affleck\Ben_Affleck_0002.jpg	Ben_Affleck\Ben_Affleck_0006.jpg	S
Ben_Affleck\Ben_Affleck_0003.jpg	Ben_Affleck\Ben_Affleck_0006.jpg	S
Bertie_Ahern\Bertie_Ahern_0002.jpg	Bertie_Ahern\Bertie_Ahern_0003.jpg	S
Bill_Frist\Bill_Frist_0001.jpg	Bill_Frist\Bill_Frist_0003.jpg	S
Bill_Frist\Bill_Frist_0002.jpg	Bill_Frist\Bill_Frist_0007.jpg	S
Bill_Frist\Bill_Frist_0003.jpg	Bill_Frist\Bill_Frist_0008.jpg	S
Bill_McBride\Bill_McBride_0002.jpg	Bill_McBride\Bill_McBride_0006.jpg	S
Bill_McBride\Bill_McBride_0002.jpg	Bill_McBride\Bill_McBride_0010.jpg	S
Bill_McBride\Bill_McBride_0003.jpg	Bill_McBride\Bill_McBride_0009.jpg	S
Bill_Sizemore\Bill_Sizemore_0001.jpg	Bill_Sizemore\Bill_Sizemore_0002.jpg	S
Bono\Bono_0001.jpg	Bono\Bono_0002.jpg	S
Bono\Bono_0001.jpg	Bono\Bono_0003.jpg	S
Bono\Bono_0002.jpg	Bono\Bono_0003.jpg	S
Brian_Cowen\Brian_Cowen_0001.jpg	Brian_Cowen\Brian_Cowen_0002.jpg	S
Bridget_Fonda\Bridget_Fonda_0001.jpg	Bridget_Fonda\Bridget_Fonda_0003.jpg	S
Bridgette_Wilson-Sampras\Bridgette_Wilson-Sampras_0001.jpg	Bridgette_Wilson-Sampras\Bridgette_Wilson-Sampras_0002.jpg	S
Butch_Davis\Butch_Davis_0001.jpg	Butch_Davis\Butch_Davis_0002.jpg	S
Calista_Flockhart\Calista_Flockhart_0002.jpg	Calista_Flockhart\Calista_Flockhart_0006.jpg	S
Candice_Bergen\Candice_Bergen_0001.jpg	Candice_Bergen\Candice_Bergen_0003.jpg	S
Carla_Del_Ponte\Carla_Del_Ponte_0002.jpg	Carla_Del_Ponte\Carla_Del_Ponte_0004.jpg	S
Carla_Del_Ponte\Carla_Del_Ponte_0004.jpg	Carla_Del_Ponte\Carla_Del_Ponte_0005.jpg	S
Carlos_Manuel_Pruneda\Carlos_Manuel_Pruneda_0001.jpg	Carlos_Manuel_Pruneda\Carlos_Manuel_Pruneda_0002.jpg	S
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Carlos_Moya\Carlos_Moya_0007.jpg	Carlos_Moya\Carlos_Moya_0011.jpg	S
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Carolyn_Dawn_Johnson\Carolyn_Dawn_Johnson_0002.jpg	Carolyn_Dawn_Johnson\Carolyn_Dawn_Johnson_0003.jpg	S
Carrie-Anne_Moss\Carrie-Anne_Moss_0002.jpg	Carrie-Anne_Moss\Carrie-Anne_Moss_0005.jpg	S
Carson_Daly\Carson_Daly_0001.jpg	Carson_Daly\Carson_Daly_0002.jpg	S
Cathy_Freeman\Cathy_Freeman_0001.jpg	Cathy_Freeman\Cathy_Freeman_0002.jpg	S
Chanda_Rubin\Chanda_Rubin_0002.jpg	Chanda_Rubin\Chanda_Rubin_0004.jpg	S
Chang_Dae-whan\Chang_Dae-whan_0001.jpg	Chang_Dae-whan\Chang_Dae-whan_0002.jpg	S
Charles_Taylor\Charles_Taylor_0003.jpg	Charles_Taylor\Charles_Taylor_0009.jpg	S
Chen_Shui-bian\Chen_Shui-bian_0003.jpg	Chen_Shui-bian\Chen_Shui-bian_0005.jpg	S
Chita_Rivera\Chita_Rivera_0001.jpg	Chita_Rivera\Chita_Rivera_0002.jpg	S
Chok_Tong_Goh\Chok_Tong_Goh_0001.jpg	Chok_Tong_Goh\Chok_Tong_Goh_0002.jpg	S
Chris_Bell\Chris_Bell_0001.jpg	Chris_Bell\Chris_Bell_0002.jpg	S
Chris_Byrd\Chris_Byrd_0001.jpg	Chris_Byrd\Chris_Byrd_0002.jpg	S
Christian_Longo\Christian_Longo_0001.jpg	Christian_Longo\Christian_Longo_0003.jpg	S
Christian_Longo\Christian_Longo_0002.jpg	Christian_Longo\Christian_Longo_0003.jpg	S
Christian_Wulff\Christian_Wulff_0001.jpg	Christian_Wulff\Christian_Wulff_0002.jpg	S
Christine_Ebersole\Christine_Ebersole_0001.jpg	Christine_Ebersole\Christine_Ebersole_0002.jpg	S
Christine_Todd_Whitman\Christine_Todd_Whitman_0005.jpg	Christine_Todd_Whitman\Christine_Todd_Whitman_0006.jpg	S
Christopher_Reeve\Christopher_Reeve_0001.jpg	Christopher_Reeve\Christopher_Reeve_0004.jpg	S
Claire_Leger\Claire_Leger_0001.jpg	Claire_Leger\Claire_Leger_0002.jpg	S
Condoleezza_Rice\Condoleezza_Rice_0002.jpg	Condoleezza_Rice\Condoleezza_Rice_0005.jpg	S
Condoleezza_Rice\Condoleezza_Rice_0007.jpg	Condoleezza_Rice\Condoleezza_Rice_0010.jpg	S
Cristina_Fernandez\Cristina_Fernandez_0001.jpg	Cristina_Fernandez\Cristina_Fernandez_0002.jpg	S
Dai_Bachtiar\Dai_Bachtiar_0001.jpg	Dai_Bachtiar\Dai_Bachtiar_0002.jpg	S
Daisy_Fuentes\Daisy_Fuentes_0003.jpg	Daisy_Fuentes\Daisy_Fuentes_0004.jpg	S
Dave_Campo\Dave_Campo_0001.jpg	Dave_Campo\Dave_Campo_0002.jpg	S
Dave_Campo\Dave_Campo_0002.jpg	Dave_Campo\Dave_Campo_0003.jpg	S
David_Stern\David_Stern_0001.jpg	David_Stern\David_Stern_0004.jpg	S
David_Stern\David_Stern_0003.jpg	David_Stern\David_Stern_0004.jpg	S
Denise_Johnson\Denise_Johnson_0001.jpg	Denise_Johnson\Denise_Johnson_0002.jpg	S
Dennis_Powell\Dennis_Powell_0001.jpg	Dennis_Powell\Dennis_Powell_0002.jpg	S
Denzel_Washington\Denzel_Washington_0001.jpg	Denzel_Washington\Denzel_Washington_0003.jpg	S
Denzel_Washington\Denzel_Washington_0002.jpg	Denzel_Washington\Denzel_Washington_0004.jpg	S
Denzel_Washington\Denzel_Washington_0002.jpg	Denzel_Washington\Denzel_Washington_0005.jpg	S
Derek_Jeter\Derek_Jeter_0002.jpg	Derek_Jeter\Derek_Jeter_0003.jpg	S
Diane_Green\Diane_Green_0001.jpg	Diane_Green\Diane_Green_0002.jpg	S
Dick_Clark\Dick_Clark_0001.jpg	Dick_Clark\Dick_Clark_0002.jpg	S
Dick_Clark\Dick_Clark_0001.jpg	Dick_Clark\Dick_Clark_0003.jpg	S
Dick_Clark\Dick_Clark_0002.jpg	Dick_Clark\Dick_Clark_0003.jpg	S
Dick_Vermeil\Dick_Vermeil_0001.jpg	Dick_Vermeil\Dick_Vermeil_0002.jpg	S
Dominique_de_Villepin\Dominique_de_Villepin_0003.jpg	Dominique_de_Villepin\Dominique_de_Villepin_0005.jpg	S
Dominique_de_Villepin\Dominique_de_Villepin_0007.jpg	Dominique_de_Villepin\Dominique_de_Villepin_0011.jpg	S
Dominique_de_Villepin\Dominique_de_Villepin_0014.jpg	Dominique_de_Villepin\Dominique_de_Villepin_0015.jpg	S
Donald_Pettit\Donald_Pettit_0001.jpg	Donald_Pettit\Donald_Pettit_0002.jpg	S
Donald_Pettit\Donald_Pettit_0002.jpg	Donald_Pettit\Donald_Pettit_0003.jpg	S
Donald_Rumsfeld\Donald_Rumsfeld_0022.jpg	Donald_Rumsfeld\Donald_Rumsfeld_0036.jpg	S
Donald_Rumsfeld\Donald_Rumsfeld_0028.jpg	Donald_Rumsfeld\Donald_Rumsfeld_0108.jpg	S
Donald_Rumsfeld\Donald_Rumsfeld_0041.jpg	Donald_Rumsfeld\Donald_Rumsfeld_0048.jpg	S
Doug_Collins\Doug_Collins_0001.jpg	Doug_Collins\Doug_Collins_0002.jpg	S
Edward_Lu\Edward_Lu_0002.jpg	Edward_Lu\Edward_Lu_0004.jpg	S
Edward_Norton\Edward_Norton_0001.jpg	Edward_Norton\Edward_Norton_0002.jpg	S
Edwin_Edwards\Edwin_Edwards_0001.jpg	Edwin_Edwards\Edwin_Edwards_0002.jpg	S
Edwin_Edwards\Edwin_Edwards_0002.jpg	Edwin_Edwards\Edwin_Edwards_0003.jpg	S
Eliane_Karp\Eliane_Karp_0001.jpg	Eliane_Karp\Eliane_Karp_0004.jpg	S
Eliane_Karp\Eliane_Karp_0002.jpg	Eliane_Karp\Eliane_Karp_0003.jpg	S
Elin_Nordegren\Elin_Nordegren_0001.jpg	Elin_Nordegren\Elin_Nordegren_0002.jpg	S
Elinor_Caplan\Elinor_Caplan_0001.jpg	Elinor_Caplan\Elinor_Caplan_0002.jpg	S
Elisabeth_Schumacher\Elisabeth_Schumacher_0001.jpg	Elisabeth_Schumacher\Elisabeth_Schumacher_0002.jpg	S
Elizabeth_Smart\Elizabeth_Smart_0001.jpg	Elizabeth_Smart\Elizabeth_Smart_0005.jpg	S
Elizabeth_Smart\Elizabeth_Smart_0003.jpg	Elizabeth_Smart\Elizabeth_Smart_0004.jpg	S
Elsa_Zylberstein\Elsa_Zylberstein_0001.jpg	Elsa_Zylberstein\Elsa_Zylberstein_0002.jpg	S
Elsa_Zylberstein\Elsa_Zylberstein_0001.jpg	Elsa_Zylberstein\Elsa_Zylberstein_0005.jpg	S
Elsa_Zylberstein\Elsa_Zylberstein_0003.jpg	Elsa_Zylberstein\Elsa_Zylberstein_0006.jpg	S
Emma_Watson\Emma_Watson_0001.jpg	Emma_Watson\Emma_Watson_0004.jpg	S
Emma_Watson\Emma_Watson_0002.jpg	Emma_Watson\Emma_Watson_0003.jpg	S
Emma_Watson\Emma_Watson_0003.jpg	Emma_Watson\Emma_Watson_0005.jpg	S
Erik_Morales\Erik_Morales_0001.jpg	Erik_Morales\Erik_Morales_0003.jpg	S
Erika_Christensen\Erika_Christensen_0001.jpg	Erika_Christensen\Erika_Christensen_0002.jpg	S
Erin_Runnion\Erin_Runnion_0003.jpg	Erin_Runnion\Erin_Runnion_0004.jpg	S
Ernie_Fletcher\Ernie_Fletcher_0001.jpg	Ernie_Fletcher\Ernie_Fletcher_0002.jpg	S
Fabiola_Zuluaga\Fabiola_Zuluaga_0001.jpg	Fabiola_Zuluaga\Fabiola_Zuluaga_0002.jpg	S
Felipe_Perez_Roque\Felipe_Perez_Roque_0001.jpg	Felipe_Perez_Roque\Felipe_Perez_Roque_0004.jpg	S
Felipe_Perez_Roque\Felipe_Perez_Roque_0002.jpg	Felipe_Perez_Roque\Felipe_Perez_Roque_0004.jpg	S
Fernando_Vargas\Fernando_Vargas_0002.jpg	Fernando_Vargas\Fernando_Vargas_0004.jpg	S
Flor_Montulo\Flor_Montulo_0001.jpg	Flor_Montulo\Flor_Montulo_0002.jpg	S
Frank_Cassell\Frank_Cassell_0001.jpg	Frank_Cassell\Frank_Cassell_0002.jpg	S
Frank_Dunham_Jr\Frank_Dunham_Jr_0001.jpg	Frank_Dunham_Jr\Frank_Dunham_Jr_0002.jpg	S
Gao_Qiang\Gao_Qiang_0001.jpg	Gao_Qiang\Gao_Qiang_0002.jpg	S
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Gary_Doer\Gary_Doer_0001.jpg	Gary_Doer\Gary_Doer_0002.jpg	S
Gary_Doer\Gary_Doer_0001.jpg	Gary_Doer\Gary_Doer_0003.jpg	S
Gary_Doer\Gary_Doer_0002.jpg	Gary_Doer\Gary_Doer_0003.jpg	S
Gary_Winnick\Gary_Winnick_0001.jpg	Gary_Winnick\Gary_Winnick_0002.jpg	S
Gene_Robinson\Gene_Robinson_0002.jpg	Gene_Robinson\Gene_Robinson_0004.jpg	S
George_Foreman\George_Foreman_0001.jpg	George_Foreman\George_Foreman_0002.jpg	S
George_Karl\George_Karl_0001.jpg	George_Karl\George_Karl_0002.jpg	S
George_Robertson\George_Robertson_0005.jpg	George_Robertson\George_Robertson_0020.jpg	S
George_Robertson\George_Robertson_0012.jpg	George_Robertson\George_Robertson_0019.jpg	S
George_Robertson\George_Robertson_0015.jpg	George_Robertson\George_Robertson_0022.jpg	S
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Geraldine_Chaplin\Geraldine_Chaplin_0001.jpg	Geraldine_Chaplin\Geraldine_Chaplin_0003.jpg	S
Gerhard_Schroeder\Gerhard_Schroeder_0003.jpg	Gerhard_Schroeder\Gerhard_Schroeder_0026.jpg	S
Gerry_Adams\Gerry_Adams_0003.jpg	Gerry_Adams\Gerry_Adams_0007.jpg	S
Gerry_Adams\Gerry_Adams_0005.jpg	Gerry_Adams\Gerry_Adams_0008.jpg	S
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Giuseppe_Gibilisco\Giuseppe_Gibilisco_0002.jpg	Giuseppe_Gibilisco\Giuseppe_Gibilisco_0004.jpg	S
Giuseppe_Gibilisco\Giuseppe_Gibilisco_0003.jpg	Giuseppe_Gibilisco\Giuseppe_Gibilisco_0004.jpg	S
Glafcos_Clerides\Glafcos_Clerides_0001.jpg	Glafcos_Clerides\Glafcos_Clerides_0004.jpg	S
Gordon_Brown\Gordon_Brown_0004.jpg	Gordon_Brown\Gordon_Brown_0011.jpg	S
Gordon_Campbell\Gordon_Campbell_0001.jpg	Gordon_Campbell\Gordon_Campbell_0002.jpg	S
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Gray_Davis\Gray_Davis_0013.jpg	Gray_Davis\Gray_Davis_0023.jpg	S
Greg_Gilbert\Greg_Gilbert_0001.jpg	Greg_Gilbert\Greg_Gilbert_0002.jpg	S
Greg_Ostertag\Greg_Ostertag_0001.jpg	Greg_Ostertag\Greg_Ostertag_0002.jpg	S
Gregory_Hines\Gregory_Hines_0001.jpg	Gregory_Hines\Gregory_Hines_0002.jpg	S
Gus_Van_Sant\Gus_Van_Sant_0001.jpg	Gus_Van_Sant\Gus_Van_Sant_0002.jpg	S
Gwendal_Peizerat\Gwendal_Peizerat_0001.jpg	Gwendal_Peizerat\Gwendal_Peizerat_0002.jpg	S
Gwyneth_Paltrow\Gwyneth_Paltrow_0004.jpg	Gwyneth_Paltrow\Gwyneth_Paltrow_0005.jpg	S
Harry_Kalas\Harry_Kalas_0001.jpg	Harry_Kalas\Harry_Kalas_0002.jpg	S
Hassan_Wirajuda\Hassan_Wirajuda_0001.jpg	Hassan_Wirajuda\Hassan_Wirajuda_0002.jpg	S
Heather_Mills\Heather_Mills_0003.jpg	Heather_Mills\Heather_Mills_0004.jpg	S
Heidi_Fleiss\Heidi_Fleiss_0001.jpg	Heidi_Fleiss\Heidi_Fleiss_0003.jpg	S
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Ian_Thorpe\Ian_Thorpe_0003.jpg	Ian_Thorpe\Ian_Thorpe_0010.jpg	S
Ian_Thorpe\Ian_Thorpe_0006.jpg	Ian_Thorpe\Ian_Thorpe_0008.jpg	S
Isabella_Rossellini\Isabella_Rossellini_0001.jpg	Isabella_Rossellini\Isabella_Rossellini_0002.jpg	S
Isabelle_Huppert\Isabelle_Huppert_0001.jpg	Isabelle_Huppert\Isabelle_Huppert_0002.jpg	S
Ismail_Merchant\Ismail_Merchant_0001.jpg	Ismail_Merchant\Ismail_Merchant_0002.jpg	S
Jack_Grubman\Jack_Grubman_0001.jpg	Jack_Grubman\Jack_Grubman_0002.jpg	S
Jack_Nicholson\Jack_Nicholson_0002.jpg	Jack_Nicholson\Jack_Nicholson_0003.jpg	S
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Jacques_Chirac\Jacques_Chirac_0031.jpg	Jacques_Chirac\Jacques_Chirac_0052.jpg	S
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Jake_Gyllenhaal\Jake_Gyllenhaal_0002.jpg	Jake_Gyllenhaal\Jake_Gyllenhaal_0004.jpg	S
Jake_Gyllenhaal\Jake_Gyllenhaal_0003.jpg	Jake_Gyllenhaal\Jake_Gyllenhaal_0004.jpg	S
James_Butts\James_Butts_0001.jpg	James_Butts\James_Butts_0002.jpg	S
James_Franco\James_Franco_0001.jpg	James_Franco\James_Franco_0002.jpg	S
James_Kelly\James_Kelly_0004.jpg	James_Kelly\James_Kelly_0011.jpg	S
James_Kelly\James_Kelly_0009.jpg	James_Kelly\James_Kelly_0011.jpg	S
James_Kopp\James_Kopp_0001.jpg	James_Kopp\James_Kopp_0003.jpg	S
James_Kopp\James_Kopp_0002.jpg	James_Kopp\James_Kopp_0003.jpg	S
James_Maguire\James_Maguire_0001.jpg	James_Maguire\James_Maguire_0002.jpg	S
James_Smith\James_Smith_0001.jpg	James_Smith\James_Smith_0002.jpg	S
Jan_Ullrich\Jan_Ullrich_0002.jpg	Jan_Ullrich\Jan_Ullrich_0003.jpg	S
Jan_Ullrich\Jan_Ullrich_0002.jpg	Jan_Ullrich\Jan_Ullrich_0005.jpg	S
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Javier_Weber\Javier_Weber_0001.jpg	Javier_Weber\Javier_Weber_0002.jpg	S
Javier_Weber\Javier_Weber_0001.jpg	Javier_Weber\Javier_Weber_0003.jpg	S
Jean-Claude_Juncker\Jean-Claude_Juncker_0001.jpg	Jean-Claude_Juncker\Jean-Claude_Juncker_0002.jpg	S
Jean-Claude_Trichet\Jean-Claude_Trichet_0001.jpg	Jean-Claude_Trichet\Jean-Claude_Trichet_0002.jpg	S
Jean-Marc_de_La_Sabliere\Jean-Marc_de_La_Sabliere_0001.jpg	Jean-Marc_de_La_Sabliere\Jean-Marc_de_La_Sabliere_0002.jpg	S
Jean-Pierre_Raffarin\Jean-Pierre_Raffarin_0002.jpg	Jean-Pierre_Raffarin\Jean-Pierre_Raffarin_0006.jpg	S
Jean_Carnahan\Jean_Carnahan_0001.jpg	Jean_Carnahan\Jean_Carnahan_0002.jpg	S
Jefferson_Perez\Jefferson_Perez_0001.jpg	Jefferson_Perez\Jefferson_Perez_0002.jpg	S
Jennifer_Capriati\Jennifer_Capriati_0003.jpg	Jennifer_Capriati\Jennifer_Capriati_0013.jpg	S
Jennifer_Capriati\Jennifer_Capriati_0024.jpg	Jennifer_Capriati\Jennifer_Capriati_0029.jpg	S
Jennifer_Connelly\Jennifer_Connelly_0001.jpg	Jennifer_Connelly\Jennifer_Connelly_0004.jpg	S
Jennifer_Connelly\Jennifer_Connelly_0003.jpg	Jennifer_Connelly\Jennifer_Connelly_0004.jpg	S
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Jennifer_Keller\Jennifer_Keller_0003.jpg	Jennifer_Keller\Jennifer_Keller_0004.jpg	S
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Jeremy_Shockey\Jeremy_Shockey_0001.jpg	Jeremy_Shockey\Jeremy_Shockey_0002.jpg	S
Jesse_Ventura\Jesse_Ventura_0001.jpg	Jesse_Ventura\Jesse_Ventura_0003.jpg	S
Jessica_Lange\Jessica_Lange_0001.jpg	Jessica_Lange\Jessica_Lange_0002.jpg	S
Jiang_Zemin\Jiang_Zemin_0002.jpg	Jiang_Zemin\Jiang_Zemin_0017.jpg	S
Jiang_Zemin\Jiang_Zemin_0012.jpg	Jiang_Zemin\Jiang_Zemin_0015.jpg	S
Jim_Harrick\Jim_Harrick_0001.jpg	Jim_Harrick\Jim_Harrick_0002.jpg	S
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Joe_Mantello\Joe_Mantello_0001.jpg	Joe_Mantello\Joe_Mantello_0002.jpg	S
Joe_Nichols\Joe_Nichols_0001.jpg	Joe_Nichols\Joe_Nichols_0003.jpg	S
Joe_Nichols\Joe_Nichols_0003.jpg	Joe_Nichols\Joe_Nichols_0004.jpg	S
John_Bolton\John_Bolton_0003.jpg	John_Bolton\John_Bolton_0010.jpg	S
John_Bolton\John_Bolton_0004.jpg	John_Bolton\John_Bolton_0014.jpg	S
John_Bolton\John_Bolton_0005.jpg	John_Bolton\John_Bolton_0013.jpg	S
John_Bolton\John_Bolton_0011.jpg	John_Bolton\John_Bolton_0014.jpg	S
John_Garamendi\John_Garamendi_0001.jpg	John_Garamendi\John_Garamendi_0002.jpg	S
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John_Negroponte\John_Negroponte_0004.jpg	John_Negroponte\John_Negroponte_0017.jpg	S
John_Rowland\John_Rowland_0001.jpg	John_Rowland\John_Rowland_0002.jpg	S
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John_Travolta\John_Travolta_0004.jpg	John_Travolta\John_Travolta_0005.jpg	S
John_Walsh\John_Walsh_0001.jpg	John_Walsh\John_Walsh_0002.jpg	S
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Jorge_Castaneda\Jorge_Castaneda_0001.jpg	Jorge_Castaneda\Jorge_Castaneda_0002.jpg	S
Jose_Dirceu\Jose_Dirceu_0001.jpg	Jose_Dirceu\Jose_Dirceu_0002.jpg	S
Joseph_Deiss\Joseph_Deiss_0001.jpg	Joseph_Deiss\Joseph_Deiss_0002.jpg	S
Judi_Dench\Judi_Dench_0001.jpg	Judi_Dench\Judi_Dench_0002.jpg	S
Julie_Gerberding\Julie_Gerberding_0007.jpg	Julie_Gerberding\Julie_Gerberding_0012.jpg	S
Julie_Gerberding\Julie_Gerberding_0008.jpg	Julie_Gerberding\Julie_Gerberding_0012.jpg	S
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King_Abdullah_II\King_Abdullah_II_0001.jpg	King_Abdullah_II\King_Abdullah_II_0002.jpg	S
King_Abdullah_II\King_Abdullah_II_0001.jpg	King_Abdullah_II\King_Abdullah_II_0003.jpg	S
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Laurent_Jalabert\Laurent_Jalabert_0001.jpg	Laurent_Jalabert\Laurent_Jalabert_0002.jpg	S
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Mark_Dacey\Mark_Dacey_0001.jpg	Mark_Dacey\Mark_Dacey_0002.jpg	S
Mark_Richt\Mark_Richt_0001.jpg	Mark_Richt\Mark_Richt_0003.jpg	S
Mark_Richt\Mark_Richt_0002.jpg	Mark_Richt\Mark_Richt_0003.jpg	S
Martha_Burk\Martha_Burk_0002.jpg	Martha_Burk\Martha_Burk_0004.jpg	S
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Martin_Sheen\Martin_Sheen_0001.jpg	Martin_Sheen\Martin_Sheen_0002.jpg	S
Mary_Landrieu\Mary_Landrieu_0001.jpg	Mary_Landrieu\Mary_Landrieu_0003.jpg	S
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Matthew_Broderick\Matthew_Broderick_0002.jpg	Matthew_Broderick\Matthew_Broderick_0003.jpg	S
Matthew_Broderick\Matthew_Broderick_0003.jpg	Matthew_Broderick\Matthew_Broderick_0004.jpg	S
Melissa_Etheridge\Melissa_Etheridge_0001.jpg	Melissa_Etheridge\Melissa_Etheridge_0002.jpg	S
Michael_Jackson\Michael_Jackson_0002.jpg	Michael_Jackson\Michael_Jackson_0008.jpg	S
Michael_Phelps\Michael_Phelps_0001.jpg	Michael_Phelps\Michael_Phelps_0003.jpg	S
Michael_Sullivan\Michael_Sullivan_0001.jpg	Michael_Sullivan\Michael_Sullivan_0002.jpg	S
Michel_Duclos\Michel_Duclos_0001.jpg	Michel_Duclos\Michel_Duclos_0002.jpg	S
Michelle_Yeoh\Michelle_Yeoh_0003.jpg	Michelle_Yeoh\Michelle_Yeoh_0004.jpg	S
Miguel_Contreras\Miguel_Contreras_0001.jpg	Miguel_Contreras\Miguel_Contreras_0002.jpg	S
Mike_Price\Mike_Price_0001.jpg	Mike_Price\Mike_Price_0002.jpg	S
Mikhail_Youzhny\Mikhail_Youzhny_0001.jpg	Mikhail_Youzhny\Mikhail_Youzhny_0002.jpg	S
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Monica_Lewinsky\Monica_Lewinsky_0002.jpg	Monica_Lewinsky\Monica_Lewinsky_0003.jpg	S
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Muhammad_Ali\Muhammad_Ali_0006.jpg	Muhammad_Ali\Muhammad_Ali_0009.jpg	S
Nancy_Pelosi\Nancy_Pelosi_0002.jpg	Nancy_Pelosi\Nancy_Pelosi_0005.jpg	S
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Naomi_Campbell\Naomi_Campbell_0001.jpg	Naomi_Campbell\Naomi_Campbell_0002.jpg	S
Naoto_Kan\Naoto_Kan_0002.jpg	Naoto_Kan\Naoto_Kan_0003.jpg	S
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Norm_Coleman\Norm_Coleman_0002.jpg	Norm_Coleman\Norm_Coleman_0007.jpg	S
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Owen_Wilson\Owen_Wilson_0001.jpg	Owen_Wilson\Owen_Wilson_0002.jpg	S
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Paris_Hilton\Paris_Hilton_0001.jpg	Paris_Hilton\Paris_Hilton_0002.jpg	S
Patrick_Leahy\Patrick_Leahy_0001.jpg	Patrick_Leahy\Patrick_Leahy_0002.jpg	S
Patti_Labelle\Patti_Labelle_0001.jpg	Patti_Labelle\Patti_Labelle_0002.jpg	S
Patti_Labelle\Patti_Labelle_0002.jpg	Patti_Labelle\Patti_Labelle_0003.jpg	S
Patty_Schnyder\Patty_Schnyder_0001.jpg	Patty_Schnyder\Patty_Schnyder_0003.jpg	S
Patty_Schnyder\Patty_Schnyder_0001.jpg	Patty_Schnyder\Patty_Schnyder_0004.jpg	S
Paul-Henri_Mathieu\Paul-Henri_Mathieu_0001.jpg	Paul-Henri_Mathieu\Paul-Henri_Mathieu_0002.jpg	S
Paul_Burrell\Paul_Burrell_0004.jpg	Paul_Burrell\Paul_Burrell_0010.jpg	S
Paul_Burrell\Paul_Burrell_0005.jpg	Paul_Burrell\Paul_Burrell_0011.jpg	S
Paul_Martin\Paul_Martin_0001.jpg	Paul_Martin\Paul_Martin_0008.jpg	S
Paul_Martin\Paul_Martin_0002.jpg	Paul_Martin\Paul_Martin_0004.jpg	S
Paul_Martin\Paul_Martin_0003.jpg	Paul_Martin\Paul_Martin_0006.jpg	S
Paul_Patton\Paul_Patton_0001.jpg	Paul_Patton\Paul_Patton_0002.jpg	S
Paul_Sarbanes\Paul_Sarbanes_0002.jpg	Paul_Sarbanes\Paul_Sarbanes_0003.jpg	S
Pedro_Malan\Pedro_Malan_0001.jpg	Pedro_Malan\Pedro_Malan_0002.jpg	S
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Peter_Greenaway\Peter_Greenaway_0001.jpg	Peter_Greenaway\Peter_Greenaway_0002.jpg	S
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Rachel_Hunter\Rachel_Hunter_0002.jpg	Rachel_Hunter\Rachel_Hunter_0003.jpg	S
Ralf_Schumacher\Ralf_Schumacher_0001.jpg	Ralf_Schumacher\Ralf_Schumacher_0006.jpg	S
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Reese_Witherspoon\Reese_Witherspoon_0001.jpg	Reese_Witherspoon\Reese_Witherspoon_0002.jpg	S
Reese_Witherspoon\Reese_Witherspoon_0001.jpg	Reese_Witherspoon\Reese_Witherspoon_0004.jpg	S
Ricardo_Maduro\Ricardo_Maduro_0001.jpg	Ricardo_Maduro\Ricardo_Maduro_0002.jpg	S
Rich_Gannon\Rich_Gannon_0001.jpg	Rich_Gannon\Rich_Gannon_0002.jpg	S
Richard_Gere\Richard_Gere_0001.jpg	Richard_Gere\Richard_Gere_0010.jpg	S
Richard_Gere\Richard_Gere_0006.jpg	Richard_Gere\Richard_Gere_0010.jpg	S
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Rick_Romley\Rick_Romley_0001.jpg	Rick_Romley\Rick_Romley_0002.jpg	S
Rick_Wagoner\Rick_Wagoner_0001.jpg	Rick_Wagoner\Rick_Wagoner_0002.jpg	S
Rob_Schneider\Rob_Schneider_0001.jpg	Rob_Schneider\Rob_Schneider_0002.jpg	S
Robbie_Fowler\Robbie_Fowler_0001.jpg	Robbie_Fowler\Robbie_Fowler_0002.jpg	S
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Robert_Horan\Robert_Horan_0001.jpg	Robert_Horan\Robert_Horan_0002.jpg	S
Robert_Mueller\Robert_Mueller_0001.jpg	Robert_Mueller\Robert_Mueller_0003.jpg	S
Robert_Redford\Robert_Redford_0002.jpg	Robert_Redford\Robert_Redford_0003.jpg	S
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Scott_McNealy\Scott_McNealy_0001.jpg	Scott_McNealy\Scott_McNealy_0002.jpg	S
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Barry_Williams\Barry_Williams_0001.jpg	Richard_Langille\Richard_Langille_0001.jpg	D
Barzan_al-Tikriti\Barzan_al-Tikriti_0001.jpg	Jim_Haslett\Jim_Haslett_0001.jpg	D
Beecher_Ray_Kirby\Beecher_Ray_Kirby_0001.jpg	Hashan_Tillakaratne\Hashan_Tillakaratne_0001.jpg	D
Begum_Khaleda_Zia\Begum_Khaleda_Zia_0001.jpg	Jesse_Jackson\Jesse_Jackson_0005.jpg	D
Ben_Cohen\Ben_Cohen_0001.jpg	Roger_Etchegaray\Roger_Etchegaray_0001.jpg	D
Ben_Cohen\Ben_Cohen_0001.jpg	Zach_Parise\Zach_Parise_0001.jpg	D
Benjamin_McKenzie\Benjamin_McKenzie_0001.jpg	Lisa_Leslie\Lisa_Leslie_0001.jpg	D
Betsy_Coffin\Betsy_Coffin_0001.jpg	Gerard_Tronche\Gerard_Tronche_0001.jpg	D
Bill_Carmody\Bill_Carmody_0001.jpg	Michael_Sheehan\Michael_Sheehan_0001.jpg	D
Bill_Carmody\Bill_Carmody_0001.jpg	Tippi_Hedren\Tippi_Hedren_0001.jpg	D
Bill_Curry\Bill_Curry_0001.jpg	Candice_Bergen\Candice_Bergen_0001.jpg	D
Bill_Frist\Bill_Frist_0002.jpg	Malcolm_Wild\Malcolm_Wild_0001.jpg	D
Bill_Frist\Bill_Frist_0004.jpg	Donald_Pettit\Donald_Pettit_0002.jpg	D
Bill_Kollar\Bill_Kollar_0001.jpg	Phillip_Seymor_Hoffmann\Phillip_Seymor_Hoffmann_0001.jpg	D
Bill_McBride\Bill_McBride_0008.jpg	John_Rowland\John_Rowland_0001.jpg	D
Bill_Sizemore\Bill_Sizemore_0001.jpg	Calista_Flockhart\Calista_Flockhart_0003.jpg	D
Billy_Boyd\Billy_Boyd_0001.jpg	Liza_Minnelli\Liza_Minnelli_0003.jpg	D
Billy_Boyd\Billy_Boyd_0001.jpg	Robin_Williams\Robin_Williams_0001.jpg	D
Bing_Crosby\Bing_Crosby_0001.jpg	Eric_Bana\Eric_Bana_0001.jpg	D
Bing_Crosby\Bing_Crosby_0001.jpg	John_Moxley\John_Moxley_0001.jpg	D
Bing_Crosby\Bing_Crosby_0001.jpg	Leonid_Kuchma\Leonid_Kuchma_0005.jpg	D
Bob_Iger\Bob_Iger_0001.jpg	Brian_Cowen\Brian_Cowen_0001.jpg	D
Bob_Iger\Bob_Iger_0001.jpg	Steve_Lavin\Steve_Lavin_0006.jpg	D
Bob_Newhart\Bob_Newhart_0001.jpg	Marina_Canetti\Marina_Canetti_0001.jpg	D
Bob_Riley\Bob_Riley_0001.jpg	Jim_Harrick\Jim_Harrick_0001.jpg	D
Bono\Bono_0001.jpg	Chen_Shui-bian\Chen_Shui-bian_0002.jpg	D
Bono\Bono_0002.jpg	Se_Hyuk_Joo\Se_Hyuk_Joo_0001.jpg	D
Brad_Miller\Brad_Miller_0001.jpg	Chris_Noth\Chris_Noth_0001.jpg	D
Brandon_Larson\Brandon_Larson_0001.jpg	James_Williams\James_Williams_0001.jpg	D
Brandon_Lloyd\Brandon_Lloyd_0001.jpg	Zach_Parise\Zach_Parise_0001.jpg	D
Brandon_Robinson\Brandon_Robinson_0001.jpg	Mitchell_Garabedian\Mitchell_Garabedian_0001.jpg	D
Brandon_Webb\Brandon_Webb_0001.jpg	Teddy_Kollek\Teddy_Kollek_0001.jpg	D
Brian_Cowen\Brian_Cowen_0002.jpg	Dave_Johnson\Dave_Johnson_0001.jpg	D
Brian_Griese\Brian_Griese_0001.jpg	Jennie_Garth\Jennie_Garth_0001.jpg	D
Brock_Berlin\Brock_Berlin_0001.jpg	Wendy_Selig\Wendy_Selig_0001.jpg	D
Brooke_Adams\Brooke_Adams_0001.jpg	Gilberto_Rodriguez_Orejuela\Gilberto_Rodriguez_Orejuela_0002.jpg	D
Brooke_Adams\Brooke_Adams_0001.jpg	Hussam_Mohammed_Amin\Hussam_Mohammed_Amin_0001.jpg	D
Bruce_Willis\Bruce_Willis_0001.jpg	Heather_Mills\Heather_Mills_0002.jpg	D
Buddy_Ryan\Buddy_Ryan_0001.jpg	Laurel_Clark\Laurel_Clark_0001.jpg	D
Buddy_Ryan\Buddy_Ryan_0001.jpg	Roy_Romanow\Roy_Romanow_0001.jpg	D
Calvin_Joseph_Coleman\Calvin_Joseph_Coleman_0001.jpg	Ekaterina_Dmitriev\Ekaterina_Dmitriev_0001.jpg	D
Calvin_Joseph_Coleman\Calvin_Joseph_Coleman_0001.jpg	Victor_Garber\Victor_Garber_0001.jpg	D
Camilla_Parker_Bowles\Camilla_Parker_Bowles_0002.jpg	Mary_Matalin\Mary_Matalin_0001.jpg	D
Camille_Lewis\Camille_Lewis_0001.jpg	Keith_Lockhart\Keith_Lockhart_0001.jpg	D
Camille_Lewis\Camille_Lewis_0001.jpg	Melissa_Etheridge\Melissa_Etheridge_0001.jpg	D
Candice_Bergen\Candice_Bergen_0001.jpg	Masum_Turker\Masum_Turker_0002.jpg	D
Candice_Bergen\Candice_Bergen_0002.jpg	Jake_Gyllenhaal\Jake_Gyllenhaal_0002.jpg	D
Candice_Bergen\Candice_Bergen_0002.jpg	Prospero_Pichay\Prospero_Pichay_0001.jpg	D
Carey_Lowell\Carey_Lowell_0001.jpg	Helio_Castroneves\Helio_Castroneves_0001.jpg	D
Carey_Lowell\Carey_Lowell_0001.jpg	Joshua_Harapko\Joshua_Harapko_0001.jpg	D
Carlo_Ancelotti\Carlo_Ancelotti_0001.jpg	Hugh_Miller\Hugh_Miller_0001.jpg	D
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Carly_Gullickson\Carly_Gullickson_0001.jpg	Mike_Helton\Mike_Helton_0002.jpg	D
Caroline_Dhavernas\Caroline_Dhavernas_0001.jpg	James_Smith\James_Smith_0001.jpg	D
Carrie-Anne_Moss\Carrie-Anne_Moss_0004.jpg	Mike_Richter\Mike_Richter_0001.jpg	D
Carson_Daly\Carson_Daly_0001.jpg	Matthew_During\Matthew_During_0001.jpg	D
Casey_Crowder\Casey_Crowder_0001.jpg	Joe_Nichols\Joe_Nichols_0001.jpg	D
Casey_Crowder\Casey_Crowder_0001.jpg	Laszlo_Kovacs\Laszlo_Kovacs_0001.jpg	D
Cecilia_Chang\Cecilia_Chang_0001.jpg	Jeffery_Hendren\Jeffery_Hendren_0001.jpg	D
Cecilia_Cheung\Cecilia_Cheung_0001.jpg	Kirsten_Clark\Kirsten_Clark_0001.jpg	D
Cecilia_Cheung\Cecilia_Cheung_0001.jpg	Simon_Chalk\Simon_Chalk_0001.jpg	D
Cedric_Benson\Cedric_Benson_0001.jpg	Greg_Hodge\Greg_Hodge_0001.jpg	D
Cesar_Maia\Cesar_Maia_0002.jpg	Karin_Viard\Karin_Viard_0001.jpg	D
Chang_Jae_On\Chang_Jae_On_0001.jpg	Oracene_Williams\Oracene_Williams_0001.jpg	D
Chante_Jawan_Mallard\Chante_Jawan_Mallard_0001.jpg	Muhammad_Ali\Muhammad_Ali_0005.jpg	D
Charla_Moye\Charla_Moye_0001.jpg	Joe_Mantegna\Joe_Mantegna_0001.jpg	D
Charla_Moye\Charla_Moye_0001.jpg	Robert_Nillson\Robert_Nillson_0001.jpg	D
Charles_Cope\Charles_Cope_0001.jpg	John_Franco\John_Franco_0001.jpg	D
Charley_Armey\Charley_Armey_0001.jpg	Jose_Cevallos\Jose_Cevallos_0001.jpg	D
Charlie_Sheen\Charlie_Sheen_0001.jpg	Deece_Eckstein\Deece_Eckstein_0001.jpg	D
Charlie_Sheen\Charlie_Sheen_0001.jpg	Janice_Goldfinger\Janice_Goldfinger_0001.jpg	D
Charlie_Zaa\Charlie_Zaa_0002.jpg	William_Harrison\William_Harrison_0001.jpg	D
Charmaine_Crooks\Charmaine_Crooks_0001.jpg	Esad_Landzo\Esad_Landzo_0001.jpg	D
Charmaine_Crooks\Charmaine_Crooks_0001.jpg	Shigeru_Ishiba\Shigeru_Ishiba_0001.jpg	D
Chawki_Armali\Chawki_Armali_0001.jpg	Hilmi_Akin_Zorlu\Hilmi_Akin_Zorlu_0001.jpg	D
Chea_Sophara\Chea_Sophara_0001.jpg	Muhammad_Ali\Muhammad_Ali_0006.jpg	D
Chen_Shui-bian\Chen_Shui-bian_0002.jpg	Simon_Cowell\Simon_Cowell_0001.jpg	D
Chen_Shui-bian\Chen_Shui-bian_0002.jpg	William_Nessen\William_Nessen_0001.jpg	D
Chen_Shui-bian\Chen_Shui-bian_0003.jpg	Elizabeth_Smart\Elizabeth_Smart_0001.jpg	D
Chita_Rivera\Chita_Rivera_0002.jpg	Jose_Luis_Chilavert\Jose_Luis_Chilavert_0001.jpg	D
Chris_Andrews\Chris_Andrews_0001.jpg	Claire_De_Gryse\Claire_De_Gryse_0001.jpg	D
Chris_Andrews\Chris_Andrews_0001.jpg	Elinor_Caplan\Elinor_Caplan_0002.jpg	D
Chris_Byrd\Chris_Byrd_0001.jpg	David_Alpay\David_Alpay_0001.jpg	D
Chris_Byrd\Chris_Byrd_0001.jpg	Lawrence_Di_Rita\Lawrence_Di_Rita_0001.jpg	D
Chris_Noth\Chris_Noth_0001.jpg	Frank_Sinatra\Frank_Sinatra_0001.jpg	D
Christian_Longo\Christian_Longo_0002.jpg	Dustan_Mohr\Dustan_Mohr_0001.jpg	D
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Christine_Ebersole\Christine_Ebersole_0002.jpg	Vincent_Cianci_Jr\Vincent_Cianci_Jr_0001.jpg	D
Christine_Todd_Whitman\Christine_Todd_Whitman_0002.jpg	Peter_Rasch\Peter_Rasch_0001.jpg	D
Christine_Todd_Whitman\Christine_Todd_Whitman_0005.jpg	Neil_Goldman\Neil_Goldman_0001.jpg	D
Christopher_Russell\Christopher_Russell_0001.jpg	Rosario_Dawson\Rosario_Dawson_0001.jpg	D
Cindy_Taylor\Cindy_Taylor_0001.jpg	Melissa_Joan_Hart\Melissa_Joan_Hart_0001.jpg	D
Claire_Danes\Claire_Danes_0001.jpg	Mitchell_Potter\Mitchell_Potter_0001.jpg	D
Claire_De_Gryse\Claire_De_Gryse_0001.jpg	Jim_Parque\Jim_Parque_0001.jpg	D
Claire_De_Gryse\Claire_De_Gryse_0001.jpg	Soenarno\Soenarno_0001.jpg	D
Claire_Leger\Claire_Leger_0002.jpg	Elin_Nordegren\Elin_Nordegren_0002.jpg	D
Coleen_Rowley\Coleen_Rowley_0001.jpg	Courtney_Love\Courtney_Love_0001.jpg	D
Colin_Campbell\Colin_Campbell_0001.jpg	Matt_Walters\Matt_Walters_0001.jpg	D
Colleen_OClair\Colleen_OClair_0001.jpg	Kim_Hong-gul\Kim_Hong-gul_0001.jpg	D
Colleen_Ryan\Colleen_Ryan_0001.jpg	Noah_Wyle\Noah_Wyle_0002.jpg	D
Conchita_Martinez\Conchita_Martinez_0001.jpg	Moby\Moby_0001.jpg	D
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Damarius_Bilbo\Damarius_Bilbo_0001.jpg	Sheila_Taormina\Sheila_Taormina_0001.jpg	D
Dan_Ackroyd\Dan_Ackroyd_0001.jpg	Nikki_Teasley\Nikki_Teasley_0001.jpg	D
Dan_Bylsma\Dan_Bylsma_0001.jpg	Jim_Parque\Jim_Parque_0001.jpg	D
Dan_Bylsma\Dan_Bylsma_0001.jpg	Scott_Yates\Scott_Yates_0001.jpg	D
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Daniel_Montgomery\Daniel_Montgomery_0001.jpg	Hassan_Wirajuda\Hassan_Wirajuda_0001.jpg	D
Daniel_Zelman\Daniel_Zelman_0001.jpg	David_Surrett\David_Surrett_0001.jpg	D
Daniele_Nardello\Daniele_Nardello_0001.jpg	Peter_Hartz\Peter_Hartz_0001.jpg	D
Dariusz_Michalczewski\Dariusz_Michalczewski_0001.jpg	Julien_Boutter\Julien_Boutter_0001.jpg	D
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Dave_Johnson\Dave_Johnson_0001.jpg	Hank_Aaron\Hank_Aaron_0001.jpg	D
David_Braley\David_Braley_0001.jpg	Gerard_Tronche\Gerard_Tronche_0001.jpg	D
David_Kelley\David_Kelley_0001.jpg	Gerald_Calabrese\Gerald_Calabrese_0001.jpg	D
David_Shayler\David_Shayler_0001.jpg	Peter_Mullan\Peter_Mullan_0001.jpg	D
David_Surrett\David_Surrett_0001.jpg	Oracene_Williams\Oracene_Williams_0001.jpg	D
Dean_Sheremet\Dean_Sheremet_0001.jpg	Marc_Racicot\Marc_Racicot_0001.jpg	D
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Derrick_Battie\Derrick_Battie_0001.jpg	Lisa_Leslie\Lisa_Leslie_0001.jpg	D
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Diane_Green\Diane_Green_0001.jpg	Tim_Salmon\Tim_Salmon_0001.jpg	D
Dick_Armey\Dick_Armey_0001.jpg	Tom_Glavine\Tom_Glavine_0002.jpg	D
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Don_Carcieri\Don_Carcieri_0001.jpg	Jane_Rooney\Jane_Rooney_0001.jpg	D
Don_King\Don_King_0001.jpg	Philip_Zalewski\Philip_Zalewski_0001.jpg	D
Don_King\Don_King_0001.jpg	Tab_Baldwin\Tab_Baldwin_0001.jpg	D
Don_Lake\Don_Lake_0001.jpg	Elena_Dementieva\Elena_Dementieva_0001.jpg	D
Donald_Keck\Donald_Keck_0001.jpg	Julia_Ormond\Julia_Ormond_0001.jpg	D
Donald_Pettit\Donald_Pettit_0003.jpg	Michel_Kratochvil\Michel_Kratochvil_0001.jpg	D
Donald_Rumsfeld\Donald_Rumsfeld_0040.jpg	Tamika_Catchings\Tamika_Catchings_0001.jpg	D
Donna_Walker\Donna_Walker_0001.jpg	Phil_Bredesen\Phil_Bredesen_0001.jpg	D
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Edith_Masai\Edith_Masai_0001.jpg	Idi_Amin\Idi_Amin_0001.jpg	D
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Frank_Sinatra\Frank_Sinatra_0001.jpg	Vicente_Fox\Vicente_Fox_0023.jpg	D
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Fred_Durst\Fred_Durst_0001.jpg	Rose_Linkins\Rose_Linkins_0001.jpg	D
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Gary_Leon_Ridgway\Gary_Leon_Ridgway_0001.jpg	Lisa_Raymond\Lisa_Raymond_0001.jpg	D
Gary_Leon_Ridgway\Gary_Leon_Ridgway_0001.jpg	Phillip_Seymor_Hoffmann\Phillip_Seymor_Hoffmann_0001.jpg	D
Gary_Sayler\Gary_Sayler_0001.jpg	Nila_Ferran\Nila_Ferran_0001.jpg	D
George_Foreman\George_Foreman_0001.jpg	George_Lucas\George_Lucas_0001.jpg	D
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Gerhard_Schroeder\Gerhard_Schroeder_0003.jpg	Izzat_Ibrahim\Izzat_Ibrahim_0001.jpg	D
Ghassan_Elashi\Ghassan_Elashi_0001.jpg	Jesse_Ventura\Jesse_Ventura_0002.jpg	D
Ghassan_Elashi\Ghassan_Elashi_0001.jpg	Peter_Rasch\Peter_Rasch_0001.jpg	D
Gideon_Yago\Gideon_Yago_0001.jpg	Robert_Gordon_Card\Robert_Gordon_Card_0001.jpg	D
Gina_Gershon\Gina_Gershon_0001.jpg	Stacey_Dales-Schuman\Stacey_Dales-Schuman_0001.jpg	D
Glenn_Tilton\Glenn_Tilton_0001.jpg	Victor_Hanescu\Victor_Hanescu_0001.jpg	D
Gordon_Brown\Gordon_Brown_0012.jpg	Monica_Gabrielle\Monica_Gabrielle_0001.jpg	D
Gordon_Campbell\Gordon_Campbell_0001.jpg	Pierre_Boulanger\Pierre_Boulanger_0002.jpg	D
Gordon_Lightfoot\Gordon_Lightfoot_0001.jpg	Janez_Drnovsek\Janez_Drnovsek_0001.jpg	D
Grace_Kelly\Grace_Kelly_0001.jpg	Leslie_Moonves\Leslie_Moonves_0001.jpg	D
Greg_Kinnear\Greg_Kinnear_0001.jpg	Tim_Salmon\Tim_Salmon_0001.jpg	D
Gregory_Geoffroy\Gregory_Geoffroy_0002.jpg	Paul_Burrell\Paul_Burrell_0011.jpg	D
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Gregory_Peck\Gregory_Peck_0001.jpg	John_Lawrence\John_Lawrence_0001.jpg	D
Gregory_Peck\Gregory_Peck_0001.jpg	John_Lynch\John_Lynch_0001.jpg	D
Guillaume_Cannet\Guillaume_Cannet_0001.jpg	Mark_Mulder\Mark_Mulder_0001.jpg	D
Guillaume_Cannet\Guillaume_Cannet_0001.jpg	Mohammad_Khatami\Mohammad_Khatami_0005.jpg	D
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Gustavo_Franco\Gustavo_Franco_0001.jpg	Melissa_Joan_Hart\Melissa_Joan_Hart_0001.jpg	D
Gwendal_Peizerat\Gwendal_Peizerat_0002.jpg	Joe_Nichols\Joe_Nichols_0002.jpg	D
Gwyneth_Paltrow\Gwyneth_Paltrow_0005.jpg	Mike_Richter\Mike_Richter_0001.jpg	D
Halbert_Fillinger\Halbert_Fillinger_0001.jpg	Rachel_Hunter\Rachel_Hunter_0001.jpg	D
Hank_Aaron\Hank_Aaron_0001.jpg	Ron_Howard\Ron_Howard_0002.jpg	D
Harland_Braun\Harland_Braun_0001.jpg	Lisa_Leslie\Lisa_Leslie_0001.jpg	D
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Helene_Eksterowicz\Helene_Eksterowicz_0001.jpg	Mario_Lemieux\Mario_Lemieux_0001.jpg	D
Helio_Castroneves\Helio_Castroneves_0001.jpg	Joxel_Garcia\Joxel_Garcia_0001.jpg	D
Hermann_Maier\Hermann_Maier_0001.jpg	Robin_Williams\Robin_Williams_0001.jpg	D
Howard_Smith\Howard_Smith_0002.jpg	Tim_Pawlenty\Tim_Pawlenty_0001.jpg	D
Hubie_Brown\Hubie_Brown_0001.jpg	Yoon_Jeong_Cho\Yoon_Jeong_Cho_0001.jpg	D
Hunter_Bates\Hunter_Bates_0001.jpg	James_Williams\James_Williams_0001.jpg	D
Hussam_Mohammed_Amin\Hussam_Mohammed_Amin_0001.jpg	Mike_Smith\Mike_Smith_0001.jpg	D
Hussam_Mohammed_Amin\Hussam_Mohammed_Amin_0001.jpg	Princess_Hisako\Princess_Hisako_0001.jpg	D
Hutomo_Mandala_Putra\Hutomo_Mandala_Putra_0001.jpg	Thomas_Mesereau_Jr\Thomas_Mesereau_Jr_0001.jpg	D
Iban_Mayo\Iban_Mayo_0002.jpg	Yves_Brodeur\Yves_Brodeur_0001.jpg	D
Imad_Moustapha\Imad_Moustapha_0001.jpg	Will_Ofenheusle\Will_Ofenheusle_0001.jpg	D
Ion_Tiriac\Ion_Tiriac_0001.jpg	Lawrence_Roberts\Lawrence_Roberts_0001.jpg	D
Irina_Yatchenko\Irina_Yatchenko_0001.jpg	Pedro_Solbes\Pedro_Solbes_0004.jpg	D
Isabelle_Huppert\Isabelle_Huppert_0001.jpg	Pedro_Solbes\Pedro_Solbes_0001.jpg	D
Isaiah_Washington\Isaiah_Washington_0002.jpg	Lee_Baca\Lee_Baca_0001.jpg	D
Islam_Karimov\Islam_Karimov_0001.jpg	Shireen_Amir_Begum\Shireen_Amir_Begum_0001.jpg	D
Ismail_Cem\Ismail_Cem_0001.jpg	Seth_Gorney\Seth_Gorney_0001.jpg	D
Ismail_Merchant\Ismail_Merchant_0001.jpg	Joseph_Deiss\Joseph_Deiss_0001.jpg	D
Ivan_Lee\Ivan_Lee_0001.jpg	Paul-Henri_Mathieu\Paul-Henri_Mathieu_0003.jpg	D
Izzat_Ibrahim\Izzat_Ibrahim_0001.jpg	Tina_Sinatra\Tina_Sinatra_0001.jpg	D
Jack_Welch\Jack_Welch_0001.jpg	Rick_Dinse\Rick_Dinse_0002.jpg	D
Jack_Welch\Jack_Welch_0001.jpg	William_Umbach\William_Umbach_0001.jpg	D
Jalal_Talabani\Jalal_Talabani_0001.jpg	Jean-Marc_Olive\Jean-Marc_Olive_0001.jpg	D
James_Franco\James_Franco_0002.jpg	Lokendra_Bahadur_Chand\Lokendra_Bahadur_Chand_0001.jpg	D
James_Ivory\James_Ivory_0001.jpg	Paul_Martin\Paul_Martin_0007.jpg	D
James_Lockhart\James_Lockhart_0001.jpg	Lisa_Girman\Lisa_Girman_0001.jpg	D
Jan_Paul_Miller\Jan_Paul_Miller_0001.jpg	Lynne_Slepian\Lynne_Slepian_0001.jpg	D
Jan_Ullrich\Jan_Ullrich_0001.jpg	William_Rehnquist\William_Rehnquist_0001.jpg	D
Janet_Chandler\Janet_Chandler_0001.jpg	Zoe_Ball\Zoe_Ball_0001.jpg	D
Janis_Ruth_Coulter\Janis_Ruth_Coulter_0001.jpg	Laurent_Woulzy\Laurent_Woulzy_0001.jpg	D
Jason_Clermont\Jason_Clermont_0001.jpg	Vladimir_Ustinov\Vladimir_Ustinov_0001.jpg	D
Jason_Kapono\Jason_Kapono_0001.jpg	Patricia_Medina\Patricia_Medina_0001.jpg	D
Jason_Mewes\Jason_Mewes_0001.jpg	Will_Smith\Will_Smith_0001.jpg	D
Jason_White\Jason_White_0001.jpg	Wolfgang_Clement\Wolfgang_Clement_0001.jpg	D
Jean-Pierre_Raffarin\Jean-Pierre_Raffarin_0002.jpg	Robert_Horan\Robert_Horan_0002.jpg	D
Jean-Pierre_Raffarin\Jean-Pierre_Raffarin_0006.jpg	Paul_Kariya\Paul_Kariya_0001.jpg	D
Jeane_Kirkpatrick\Jeane_Kirkpatrick_0001.jpg	Richard_Carl\Richard_Carl_0001.jpg	D
Jeane_Kirkpatrick\Jeane_Kirkpatrick_0001.jpg	Tamika_Catchings\Tamika_Catchings_0001.jpg	D
Jeanne_Anne_Schroeder\Jeanne_Anne_Schroeder_0001.jpg	Yoriko_Kawaguchi\Yoriko_Kawaguchi_0013.jpg	D
Jeannette_Biedermann\Jeannette_Biedermann_0001.jpg	Roy_Moore\Roy_Moore_0006.jpg	D
Jeffrey_Pfeffer\Jeffrey_Pfeffer_0001.jpg	Terry_Lynn_Barton\Terry_Lynn_Barton_0001.jpg	D
Jen_Bice\Jen_Bice_0001.jpg	Lily_Tomlin\Lily_Tomlin_0002.jpg	D
Jen_Bice\Jen_Bice_0001.jpg	Martha_Burk\Martha_Burk_0002.jpg	D
Jenna_Elfman\Jenna_Elfman_0001.jpg	Mack_Brown\Mack_Brown_0001.jpg	D
Jenna_Elfman\Jenna_Elfman_0001.jpg	Steffi_Graf\Steffi_Graf_0005.jpg	D
Jenna_Elfman\Jenna_Elfman_0001.jpg	Willie_Wilson\Willie_Wilson_0001.jpg	D
Jennifer_Keller\Jennifer_Keller_0004.jpg	Paula_Abdul\Paula_Abdul_0001.jpg	D
Jennifer_Thompson\Jennifer_Thompson_0001.jpg	Serge_Melac\Serge_Melac_0001.jpg	D
Jeremy_Greenstock\Jeremy_Greenstock_0007.jpg	Jim_Flaherty\Jim_Flaherty_0001.jpg	D
Jerry_Bruckheimer\Jerry_Bruckheimer_0001.jpg	John_Blaney\John_Blaney_0001.jpg	D
Jerry_Jones\Jerry_Jones_0001.jpg	Robert_Woody_Johnson\Robert_Woody_Johnson_0001.jpg	D
Jesse_Ventura\Jesse_Ventura_0001.jpg	Reggie_Lewis\Reggie_Lewis_0001.jpg	D
Jesse_Ventura\Jesse_Ventura_0003.jpg	Roy_Romanow\Roy_Romanow_0001.jpg	D
Jessica_Biel\Jessica_Biel_0001.jpg	Jim_Freudenberg\Jim_Freudenberg_0001.jpg	D
Jim_Calhoun\Jim_Calhoun_0001.jpg	Perry_Farrell\Perry_Farrell_0001.jpg	D
Jim_Cantalupo\Jim_Cantalupo_0001.jpg	Joe_Pantoliano\Joe_Pantoliano_0001.jpg	D
Jim_Hahn\Jim_Hahn_0004.jpg	Vaclav_Havel\Vaclav_Havel_0003.jpg	D
Jim_Hahn\Jim_Hahn_0004.jpg	Vicente_Fernandez\Vicente_Fernandez_0002.jpg	D
Jim_Letten\Jim_Letten_0001.jpg	Victor_Hanescu\Victor_Hanescu_0001.jpg	D
Joaquin_Phoenix\Joaquin_Phoenix_0001.jpg	Kajsa_Bergqvist\Kajsa_Bergqvist_0001.jpg	D
Joe_Pantoliano\Joe_Pantoliano_0001.jpg	Robin_Tunney\Robin_Tunney_0001.jpg	D
John_Belushi\John_Belushi_0001.jpg	Mahima_Chaudhari\Mahima_Chaudhari_0001.jpg	D
John_Blaney\John_Blaney_0002.jpg	Sam_Brownback\Sam_Brownback_0001.jpg	D
John_Franco\John_Franco_0001.jpg	Teri_Files\Teri_Files_0001.jpg	D
John_Garamendi\John_Garamendi_0002.jpg	Peter_Goldmark\Peter_Goldmark_0001.jpg	D
John_Kerr\John_Kerr_0001.jpg	Susan_Whelan\Susan_Whelan_0001.jpg	D
John_Lynch\John_Lynch_0001.jpg	Stefano_Gabbana\Stefano_Gabbana_0001.jpg	D
John_Mayer\John_Mayer_0003.jpg	Miguel_Jimenez\Miguel_Jimenez_0001.jpg	D
John_McCallum\John_McCallum_0001.jpg	Mark_Andrew\Mark_Andrew_0001.jpg	D
John_Rowland\John_Rowland_0002.jpg	Robert_Lee_Yates_Jr\Robert_Lee_Yates_Jr_0001.jpg	D
John_Walsh\John_Walsh_0002.jpg	Paul_Hogan\Paul_Hogan_0002.jpg	D
Johnny_Depp\Johnny_Depp_0002.jpg	Scott_Dickson\Scott_Dickson_0001.jpg	D
Jorge_Arce\Jorge_Arce_0001.jpg	Samuel_Waksal\Samuel_Waksal_0003.jpg	D
Jorge_Quiroga\Jorge_Quiroga_0001.jpg	Ramona_Rispton\Ramona_Rispton_0001.jpg	D
Jorge_Quiroga\Jorge_Quiroga_0001.jpg	Surakait_Sathirathai\Surakait_Sathirathai_0001.jpg	D
Jose_Bove\Jose_Bove_0001.jpg	Michalis_Chrisohoides\Michalis_Chrisohoides_0001.jpg	D
Jose_Bove\Jose_Bove_0001.jpg	Princess_Diana\Princess_Diana_0001.jpg	D
Jose_Luis_Chilavert\Jose_Luis_Chilavert_0001.jpg	Sofyan_Dawood\Sofyan_Dawood_0001.jpg	D
Juan_Carlos\Juan_Carlos_0001.jpg	Patricia_Phillips\Patricia_Phillips_0001.jpg	D
Judy_Dean\Judy_Dean_0001.jpg	Kristanna_Loken\Kristanna_Loken_0001.jpg	D
Julia_Ormond\Julia_Ormond_0001.jpg	Randy_Dryer\Randy_Dryer_0001.jpg	D
Julio_Cesar_Chavez\Julio_Cesar_Chavez_0001.jpg	Marc_Racicot\Marc_Racicot_0001.jpg	D
Kaoru_Hasuike\Kaoru_Hasuike_0001.jpg	Tom_Foy\Tom_Foy_0001.jpg	D
Karen_Allen\Karen_Allen_0001.jpg	LeRoy_Millette_Jr\LeRoy_Millette_Jr_0001.jpg	D
Karen_Allen\Karen_Allen_0001.jpg	Rick_Bragg\Rick_Bragg_0001.jpg	D
Karl-Heinz_Rummenigge\Karl-Heinz_Rummenigge_0001.jpg	Wayne_Newton\Wayne_Newton_0001.jpg	D
Katie_Boone\Katie_Boone_0001.jpg	Terri_Clark\Terri_Clark_0001.jpg	D
Keith_Osik\Keith_Osik_0001.jpg	Robert_Nardelli\Robert_Nardelli_0001.jpg	D
Kent_Robinson\Kent_Robinson_0001.jpg	Marquier_Montano_Contreras\Marquier_Montano_Contreras_0001.jpg	D
Kevin_Gil\Kevin_Gil_0001.jpg	Mary_Bono\Mary_Bono_0001.jpg	D
Kevin_Hearn\Kevin_Hearn_0001.jpg	Todd_Haynes\Todd_Haynes_0003.jpg	D
Khader_Rashid_Rahim\Khader_Rashid_Rahim_0001.jpg	Martha_Burk\Martha_Burk_0001.jpg	D
Khader_Rashid_Rahim\Khader_Rashid_Rahim_0001.jpg	Michael_Arif\Michael_Arif_0001.jpg	D
Kim_Yong-il\Kim_Yong-il_0002.jpg	Terri_Clark\Terri_Clark_0001.jpg	D
Koichi_Tanaka\Koichi_Tanaka_0001.jpg	Sterling_Hitchcock\Sterling_Hitchcock_0001.jpg	D
Kosuke_Kitajima\Kosuke_Kitajima_0002.jpg	Qazi_Hussain_Ahmed\Qazi_Hussain_Ahmed_0001.jpg	D
Kristin_Davis\Kristin_Davis_0003.jpg	Steven_Van_Zandt\Steven_Van_Zandt_0001.jpg	D
Kurt_Hellstrom\Kurt_Hellstrom_0001.jpg	Manuel_Pellegrini\Manuel_Pellegrini_0001.jpg	D
Laszlo_Kovacs\Laszlo_Kovacs_0001.jpg	Michael_Arif\Michael_Arif_0001.jpg	D
Laura_Elena_Harring\Laura_Elena_Harring_0001.jpg	Rowan_Williams\Rowan_Williams_0001.jpg	D
Laurel_Clark\Laurel_Clark_0001.jpg	Rahul_Dravid\Rahul_Dravid_0001.jpg	D
Lawrence_Di_Rita\Lawrence_Di_Rita_0001.jpg	Tim_Allen\Tim_Allen_0002.jpg	D
Lawrence_Roberts\Lawrence_Roberts_0001.jpg	Malik_Mahmud\Malik_Mahmud_0001.jpg	D
Lea_Fastow\Lea_Fastow_0001.jpg	Todd_Parrott\Todd_Parrott_0001.jpg	D
Lee_Baca\Lee_Baca_0001.jpg	Pat_Summerall\Pat_Summerall_0001.jpg	D
Leisel_Jones\Leisel_Jones_0001.jpg	Steven_Hatfill\Steven_Hatfill_0001.jpg	D
Lena_Katina\Lena_Katina_0001.jpg	Queen_Noor\Queen_Noor_0001.jpg	D
Leonard_Glick\Leonard_Glick_0001.jpg	Terrence_Trammell\Terrence_Trammell_0001.jpg	D
Leonard_Schrank\Leonard_Schrank_0001.jpg	Ozzy_Osbourne\Ozzy_Osbourne_0001.jpg	D
Leslie_Wiser_Jr\Leslie_Wiser_Jr_0001.jpg	Mireya_Moscoso\Mireya_Moscoso_0001.jpg	D
Lisa_Murkowski\Lisa_Murkowski_0001.jpg	Svetlana_Belousova\Svetlana_Belousova_0001.jpg	D
Lisa_Raymond\Lisa_Raymond_0002.jpg	Robert_Redford\Robert_Redford_0007.jpg	D
Ludwig_Ovalle\Ludwig_Ovalle_0001.jpg	Mauricio_Macri\Mauricio_Macri_0001.jpg	D
Luis_Pujols\Luis_Pujols_0001.jpg	Rohman_al-Ghozi\Rohman_al-Ghozi_0001.jpg	D
Makhdoom_Amin_Fahim\Makhdoom_Amin_Fahim_0001.jpg	Tang_Jiaxuan\Tang_Jiaxuan_0005.jpg	D
Malcolm_Wild\Malcolm_Wild_0001.jpg	Owen_Wilson\Owen_Wilson_0002.jpg	D
Mamdouh_Habib\Mamdouh_Habib_0001.jpg	Polona_Bas\Polona_Bas_0001.jpg	D
Manijeh_Hekmat\Manijeh_Hekmat_0001.jpg	Richard_Carl\Richard_Carl_0001.jpg	D
Manijeh_Hekmat\Manijeh_Hekmat_0001.jpg	Se_Hyuk_Joo\Se_Hyuk_Joo_0001.jpg	D
Marc_Anthony\Marc_Anthony_0001.jpg	Vince_Vaughan\Vince_Vaughan_0001.jpg	D
Margie_Puente\Margie_Puente_0001.jpg	Rafiq_Hariri\Rafiq_Hariri_0001.jpg	D
Maria_Callas\Maria_Callas_0001.jpg	Melchor_Cob_Castro\Melchor_Cob_Castro_0001.jpg	D
Mario_Lemieux\Mario_Lemieux_0001.jpg	Pedro_Solbes\Pedro_Solbes_0004.jpg	D
Marissa_Jaret_Winokur\Marissa_Jaret_Winokur_0001.jpg	Vincent_Sombrotto\Vincent_Sombrotto_0001.jpg	D
Mark_Dacey\Mark_Dacey_0002.jpg	Russ_Ortiz\Russ_Ortiz_0001.jpg	D
Mark_Martin\Mark_Martin_0001.jpg	Vladimir_Spidla\Vladimir_Spidla_0002.jpg	D
Mark_Mishkin\Mark_Mishkin_0001.jpg	Nick_Reilly\Nick_Reilly_0001.jpg	D
Mark_Mishkin\Mark_Mishkin_0001.jpg	Shawn_Marion\Shawn_Marion_0001.jpg	D
Marricia_Tate\Marricia_Tate_0001.jpg	Rita_Moreno\Rita_Moreno_0002.jpg	D
Mary_Landrieu\Mary_Landrieu_0001.jpg	Robert_Gordon_Card\Robert_Gordon_Card_0001.jpg	D
Maryn_McKenna\Maryn_McKenna_0001.jpg	Shawn_Marion\Shawn_Marion_0001.jpg	D
Maryn_McKenna\Maryn_McKenna_0001.jpg	Tim_Pawlenty\Tim_Pawlenty_0001.jpg	D
Masum_Turker\Masum_Turker_0001.jpg	Norman_Mineta\Norman_Mineta_0001.jpg	D
Matt_Dillon\Matt_Dillon_0001.jpg	Regina_Ip\Regina_Ip_0001.jpg	D
Matthias_Sammer\Matthias_Sammer_0001.jpg	Robbie_Naish\Robbie_Naish_0001.jpg	D
Melissa_Etheridge\Melissa_Etheridge_0002.jpg	Teri_Files\Teri_Files_0001.jpg	D
Michael_J_Sheehan\Michael_J_Sheehan_0001.jpg	Michael_Smith_Foster\Michael_Smith_Foster_0001.jpg	D
Michael_Linscott\Michael_Linscott_0001.jpg	Robin_Tunney\Robin_Tunney_0001.jpg	D
Michael_Phelps\Michael_Phelps_0005.jpg	Pat_Burns\Pat_Burns_0002.jpg	D
Michael_Sheehan\Michael_Sheehan_0001.jpg	Vincent_Cianci_Jr\Vincent_Cianci_Jr_0001.jpg	D
Michael_Smith_Foster\Michael_Smith_Foster_0001.jpg	Rupert_Murdoch\Rupert_Murdoch_0001.jpg	D
Michelle_Yeoh\Michelle_Yeoh_0005.jpg	Shoshannah_Stern\Shoshannah_Stern_0001.jpg	D
Miguel_Aldana_Ibarra\Miguel_Aldana_Ibarra_0001.jpg	Mikhail_Gorbachev\Mikhail_Gorbachev_0001.jpg	D
Miguel_Jimenez\Miguel_Jimenez_0001.jpg	Paris_Hilton\Paris_Hilton_0001.jpg	D
Mike_Helton\Mike_Helton_0002.jpg	Reggie_Lewis\Reggie_Lewis_0001.jpg	D
Mike_Leach\Mike_Leach_0001.jpg	Thomas_Haeggstroem\Thomas_Haeggstroem_0001.jpg	D
Mike_Maroth\Mike_Maroth_0001.jpg	Stefan_Holm\Stefan_Holm_0001.jpg	D
Mike_Slive\Mike_Slive_0001.jpg	Paul_Sarbanes\Paul_Sarbanes_0003.jpg	D
Mikhail_Youzhny\Mikhail_Youzhny_0002.jpg	Vince_Dooley\Vince_Dooley_0001.jpg	D
Mikulas_Dzurinda\Mikulas_Dzurinda_0002.jpg	Shirley_Jones\Shirley_Jones_0001.jpg	D
Miles_Stewart\Miles_Stewart_0001.jpg	Yasushi_Akashi\Yasushi_Akashi_0001.jpg	D
Mirela_Manjani\Mirela_Manjani_0001.jpg	Robert_Woody_Johnson\Robert_Woody_Johnson_0001.jpg	D
Mitchell_McLaughlin\Mitchell_McLaughlin_0001.jpg	Timothy_Goebel\Timothy_Goebel_0001.jpg	D
Mohammed_Baqir_al-Hakim\Mohammed_Baqir_al-Hakim_0003.jpg	Neil_Goldman\Neil_Goldman_0001.jpg	D
Mona_Ayoub\Mona_Ayoub_0001.jpg	Todd_Parrott\Todd_Parrott_0001.jpg	D
Mufti_Mohammad_Syed\Mufti_Mohammad_Syed_0001.jpg	Ralf_Schumacher\Ralf_Schumacher_0004.jpg	D
Nathalie_Gagnon\Nathalie_Gagnon_0001.jpg	Rupert_Grint\Rupert_Grint_0002.jpg	D
Neil_Goldman\Neil_Goldman_0001.jpg	Niall_Connolly\Niall_Connolly_0001.jpg	D
Nick_Reilly\Nick_Reilly_0001.jpg	Tassos_Papadopoulos\Tassos_Papadopoulos_0001.jpg	D
Nicolas_Sarkozy\Nicolas_Sarkozy_0001.jpg	Shanna_Zolman\Shanna_Zolman_0001.jpg	D
Norm_Coleman\Norm_Coleman_0002.jpg	Osmond_Smith\Osmond_Smith_0001.jpg	D
Norman_Mailer\Norman_Mailer_0001.jpg	Steven_Curtis_Chapman\Steven_Curtis_Chapman_0001.jpg	D
Oliver_Neuville\Oliver_Neuville_0001.jpg	Shawn_Marion\Shawn_Marion_0001.jpg	D
Park_Jie-won\Park_Jie-won_0001.jpg	Steve_Patterson\Steve_Patterson_0001.jpg	D
Patty_Sheehan\Patty_Sheehan_0001.jpg	William_Nessen\William_Nessen_0001.jpg	D
Paul_Hogan\Paul_Hogan_0001.jpg	Thomas_Watjen\Thomas_Watjen_0001.jpg	D
Paul_Hogan\Paul_Hogan_0001.jpg	William_Martin\William_Martin_0001.jpg	D
Paul_Kariya\Paul_Kariya_0001.jpg	Shannon_OBrien\Shannon_OBrien_0002.jpg	D
Paul_Martin\Paul_Martin_0001.jpg	Stephanie_Cohen_Aloro\Stephanie_Cohen_Aloro_0001.jpg	D
Paul_Michael_Daniels\Paul_Michael_Daniels_0001.jpg	Simon_Chalk\Simon_Chalk_0001.jpg	D
Paul_Schrader\Paul_Schrader_0001.jpg	Teri_Files\Teri_Files_0001.jpg	D
Paula_Prentiss\Paula_Prentiss_0001.jpg	Thomas_Mesereau_Jr\Thomas_Mesereau_Jr_0001.jpg	D
Pedro_Martinez\Pedro_Martinez_0001.jpg	Stephen_Glassroth\Stephen_Glassroth_0001.jpg	D
Peter_Fitzgerald\Peter_Fitzgerald_0001.jpg	Zelma_Novelo\Zelma_Novelo_0001.jpg	D
Phil_Jackson\Phil_Jackson_0001.jpg	Richard_Penniman\Richard_Penniman_0001.jpg	D
Phillipe_Comtois\Phillipe_Comtois_0001.jpg	Richard_Carl\Richard_Carl_0001.jpg	D
Pierre_Boulanger\Pierre_Boulanger_0001.jpg	Shania_Twain\Shania_Twain_0001.jpg	D
Princess_Diana\Princess_Diana_0001.jpg	Steffi_Graf\Steffi_Graf_0002.jpg	D
Priscilla_Presley\Priscilla_Presley_0001.jpg	Sergey_Lavrov\Sergey_Lavrov_0005.jpg	D
Priscilla_Presley\Priscilla_Presley_0001.jpg	Victoria_Beckham\Victoria_Beckham_0003.jpg	D
Richard_Butler\Richard_Butler_0001.jpg	Victoria_Beckham\Victoria_Beckham_0001.jpg	D
Richard_Pennington\Richard_Pennington_0001.jpg	Stacy_Nelson\Stacy_Nelson_0001.jpg	D
Rick_Caruso\Rick_Caruso_0001.jpg	Steve_Wariner\Steve_Wariner_0001.jpg	D
Rick_Perry\Rick_Perry_0006.jpg	Svetlana_Koroleva\Svetlana_Koroleva_0001.jpg	D
Ricky_Cottrill\Ricky_Cottrill_0001.jpg	Sananda_Maitreya\Sananda_Maitreya_0001.jpg	D
Robert_Flodquist\Robert_Flodquist_0001.jpg	Winona_Ryder\Winona_Ryder_0011.jpg	D
Rod_Stewart\Rod_Stewart_0001.jpg	Tom_Scully\Tom_Scully_0001.jpg	D
Rod_Stewart\Rod_Stewart_0003.jpg	Se_Hyuk_Joo\Se_Hyuk_Joo_0001.jpg	D
Rod_Thorn\Rod_Thorn_0001.jpg	Yves_Brodeur\Yves_Brodeur_0001.jpg	D
Ron_Howard\Ron_Howard_0001.jpg	Tim_Pawlenty\Tim_Pawlenty_0001.jpg	D
Ronaldo_Luis_Nazario_de_Lima\Ronaldo_Luis_Nazario_de_Lima_0001.jpg	Samuel_Waksal\Samuel_Waksal_0002.jpg	D
Sami_Al-Arian\Sami_Al-Arian_0001.jpg	Tommy_Lasorda\Tommy_Lasorda_0001.jpg	D
Sarah_Canale\Sarah_Canale_0001.jpg	Steven_Curtis_Chapman\Steven_Curtis_Chapman_0001.jpg	D
Sasha_Cohen\Sasha_Cohen_0001.jpg	Valery_Giscard_dEstaing\Valery_Giscard_dEstaing_0005.jpg	D
Scott_Dalton\Scott_Dalton_0001.jpg	Tamara_Mowry\Tamara_Mowry_0001.jpg	D
Sergio_Castellitto\Sergio_Castellitto_0001.jpg	Steve_Lavin\Steve_Lavin_0005.jpg	D
Seth_Gorney\Seth_Gorney_0001.jpg	Wilton_Gregory\Wilton_Gregory_0001.jpg	D
Shane_Mosley\Shane_Mosley_0001.jpg	Stacey_Dales-Schuman\Stacey_Dales-Schuman_0001.jpg	D
Sheila_Taormina\Sheila_Taormina_0001.jpg	Stephan_Eberharter\Stephan_Eberharter_0001.jpg	D
Stefano_Gabbana\Stefano_Gabbana_0001.jpg	Tang_Jiaxuan\Tang_Jiaxuan_0003.jpg	D
Steve_Wariner\Steve_Wariner_0001.jpg	Toshi_Izawa\Toshi_Izawa_0001.jpg	D
Steve_Zahn\Steve_Zahn_0001.jpg	Tab_Baldwin\Tab_Baldwin_0001.jpg	D
Susan_Whelan\Susan_Whelan_0001.jpg	Wolfgang_Schneiderhan\Wolfgang_Schneiderhan_0001.jpg	D
Takeo_Fukui\Takeo_Fukui_0001.jpg	Will_Ofenheusle\Will_Ofenheusle_0001.jpg	D
Tamara_Mowry\Tamara_Mowry_0001.jpg	Zach_Parise\Zach_Parise_0001.jpg	D
Tatiana_Kennedy_Schlossberg\Tatiana_Kennedy_Schlossberg_0001.jpg	Thomas_Watjen\Thomas_Watjen_0001.jpg	D
Todd_Petit\Todd_Petit_0001.jpg	Vicente_Fernandez\Vicente_Fernandez_0003.jpg	D


================================================
FILE: TestCases/verification_text_files/LFW/validation_test_gen.py
================================================
'''
conver a standard parisDevTest.txt file from LFW database to standard validation.txt

examples of pairsDevTest:
Abdullah_Gul	13	14
Candice_Bergen	2	Prospero_Pichay	1

examples of validation.txt
Abdullah_Gul\Abdullah_Gul_0013.jpg      Abdullah_Gul\Abdullah_Gul_0014.jpg          S
Candice_Bergen\Candice_Bergen_0013.jpg  Prospero_Pichay\Prospero_Pichay_0014.jpg    D 
'''

import pandas as pd
from os.path import join

path_from = 'pairsDevTest.txt'
path_to = 'validation.txt'

def CreateFilename(name, idx):
    idx = int(idx)
    return name + '_' + '%04d' % idx + '.jpg'
    
def TransforDifferent(inputs):
    assert len(inputs)==4
    name1, idx1, name2, idx2 = inputs
    path1 = join(name1, CreateFilename(name1, idx1))
    path2 = join(name2, CreateFilename(name2, idx2))
    label = 'D'
    return path1, path2, label
    
def TransforSame(inputs):
    assert len(inputs)==3
    name, idx1, idx2 = inputs
    path1 = join(name, CreateFilename(name, idx1))
    path2 = join(name, CreateFilename(name, idx2))
    label = 'S'
    return path1, path2, label
    

    
if __name__=='__main__':
    list_path1 = []
    list_path2 = []
    list_label = []
    with open(path_from) as file:
        for line in file:
            # print(line)
            line = line.split(sep='\t')
            if len(line)==4: #deffierent person
                path1, path2, label = TransforDifferent(line)
            else: # same person
                path1, path2, label = TransforSame(line)
            list_path1.append(path1)
            list_path2.append(path2)
            list_label.append(label)
        
    df = pd.DataFrame([])
    df['img1'] = pd.Series(list_path1)
    df['img2'] = pd.Series(list_path2)
    df['class'] = pd.Series(list_label)
    df.to_csv(path_to, sep='\t', index=False, header=True)
    
    

================================================
FILE: TestCases/verification_text_files/PCD/read me.txt
================================================
python script of generating this validation.txt file is lost :(

================================================
FILE: TestCases/verification_text_files/PCD/validation.txt
================================================
img1	img2	class
002\01.jpg	002\21.jpg	S
013\04.jpg	013\08.jpg	S
025\17.jpg	025\05.jpg	S
027\27.jpg	027\22.jpg	S
026\04.jpg	026\15.jpg	S
008\08.jpg	008\18.jpg	S
022\04.jpg	022\22.jpg	S
023\27.jpg	023\26.jpg	S
023\23.jpg	023\19.jpg	S
004\16.jpg	004\21.jpg	S
009\22.jpg	009\14.jpg	S
005\13.jpg	005\01.jpg	S
013\18.jpg	013\10.jpg	S
027\05.jpg	027\04.jpg	S
021\21.jpg	021\13.jpg	S
022\10.jpg	022\09.jpg	S
011\07.jpg	011\19.jpg	S
012\13.jpg	012\31.jpg	S
025\10.jpg	025\00.jpg	S
029\03.jpg	029\20.jpg	S
029\12.jpg	029\17.jpg	S
007\17.jpg	007\18.jpg	S
006\06.jpg	006\31.jpg	S
028\08.jpg	028\16.jpg	S
015\08.jpg	015\01.jpg	S
021\21.jpg	021\04.jpg	S
013\15.jpg	013\16.jpg	S
003\16.jpg	003\11.jpg	S
006\03.jpg	006\26.jpg	S
018\04.jpg	018\18.jpg	S
003\14.jpg	003\23.jpg	S
021\03.jpg	021\02.jpg	S
018\24.jpg	018\08.jpg	S
010\21.jpg	010\18.jpg	S
022\18.jpg	022\10.jpg	S
017\24.jpg	017\12.jpg	S
014\30.jpg	014\09.jpg	S
029\00.jpg	029\04.jpg	S
021\11.jpg	021\19.jpg	S
009\05.jpg	009\19.jpg	S
019\06.jpg	019\23.jpg	S
006\20.jpg	006\26.jpg	S
029\13.jpg	029\09.jpg	S
022\24.jpg	022\18.jpg	S
006\22.jpg	006\11.jpg	S
020\08.jpg	020\05.jpg	S
013\10.jpg	013\03.jpg	S
027\03.jpg	027\11.jpg	S
003\05.jpg	003\16.jpg	S
004\10.jpg	004\21.jpg	S
005\09.jpg	005\23.jpg	S
028\18.jpg	028\19.jpg	S
016\02.jpg	016\34.jpg	S
016\12.jpg	016\34.jpg	S
001\27.jpg	001\18.jpg	S
003\19.jpg	003\21.jpg	S
015\19.jpg	015\24.jpg	S
005\22.jpg	005\21.jpg	S
009\14.jpg	009\12.jpg	S
024\17.jpg	024\14.jpg	S
014\01.jpg	014\27.jpg	S
007\17.jpg	007\16.jpg	S
008\15.jpg	008\19.jpg	S
015\13.jpg	015\03.jpg	S
027\26.jpg	027\23.jpg	S
018\09.jpg	018\21.jpg	S
022\04.jpg	022\20.jpg	S
023\10.jpg	023\07.jpg	S
020\25.jpg	020\04.jpg	S
019\12.jpg	019\00.jpg	S
023\23.jpg	023\24.jpg	S
007\09.jpg	007\20.jpg	S
022\14.jpg	022\18.jpg	S
004\02.jpg	004\15.jpg	S
024\13.jpg	024\15.jpg	S
012\15.jpg	012\21.jpg	S
002\17.jpg	002\19.jpg	S
006\36.jpg	006\07.jpg	S
026\11.jpg	026\01.jpg	S
012\17.jpg	012\00.jpg	S
019\17.jpg	019\05.jpg	S
016\24.jpg	016\25.jpg	S
011\05.jpg	011\13.jpg	S
000\25.jpg	000\19.jpg	S
012\09.jpg	012\14.jpg	S
017\20.jpg	017\06.jpg	S
023\18.jpg	023\12.jpg	S
009\17.jpg	009\00.jpg	S
023\10.jpg	023\21.jpg	S
020\14.jpg	020\19.jpg	S
010\22.jpg	010\09.jpg	S
021\01.jpg	021\12.jpg	S
009\08.jpg	009\16.jpg	S
000\18.jpg	000\19.jpg	S
025\03.jpg	025\21.jpg	S
012\11.jpg	012\18.jpg	S
020\08.jpg	020\00.jpg	S
016\34.jpg	016\17.jpg	S
022\06.jpg	022\10.jpg	S
017\26.jpg	017\23.jpg	S
012\02.jpg	012\07.jpg	S
009\24.jpg	009\20.jpg	S
019\23.jpg	019\03.jpg	S
010\07.jpg	010\18.jpg	S
016\05.jpg	016\34.jpg	S
025\04.jpg	025\26.jpg	S
010\24.jpg	010\25.jpg	S
007\21.jpg	007\17.jpg	S
011\14.jpg	011\04.jpg	S
002\14.jpg	002\16.jpg	S
027\23.jpg	027\33.jpg	S
027\10.jpg	027\03.jpg	S
016\26.jpg	016\17.jpg	S
017\09.jpg	017\16.jpg	S
006\26.jpg	006\38.jpg	S
020\06.jpg	020\25.jpg	S
003\10.jpg	003\24.jpg	S
001\26.jpg	001\17.jpg	S
019\19.jpg	019\13.jpg	S
006\11.jpg	006\10.jpg	S
021\10.jpg	021\16.jpg	S
012\09.jpg	012\21.jpg	S
026\01.jpg	026\05.jpg	S
014\08.jpg	014\05.jpg	S
001\09.jpg	001\19.jpg	S
014\22.jpg	014\21.jpg	S
029\20.jpg	029\03.jpg	S
008\12.jpg	008\06.jpg	S
025\11.jpg	025\06.jpg	S
002\05.jpg	002\01.jpg	S
000\23.jpg	000\24.jpg	S
001\05.jpg	001\09.jpg	S
020\13.jpg	020\27.jpg	S
018\14.jpg	018\06.jpg	S
028\10.jpg	028\26.jpg	S
002\10.jpg	002\04.jpg	S
003\12.jpg	003\01.jpg	S
020\15.jpg	020\11.jpg	S
002\01.jpg	002\17.jpg	S
019\17.jpg	019\25.jpg	S
020\02.jpg	020\03.jpg	S
008\23.jpg	008\05.jpg	S
028\00.jpg	028\09.jpg	S
003\20.jpg	003\17.jpg	S
009\23.jpg	009\17.jpg	S
001\05.jpg	001\09.jpg	S
001\07.jpg	001\06.jpg	S
020\01.jpg	020\14.jpg	S
029\07.jpg	029\17.jpg	S
017\08.jpg	017\00.jpg	S
011\27.jpg	011\16.jpg	S
003\03.jpg	003\10.jpg	S
016\23.jpg	016\31.jpg	S
018\07.jpg	018\03.jpg	S
009\18.jpg	009\23.jpg	S
009\00.jpg	009\05.jpg	S
002\02.jpg	002\11.jpg	S
025\01.jpg	025\09.jpg	S
016\16.jpg	016\11.jpg	S
001\29.jpg	001\12.jpg	S
024\20.jpg	024\09.jpg	S
002\17.jpg	002\15.jpg	S
019\23.jpg	019\08.jpg	S
015\19.jpg	015\10.jpg	S
004\17.jpg	004\11.jpg	S
016\02.jpg	016\03.jpg	S
019\08.jpg	019\10.jpg	S
024\20.jpg	024\15.jpg	S
013\03.jpg	013\11.jpg	S
016\30.jpg	016\07.jpg	S
010\20.jpg	010\27.jpg	S
023\13.jpg	023\23.jpg	S
015\21.jpg	015\19.jpg	S
009\12.jpg	009\02.jpg	S
014\21.jpg	014\07.jpg	S
022\20.jpg	022\11.jpg	S
015\07.jpg	015\12.jpg	S
023\03.jpg	023\06.jpg	S
016\18.jpg	016\22.jpg	S
022\19.jpg	022\12.jpg	S
019\09.jpg	019\16.jpg	S
011\25.jpg	011\28.jpg	S
005\04.jpg	005\16.jpg	S
008\01.jpg	008\15.jpg	S
023\03.jpg	023\17.jpg	S
008\23.jpg	008\06.jpg	S
029\06.jpg	029\09.jpg	S
004\15.jpg	004\13.jpg	S
029\23.jpg	029\11.jpg	S
001\28.jpg	001\29.jpg	S
000\03.jpg	000\13.jpg	S
017\07.jpg	017\24.jpg	S
012\13.jpg	012\18.jpg	S
009\08.jpg	009\00.jpg	S
027\15.jpg	027\29.jpg	S
009\16.jpg	009\17.jpg	S
027\17.jpg	027\25.jpg	S
003\01.jpg	003\04.jpg	S
002\07.jpg	002\01.jpg	S
018\26.jpg	018\13.jpg	S
021\04.jpg	021\12.jpg	S
015\15.jpg	015\12.jpg	S
024\19.jpg	024\16.jpg	S
004\24.jpg	004\07.jpg	S
004\19.jpg	004\18.jpg	S
015\19.jpg	015\06.jpg	S
019\25.jpg	019\15.jpg	S
018\13.jpg	018\08.jpg	S
000\28.jpg	000\20.jpg	S
021\06.jpg	021\11.jpg	S
022\01.jpg	022\13.jpg	S
024\15.jpg	024\17.jpg	S
009\16.jpg	009\23.jpg	S
008\16.jpg	008\14.jpg	S
009\09.jpg	009\19.jpg	S
028\24.jpg	028\18.jpg	S
019\11.jpg	019\15.jpg	S
006\13.jpg	006\05.jpg	S
005\21.jpg	005\18.jpg	S
000\20.jpg	000\06.jpg	S
021\13.jpg	021\15.jpg	S
001\13.jpg	001\03.jpg	S
015\10.jpg	015\11.jpg	S
012\18.jpg	012\24.jpg	S
011\15.jpg	011\16.jpg	S
026\21.jpg	026\02.jpg	S
010\19.jpg	010\16.jpg	S
018\01.jpg	018\02.jpg	S
013\22.jpg	013\14.jpg	S
007\09.jpg	007\07.jpg	S
010\06.jpg	010\05.jpg	S
017\15.jpg	017\12.jpg	S
002\04.jpg	002\08.jpg	S
003\15.jpg	003\01.jpg	S
025\18.jpg	025\02.jpg	S
004\17.jpg	004\11.jpg	S
021\15.jpg	021\03.jpg	S
018\09.jpg	018\24.jpg	S
009\00.jpg	009\21.jpg	S
015\14.jpg	015\17.jpg	S
025\07.jpg	025\23.jpg	S
007\01.jpg	007\00.jpg	S
000\04.jpg	000\02.jpg	S
005\07.jpg	005\16.jpg	S
028\28.jpg	028\25.jpg	S
000\14.jpg	000\03.jpg	S
007\22.jpg	007\10.jpg	S
000\01.jpg	000\25.jpg	S
022\19.jpg	022\15.jpg	S
019\13.jpg	019\15.jpg	S
014\06.jpg	014\00.jpg	S
024\00.jpg	024\12.jpg	S
007\22.jpg	007\18.jpg	S
015\16.jpg	015\08.jpg	S
012\20.jpg	012\27.jpg	S
004\19.jpg	004\26.jpg	S
018\12.jpg	018\22.jpg	S
017\16.jpg	017\19.jpg	S
020\23.jpg	020\00.jpg	S
021\10.jpg	021\07.jpg	S
009\12.jpg	009\06.jpg	S
019\14.jpg	019\07.jpg	S
011\24.jpg	011\15.jpg	S
026\00.jpg	026\21.jpg	S
012\20.jpg	012\02.jpg	S
015\17.jpg	015\01.jpg	S
005\17.jpg	005\15.jpg	S
000\16.jpg	000\13.jpg	S
006\24.jpg	006\06.jpg	S
016\34.jpg	016\02.jpg	S
001\29.jpg	001\13.jpg	S
029\11.jpg	029\10.jpg	S
023\06.jpg	023\16.jpg	S
029\02.jpg	029\05.jpg	S
017\23.jpg	017\11.jpg	S
005\18.jpg	005\09.jpg	S
029\10.jpg	029\13.jpg	S
029\11.jpg	029\10.jpg	S
018\13.jpg	018\07.jpg	S
016\23.jpg	016\29.jpg	S
007\23.jpg	007\15.jpg	S
019\13.jpg	019\01.jpg	S
017\07.jpg	017\03.jpg	S
027\07.jpg	027\22.jpg	S
025\07.jpg	025\11.jpg	S
018\20.jpg	018\17.jpg	S
010\12.jpg	010\25.jpg	S
000\24.jpg	000\20.jpg	S
003\04.jpg	003\15.jpg	S
005\20.jpg	005\19.jpg	S
026\03.jpg	026\21.jpg	S
028\14.jpg	028\09.jpg	S
014\19.jpg	014\16.jpg	S
023\23.jpg	023\00.jpg	S
026\13.jpg	026\06.jpg	S
010\19.jpg	010\14.jpg	S
014\13.jpg	014\06.jpg	S
001\04.jpg	001\10.jpg	S
017\20.jpg	017\18.jpg	S
026\16.jpg	026\12.jpg	S
024\12.jpg	024\21.jpg	S
005\04.jpg	005\12.jpg	S
005\10.jpg	005\06.jpg	S
000\24.jpg	000\21.jpg	S
009\19.jpg	009\00.jpg	S
021\01.jpg	021\09.jpg	S
023\07.jpg	023\09.jpg	S
008\14.jpg	008\06.jpg	S
005\21.jpg	005\07.jpg	S
021\02.jpg	021\09.jpg	S
014\09.jpg	014\20.jpg	S
008\10.jpg	008\22.jpg	S
002\06.jpg	002\17.jpg	S
013\13.jpg	013\06.jpg	S
009\08.jpg	009\04.jpg	S
022\00.jpg	022\23.jpg	S
006\10.jpg	006\25.jpg	S
002\08.jpg	002\03.jpg	S
002\10.jpg	002\11.jpg	S
005\18.jpg	005\03.jpg	S
014\24.jpg	014\29.jpg	S
007\11.jpg	007\02.jpg	S
024\03.jpg	024\19.jpg	S
023\27.jpg	023\24.jpg	S
014\07.jpg	014\27.jpg	S
027\36.jpg	027\30.jpg	S
009\16.jpg	009\04.jpg	S
028\03.jpg	028\04.jpg	S
027\00.jpg	027\25.jpg	S
023\03.jpg	023\01.jpg	S
018\07.jpg	018\14.jpg	S
021\02.jpg	021\20.jpg	S
008\22.jpg	008\07.jpg	S
020\06.jpg	020\01.jpg	S
017\16.jpg	017\06.jpg	S
024\07.jpg	024\00.jpg	S
021\19.jpg	021\20.jpg	S
023\23.jpg	023\04.jpg	S
011\25.jpg	011\30.jpg	S
013\05.jpg	013\10.jpg	S
009\20.jpg	009\05.jpg	S
010\02.jpg	010\13.jpg	S
022\02.jpg	022\19.jpg	S
024\02.jpg	024\00.jpg	S
001\08.jpg	001\25.jpg	S
003\15.jpg	003\18.jpg	S
017\19.jpg	017\08.jpg	S
005\21.jpg	005\14.jpg	S
015\19.jpg	015\08.jpg	S
021\01.jpg	021\08.jpg	S
021\03.jpg	021\01.jpg	S
003\03.jpg	003\18.jpg	S
015\00.jpg	015\07.jpg	S
017\26.jpg	017\08.jpg	S
012\18.jpg	012\20.jpg	S
025\09.jpg	025\26.jpg	S
020\20.jpg	020\23.jpg	S
017\23.jpg	017\22.jpg	S
021\22.jpg	021\05.jpg	S
002\16.jpg	002\13.jpg	S
009\07.jpg	009\23.jpg	S
012\15.jpg	012\08.jpg	S
026\10.jpg	026\08.jpg	S
022\16.jpg	022\12.jpg	S
010\08.jpg	010\02.jpg	S
015\05.jpg	015\18.jpg	S
018\11.jpg	018\00.jpg	S
005\18.jpg	005\05.jpg	S
004\04.jpg	004\13.jpg	S
026\06.jpg	026\20.jpg	S
008\13.jpg	008\17.jpg	S
026\03.jpg	026\00.jpg	S
023\05.jpg	023\20.jpg	S
002\15.jpg	002\13.jpg	S
011\14.jpg	011\07.jpg	S
011\22.jpg	011\17.jpg	S
029\03.jpg	029\07.jpg	S
013\16.jpg	013\11.jpg	S
005\00.jpg	005\18.jpg	S
005\12.jpg	005\14.jpg	S
025\10.jpg	025\09.jpg	S
022\12.jpg	022\01.jpg	S
002\14.jpg	002\17.jpg	S
016\33.jpg	016\10.jpg	S
027\33.jpg	027\01.jpg	S
004\11.jpg	004\13.jpg	S
000\09.jpg	000\15.jpg	S
029\19.jpg	029\24.jpg	S
000\22.jpg	000\21.jpg	S
018\04.jpg	018\13.jpg	S
018\07.jpg	018\00.jpg	S
013\04.jpg	013\21.jpg	S
023\11.jpg	023\01.jpg	S
019\02.jpg	019\26.jpg	S
002\13.jpg	002\20.jpg	S
014\27.jpg	014\01.jpg	S
002\16.jpg	002\06.jpg	S
007\15.jpg	007\07.jpg	S
005\03.jpg	005\23.jpg	S
025\14.jpg	025\02.jpg	S
010\13.jpg	010\10.jpg	S
029\13.jpg	029\02.jpg	S
009\18.jpg	009\09.jpg	S
000\24.jpg	000\05.jpg	S
001\26.jpg	001\09.jpg	S
008\21.jpg	008\23.jpg	S
001\29.jpg	001\04.jpg	S
004\16.jpg	004\12.jpg	S
017\07.jpg	017\20.jpg	S
028\00.jpg	028\04.jpg	S
002\10.jpg	002\06.jpg	S
001\16.jpg	001\09.jpg	S
016\10.jpg	016\07.jpg	S
017\06.jpg	017\13.jpg	S
012\02.jpg	012\15.jpg	S
006\25.jpg	006\17.jpg	S
016\17.jpg	016\10.jpg	S
018\20.jpg	018\05.jpg	S
016\23.jpg	016\12.jpg	S
010\27.jpg	010\03.jpg	S
007\21.jpg	007\13.jpg	S
003\21.jpg	003\23.jpg	S
008\21.jpg	008\20.jpg	S
001\13.jpg	001\22.jpg	S
018\07.jpg	018\08.jpg	S
014\27.jpg	014\23.jpg	S
004\06.jpg	004\16.jpg	S
000\01.jpg	000\10.jpg	S
014\16.jpg	014\23.jpg	S
022\10.jpg	022\13.jpg	S
015\02.jpg	015\06.jpg	S
013\06.jpg	013\17.jpg	S
019\21.jpg	019\02.jpg	S
016\34.jpg	016\12.jpg	S
014\16.jpg	014\04.jpg	S
025\23.jpg	025\11.jpg	S
011\17.jpg	011\16.jpg	S
003\08.jpg	003\14.jpg	S
001\15.jpg	001\08.jpg	S
008\10.jpg	008\12.jpg	S
006\15.jpg	006\16.jpg	S
024\21.jpg	024\11.jpg	S
025\20.jpg	025\07.jpg	S
025\26.jpg	025\11.jpg	S
000\08.jpg	000\13.jpg	S
009\07.jpg	009\20.jpg	S
013\15.jpg	013\07.jpg	S
016\32.jpg	016\17.jpg	S
012\06.jpg	012\19.jpg	S
019\25.jpg	019\19.jpg	S
029\21.jpg	029\10.jpg	S
016\04.jpg	016\02.jpg	S
013\18.jpg	013\13.jpg	S
029\15.jpg	029\07.jpg	S
006\15.jpg	006\04.jpg	S
004\07.jpg	004\05.jpg	S
011\28.jpg	011\20.jpg	S
027\16.jpg	027\24.jpg	S
005\00.jpg	005\21.jpg	S
022\23.jpg	022\15.jpg	S
014\13.jpg	014\19.jpg	S
017\10.jpg	017\24.jpg	S
003\01.jpg	003\22.jpg	S
020\19.jpg	020\13.jpg	S
021\19.jpg	021\03.jpg	S
029\24.jpg	029\19.jpg	S
007\08.jpg	007\23.jpg	S
021\19.jpg	021\16.jpg	S
005\22.jpg	005\04.jpg	S
026\07.jpg	026\10.jpg	S
009\20.jpg	009\24.jpg	S
023\06.jpg	023\01.jpg	S
018\11.jpg	018\21.jpg	S
023\09.jpg	023\08.jpg	S
015\12.jpg	015\01.jpg	S
004\26.jpg	004\08.jpg	S
007\23.jpg	007\14.jpg	S
003\22.jpg	003\01.jpg	S
027\20.jpg	027\36.jpg	S
003\09.jpg	003\22.jpg	S
015\21.jpg	015\19.jpg	S
017\19.jpg	017\23.jpg	S
014\07.jpg	014\19.jpg	S
016\08.jpg	016\04.jpg	S
027\04.jpg	027\08.jpg	S
028\09.jpg	028\25.jpg	S
001\27.jpg	001\08.jpg	S
008\12.jpg	008\14.jpg	S
024\07.jpg	024\06.jpg	S
020\06.jpg	020\11.jpg	S
001\04.jpg	001\15.jpg	S
025\03.jpg	025\20.jpg	S
007\06.jpg	007\16.jpg	S
029\18.jpg	029\10.jpg	S
007\22.jpg	007\04.jpg	S
000\24.jpg	000\09.jpg	S
013\07.jpg	013\04.jpg	S
024\03.jpg	024\04.jpg	S
014\29.jpg	014\28.jpg	S
027\12.jpg	027\20.jpg	S
013\11.jpg	007\22.jpg	D
010\00.jpg	011\15.jpg	D
002\05.jpg	014\03.jpg	D
000\02.jpg	001\23.jpg	D
028\26.jpg	021\18.jpg	D
015\01.jpg	027\26.jpg	D
002\15.jpg	004\20.jpg	D
011\17.jpg	001\18.jpg	D
027\11.jpg	010\12.jpg	D
012\05.jpg	018\23.jpg	D
006\04.jpg	010\06.jpg	D
010\26.jpg	002\11.jpg	D
009\13.jpg	002\22.jpg	D
023\24.jpg	029\11.jpg	D
001\19.jpg	015\05.jpg	D
027\35.jpg	021\11.jpg	D
005\18.jpg	014\03.jpg	D
027\23.jpg	009\18.jpg	D
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027\29.jpg	012\12.jpg	D
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014\19.jpg	004\06.jpg	D
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001\07.jpg	015\18.jpg	D
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010\07.jpg	009\23.jpg	D
008\09.jpg	016\06.jpg	D
014\25.jpg	027\33.jpg	D
011\00.jpg	013\09.jpg	D
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029\10.jpg	020\10.jpg	D
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005\02.jpg	001\06.jpg	D
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015\12.jpg	019\24.jpg	D
001\09.jpg	006\23.jpg	D
018\23.jpg	006\09.jpg	D
027\01.jpg	019\05.jpg	D
027\19.jpg	012\05.jpg	D
028\09.jpg	005\12.jpg	D
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013\00.jpg	017\02.jpg	D
002\07.jpg	007\19.jpg	D
008\07.jpg	016\14.jpg	D
017\09.jpg	009\19.jpg	D
014\12.jpg	029\04.jpg	D
002\07.jpg	005\18.jpg	D
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023\02.jpg	018\09.jpg	D
025\01.jpg	008\06.jpg	D
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003\17.jpg	009\01.jpg	D
005\17.jpg	021\09.jpg	D
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020\03.jpg	017\24.jpg	D
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006\05.jpg	007\17.jpg	D
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002\07.jpg	010\16.jpg	D
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016\25.jpg	020\03.jpg	D
013\05.jpg	011\24.jpg	D
001\19.jpg	013\03.jpg	D
010\16.jpg	025\00.jpg	D
000\27.jpg	026\15.jpg	D
001\13.jpg	002\01.jpg	D
003\12.jpg	029\20.jpg	D
000\08.jpg	029\15.jpg	D
016\33.jpg	012\24.jpg	D
011\26.jpg	027\18.jpg	D
018\02.jpg	023\01.jpg	D
014\28.jpg	008\03.jpg	D
013\13.jpg	021\13.jpg	D
011\17.jpg	028\11.jpg	D
028\13.jpg	023\00.jpg	D
000\28.jpg	020\19.jpg	D
005\01.jpg	012\30.jpg	D
023\02.jpg	013\18.jpg	D
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003\05.jpg	017\25.jpg	D
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006\11.jpg	026\00.jpg	D
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004\03.jpg	006\15.jpg	D
012\22.jpg	000\03.jpg	D
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027\19.jpg	000\08.jpg	D
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014\05.jpg	025\05.jpg	D
027\36.jpg	023\17.jpg	D
007\08.jpg	021\09.jpg	D
024\09.jpg	029\14.jpg	D
024\21.jpg	002\03.jpg	D
008\18.jpg	022\04.jpg	D
000\10.jpg	015\21.jpg	D
008\18.jpg	017\21.jpg	D
005\06.jpg	029\12.jpg	D
027\34.jpg	003\02.jpg	D
022\10.jpg	018\16.jpg	D
019\21.jpg	002\21.jpg	D
022\17.jpg	005\03.jpg	D
007\15.jpg	001\21.jpg	D
015\22.jpg	011\01.jpg	D
018\09.jpg	023\17.jpg	D
013\11.jpg	006\02.jpg	D
014\18.jpg	019\07.jpg	D
009\03.jpg	019\20.jpg	D
028\22.jpg	015\23.jpg	D
003\15.jpg	029\00.jpg	D
017\15.jpg	028\02.jpg	D
021\05.jpg	028\13.jpg	D
014\05.jpg	023\03.jpg	D
011\10.jpg	001\28.jpg	D
013\04.jpg	002\13.jpg	D
000\04.jpg	021\12.jpg	D
019\19.jpg	001\01.jpg	D
001\25.jpg	024\20.jpg	D
012\27.jpg	026\19.jpg	D
024\17.jpg	016\23.jpg	D
029\23.jpg	008\02.jpg	D
028\08.jpg	000\11.jpg	D
021\05.jpg	024\05.jpg	D
012\20.jpg	023\13.jpg	D
010\10.jpg	002\17.jpg	D
013\11.jpg	028\09.jpg	D
027\20.jpg	025\12.jpg	D
020\06.jpg	012\16.jpg	D
027\04.jpg	023\25.jpg	D
015\23.jpg	017\04.jpg	D
013\20.jpg	012\18.jpg	D
012\20.jpg	024\09.jpg	D
017\06.jpg	023\17.jpg	D
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025\06.jpg	014\30.jpg	D
021\09.jpg	004\22.jpg	D
008\21.jpg	007\14.jpg	D
019\18.jpg	002\02.jpg	D
007\05.jpg	005\01.jpg	D


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FILE: UtilsAlign/__init__.py
================================================
from .database import AlignDatabase
from .bbox import GetAlignFuncByBoundingBox
from .landmarks import GetAlignFuncByLandmarks, GetLargestLandmark, GetLandmarks
from .common import Inputs2ArrayImage

================================================
FILE: UtilsAlign/base/__init__.py
================================================


================================================
FILE: UtilsAlign/base/detect.py
================================================
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from six import string_types, iteritems

import numpy as np
import tensorflow as tf
import cv2
import os

def layer(op):
    '''Decorator for composable network layers.'''

    def layer_decorated(self, *args, **kwargs):
        # Automatically set a name if not provided.
        name = kwargs.setdefault('name', self.get_unique_name(op.__name__))
        # Figure out the layer inputs.
        if len(self.terminals) == 0:
            raise RuntimeError('No input variables found for layer %s.' % name)
        elif len(self.terminals) == 1:
            layer_input = self.terminals[0]
        else:
            layer_input = list(self.terminals)
        # Perform the operation and get the output.
        layer_output = op(self, layer_input, *args, **kwargs)
        # Add to layer LUT.
        self.layers[name] = layer_output
        # This output is now the input for the next layer.
        self.feed(layer_output)
        # Return self for chained calls.
        return self

    return layer_decorated

class Network(object):

    def __init__(self, inputs, trainable=True):
        # The input nodes for this network
        self.inputs = inputs
        # The current list of terminal nodes
        self.terminals = []
        # Mapping from layer names to layers
        self.layers = dict(inputs)
        # If true, the resulting variables are set as trainable
        self.trainable = trainable
        self.setup()

    def setup(self):
        '''Construct the network. '''
        raise NotImplementedError('Must be implemented by the subclass.')

    def load(self, data_path, session, ignore_missing=False):
        '''Load network weights.
        data_path: The path to the numpy-serialized network weights
        session: The current TensorFlow session
        ignore_missing: If true, serialized weights for missing layers are ignored.
        '''
        data_dict = np.load(data_path, encoding='latin1').item() #pylint: disable=no-member

        for op_name in data_dict:
            with tf.variable_scope(op_name, reuse=True):
                for param_name, data in iteritems(data_dict[op_name]):
                    try:
                        var = tf.get_variable(param_name)
                        session.run(var.assign(data))
                    except ValueError:
                        if not ignore_missing:
                            raise

    def feed(self, *args):
        '''Set the input(s) for the next operation by replacing the terminal nodes.
        The arguments can be either layer names or the actual layers.
        '''
        assert len(args) != 0
        self.terminals = []
        for fed_layer in args:
            if isinstance(fed_layer, string_types):
                try:
                    fed_layer = self.layers[fed_layer]
                except KeyError:
                    raise KeyError('Unknown layer name fed: %s' % fed_layer)
            self.terminals.append(fed_layer)
        return self

    def get_output(self):
        '''Returns the current network output.'''
        return self.terminals[-1]

    def get_unique_name(self, prefix):
        '''Returns an index-suffixed unique name for the given prefix.
        This is used for auto-generating layer names based on the type-prefix.
        '''
        ident = sum(t.startswith(prefix) for t, _ in self.layers.items()) + 1
        return '%s_%d' % (prefix, ident)

    def make_var(self, name, shape):
        '''Creates a new TensorFlow variable.'''
        return tf.get_variable(name, shape, trainable=self.trainable)

    def validate_padding(self, padding):
        '''Verifies that the padding is one of the supported ones.'''
        assert padding in ('SAME', 'VALID')

    @layer
    def conv(self,
             inp,
             k_h,
             k_w,
             c_o,
             s_h,
             s_w,
             name,
             relu=True,
             padding='SAME',
             group=1,
             biased=True):
        # Verify that the padding is acceptable
        self.validate_padding(padding)
        # Get the number of channels in the input
        c_i = int(inp.get_shape()[-1])
        # Verify that the grouping parameter is valid
        assert c_i % group == 0
        assert c_o % group == 0
        # Convolution for a given input and kernel
        convolve = lambda i, k: tf.nn.conv2d(i, k, [1, s_h, s_w, 1], padding=padding)
        with tf.variable_scope(name) as scope:
            kernel = self.make_var('weights', shape=[k_h, k_w, c_i // group, c_o])
            # This is the common-case. Convolve the input without any further complications.
            output = convolve(inp, kernel)
            # Add the biases
            if biased:
                biases = self.make_var('biases', [c_o])
                output = tf.nn.bias_add(output, biases)
            if relu:
                # ReLU non-linearity
                output = tf.nn.relu(output, name=scope.name)
            return output

    @layer
    def prelu(self, inp, name):
        with tf.variable_scope(name):
            i = int(inp.get_shape()[-1])
            alpha = self.make_var('alpha', shape=(i,))
            output = tf.nn.relu(inp) + tf.multiply(alpha, -tf.nn.relu(-inp))
        return output

    @layer
    def max_pool(self, inp, k_h, k_w, s_h, s_w, name, padding='SAME'):
        self.validate_padding(padding)
        return tf.nn.max_pool(inp,
                              ksize=[1, k_h, k_w, 1],
                              strides=[1, s_h, s_w, 1],
                              padding=padding,
                              name=name)

    @layer
    def fc(self, inp, num_out, name, relu=True):
        with tf.variable_scope(name):
            input_shape = inp.get_shape()
            if input_shape.ndims == 4:
                # The input is spatial. Vectorize it first.
                dim = 1
                for d in input_shape[1:].as_list():
                    dim *= int(d)
                feed_in = tf.reshape(inp, [-1, dim])
            else:
                feed_in, dim = (inp, input_shape[-1].value)
            weights = self.make_var('weights', shape=[dim, num_out])
            biases = self.make_var('biases', [num_out])
            op = tf.nn.relu_layer if relu else tf.nn.xw_plus_b
            fc = op(feed_in, weights, biases, name=name)
            return fc


    """
    Multi dimensional softmax,
    refer to https://github.com/tensorflow/tensorflow/issues/210
    compute softmax along the dimension of target
    the native softmax only supports batch_size x dimension
    """
    @layer
    def softmax(self, target, axis, name=None):
        max_axis = tf.reduce_max(target, axis, keep_dims=True)
        target_exp = tf.exp(target-max_axis)
        normalize = tf.reduce_sum(target_exp, axis, keep_dims=True)
        softmax = tf.div(target_exp, normalize, name)
        return softmax
    
class PNet(Network):
    def setup(self):
        (self.feed('data') #pylint: disable=no-value-for-parameter, no-member
             .conv(3, 3, 10, 1, 1, padding='VALID', relu=False, name='conv1')
             .prelu(name='PReLU1')
             .max_pool(2, 2, 2, 2, name='pool1')
             .conv(3, 3, 16, 1, 1, padding='VALID', relu=False, name='conv2')
             .prelu(name='PReLU2')
             .conv(3, 3, 32, 1, 1, padding='VALID', relu=False, name='conv3')
             .prelu(name='PReLU3')
             .conv(1, 1, 2, 1, 1, relu=False, name='conv4-1')
             .softmax(3,name='prob1'))

        (self.feed('PReLU3') #pylint: disable=no-value-for-parameter
             .conv(1, 1, 4, 1, 1, relu=False, name='conv4-2'))
        
class RNet(Network):
    def setup(self):
        (self.feed('data') #pylint: disable=no-value-for-parameter, no-member
             .conv(3, 3, 28, 1, 1, padding='VALID', relu=False, name='conv1')
             .prelu(name='prelu1')
             .max_pool(3, 3, 2, 2, name='pool1')
             .conv(3, 3, 48, 1, 1, padding='VALID', relu=False, name='conv2')
             .prelu(name='prelu2')
             .max_pool(3, 3, 2, 2, padding='VALID', name='pool2')
             .conv(2, 2, 64, 1, 1, padding='VALID', relu=False, name='conv3')
             .prelu(name='prelu3')
             .fc(128, relu=False, name='conv4')
             .prelu(name='prelu4')
             .fc(2, relu=False, name='conv5-1')
             .softmax(1,name='prob1'))

        (self.feed('prelu4') #pylint: disable=no-value-for-parameter
             .fc(4, relu=False, name='conv5-2'))

class ONet(Network):
    def setup(self):
        (self.feed('data') #pylint: disable=no-value-for-parameter, no-member
             .conv(3, 3, 32, 1, 1, padding='VALID', relu=False, name='conv1')
             .prelu(name='prelu1')
             .max_pool(3, 3, 2, 2, name='pool1')
             .conv(3, 3, 64, 1, 1, padding='VALID', relu=False, name='conv2')
             .prelu(name='prelu2')
             .max_pool(3, 3, 2, 2, padding='VALID', name='pool2')
             .conv(3, 3, 64, 1, 1, padding='VALID', relu=False, name='conv3')
             .prelu(name='prelu3')
             .max_pool(2, 2, 2, 2, name='pool3')
             .conv(2, 2, 128, 1, 1, padding='VALID', relu=False, name='conv4')
             .prelu(name='prelu4')
             .fc(256, relu=False, name='conv5')
             .prelu(name='prelu5')
             .fc(2, relu=False, name='conv6-1')
             .softmax(1, name='prob1'))

        (self.feed('prelu5') #pylint: disable=no-value-for-parameter
             .fc(4, relu=False, name='conv6-2'))

        (self.feed('prelu5') #pylint: disable=no-value-for-parameter
             .fc(10, relu=False, name='conv6-3'))

def create_mtcnn(sess, model_path):
    if not model_path:
        model_path,_ = os.path.split(os.path.realpath(__file__))

    with tf.variable_scope('pnet'):
        data = tf.placeholder(tf.float32, (None,None,None,3), 'input')
        pnet = PNet({'data':data})
        pnet.load(os.path.join(model_path, 'det1.npy'), sess)
    with tf.variable_scope('rnet'):
        data = tf.placeholder(tf.float32, (None,24,24,3), 'input')
        rnet = RNet({'data':data})
        rnet.load(os.path.join(model_path, 'det2.npy'), sess)
    with tf.variable_scope('onet'):
        data = tf.placeholder(tf.float32, (None,48,48,3), 'input')
        onet = ONet({'data':data})
        onet.load(os.path.join(model_path, 'det3.npy'), sess)
        
    pnet_fun = lambda img : sess.run(('pnet/conv4-2/BiasAdd:0', 'pnet/prob1:0'), feed_dict={'pnet/input:0':img})
    rnet_fun = lambda img : sess.run(('rnet/conv5-2/conv5-2:0', 'rnet/prob1:0'), feed_dict={'rnet/input:0':img})
    onet_fun = lambda img : sess.run(('onet/conv6-2/conv6-2:0', 'onet/conv6-3/conv6-3:0', 'onet/prob1:0'), feed_dict={'onet/input:0':img})
    return pnet_fun, rnet_fun, onet_fun

def detect_face(img, minsize, pnet, rnet, onet, threshold, factor):
    # im: input image
    # minsize: minimum of faces' size
    # pnet, rnet, onet: caffemodel
    # threshold: threshold=[th1 th2 th3], th1-3 are three steps's threshold
    # fastresize: resize img from last scale (using in high-resolution images) if fastresize==true
    factor_count=0
    total_boxes=np.empty((0,9))
    points=np.empty(0)
    h=img.shape[0]
    w=img.shape[1]
    minl=np.amin([h, w])
    m=12.0/minsize
    minl=minl*m
    # creat scale pyramid
    scales=[]
    while minl>=12:
        scales += [m*np.power(factor, factor_count)]
        minl = minl*factor
        factor_count += 1

    # first stage
    for j in range(len(scales)):
        scale=scales[j]
        hs=int(np.ceil(h*scale))
        ws=int(np.ceil(w*scale))
        im_data = imresample(img, (hs, ws))
        im_data = (im_data-127.5)*0.0078125
        img_x = np.expand_dims(im_data, 0)
        img_y = np.transpose(img_x, (0,2,1,3))
        out = pnet(img_y)
        out0 = np.transpose(out[0], (0,2,1,3))
        out1 = np.transpose(out[1], (0,2,1,3))
        
        boxes, _ = generateBoundingBox(out1[0,:,:,1].copy(), out0[0,:,:,:].copy(), scale, threshold[0])
        
        # inter-scale nms
        pick = nms(boxes.copy(), 0.5, 'Union')
        if boxes.size>0 and pick.size>0:
            boxes = boxes[pick,:]
            total_boxes = np.append(total_boxes, boxes, axis=0)

    numbox = total_boxes.shape[0]
    if numbox>0:
        pick = nms(total_boxes.copy(), 0.7, 'Union')
        total_boxes = total_boxes[pick,:]
        regw = total_boxes[:,2]-total_boxes[:,0]
        regh = total_boxes[:,3]-total_boxes[:,1]
        qq1 = total_boxes[:,0]+total_boxes[:,5]*regw
        qq2 = total_boxes[:,1]+total_boxes[:,6]*regh
        qq3 = total_boxes[:,2]+total_boxes[:,7]*regw
        qq4 = total_boxes[:,3]+total_boxes[:,8]*regh
        total_boxes = np.transpose(np.vstack([qq1, qq2, qq3, qq4, total_boxes[:,4]]))
        total_boxes = rerec(total_boxes.copy())
        total_boxes[:,0:4] = np.fix(total_boxes[:,0:4]).astype(np.int32)
        dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(total_boxes.copy(), w, h)

    numbox = total_boxes.shape[0]
    if numbox>0:
        # second stage
        tempimg = np.zeros((24,24,3,numbox))
        for k in range(0,numbox):
            tmp = np.zeros((int(tmph[k]),int(tmpw[k]),3))
            tmp[dy[k]-1:edy[k],dx[k]-1:edx[k],:] = img[y[k]-1:ey[k],x[k]-1:ex[k],:]
            if tmp.shape[0]>0 and tmp.shape[1]>0 or tmp.shape[0]==0 and tmp.shape[1]==0:
                tempimg[:,:,:,k] = imresample(tmp, (24, 24))
            else:
                return np.empty()
        tempimg = (tempimg-127.5)*0.0078125
        tempimg1 = np.transpose(tempimg, (3,1,0,2))
        out = rnet(tempimg1)
        out0 = np.transpose(out[0])
        out1 = np.transpose(out[1])
        score = out1[1,:]
        ipass = np.where(score>threshold[1])
        total_boxes = np.hstack([total_boxes[ipass[0],0:4].copy(), np.expand_dims(score[ipass].copy(),1)])
        mv = out0[:,ipass[0]]
        if total_boxes.shape[0]>0:
            pick = nms(total_boxes, 0.7, 'Union')
            total_boxes = total_boxes[pick,:]
            total_boxes = bbreg(total_boxes.copy(), np.transpose(mv[:,pick]))
            total_boxes = rerec(total_boxes.copy())

    numbox = total_boxes.shape[0]
    if numbox>0:
        # third stage
        total_boxes = np.fix(total_boxes).astype(np.int32)
        dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(total_boxes.copy(), w, h)
        tempimg = np.zeros((48,48,3,numbox))
        for k in range(0,numbox):
            tmp = np.zeros((int(tmph[k]),int(tmpw[k]),3))
            tmp[dy[k]-1:edy[k],dx[k]-1:edx[k],:] = img[y[k]-1:ey[k],x[k]-1:ex[k],:]
            if tmp.shape[0]>0 and tmp.shape[1]>0 or tmp.shape[0]==0 and tmp.shape[1]==0:
                tempimg[:,:,:,k] = imresample(tmp, (48, 48))
            else:
                return np.empty()
        tempimg = (tempimg-127.5)*0.0078125
        tempimg1 = np.transpose(tempimg, (3,1,0,2))
        out = onet(tempimg1)
        out0 = np.transpose(out[0])
        out1 = np.transpose(out[1])
        out2 = np.transpose(out[2])
        score = out2[1,:]
        points = out1
        ipass = np.where(score>threshold[2])
        points = points[:,ipass[0]]
        total_boxes = np.hstack([total_boxes[ipass[0],0:4].copy(), np.expand_dims(score[ipass].copy(),1)])
        mv = out0[:,ipass[0]]

        w = total_boxes[:,2]-total_boxes[:,0]+1
        h = total_boxes[:,3]-total_boxes[:,1]+1
        points[0:5,:] = np.tile(w,(5, 1))*points[0:5,:] + np.tile(total_boxes[:,0],(5, 1))-1
        points[5:10,:] = np.tile(h,(5, 1))*points[5:10,:] + np.tile(total_boxes[:,1],(5, 1))-1
        if total_boxes.shape[0]>0:
            total_boxes = bbreg(total_boxes.copy(), np.transpose(mv))
            pick = nms(total_boxes.copy(), 0.7, 'Min')
            total_boxes = total_boxes[pick,:]
            points = points[:,pick]
                
    return total_boxes, points


def bulk_detect_face(images, detection_window_size_ratio, pnet, rnet, onet, threshold, factor):
    # im: input image
    # minsize: minimum of faces' size
    # pnet, rnet, onet: caffemodel
    # threshold: threshold=[th1 th2 th3], th1-3 are three steps's threshold [0-1]

    all_scales = [None] * len(images)
    images_with_boxes = [None] * len(images)

    for i in range(len(images)):
        images_with_boxes[i] = {'total_boxes': np.empty((0, 9))}

    # create scale pyramid
    for index, img in enumerate(images):
        all_scales[index] = []
        h = img.shape[0]
        w = img.shape[1]
        minsize = int(detection_window_size_ratio * np.minimum(w, h))
        factor_count = 0
        minl = np.amin([h, w])
        if minsize <= 12:
            minsize = 12

        m = 12.0 / minsize
        minl = minl * m
        while minl >= 12:
            all_scales[index].append(m * np.power(factor, factor_count))
            minl = minl * factor
            factor_count += 1

    # # # # # # # # # # # # #
    # first stage - fast proposal network (pnet) to obtain face candidates
    # # # # # # # # # # # # #

    images_obj_per_resolution = {}

    # TODO: use some type of rounding to number module 8 to increase probability that pyramid images will have the same resolution across input images

    for index, scales in enumerate(all_scales):
        h = images[index].shape[0]
        w = images[index].shape[1]

        for scale in scales:
            hs = int(np.ceil(h * scale))
            ws = int(np.ceil(w * scale))

            if (ws, hs) not in images_obj_per_resolution:
                images_obj_per_resolution[(ws, hs)] = []

            im_data = imresample(images[index], (hs, ws))
            im_data = (im_data - 127.5) * 0.0078125
            img_y = np.transpose(im_data, (1, 0, 2))  # caffe uses different dimensions ordering
            images_obj_per_resolution[(ws, hs)].append({'scale': scale, 'image': img_y, 'index': index})

    for resolution in images_obj_per_resolution:
        images_per_resolution = [i['image'] for i in images_obj_per_resolution[resolution]]
        outs = pnet(images_per_resolution)

        for index in range(len(outs[0])):
            scale = images_obj_per_resolution[resolution][index]['scale']
            image_index = images_obj_per_resolution[resolution][index]['index']
            out0 = np.transpose(outs[0][index], (1, 0, 2))
            out1 = np.transpose(outs[1][index], (1, 0, 2))

            boxes, _ = generateBoundingBox(out1[:, :, 1].copy(), out0[:, :, :].copy(), scale, threshold[0])

            # inter-scale nms
            pick = nms(boxes.copy(), 0.5, 'Union')
            if boxes.size > 0 and pick.size > 0:
                boxes = boxes[pick, :]
                images_with_boxes[image_index]['total_boxes'] = np.append(images_with_boxes[image_index]['total_boxes'],
                                                                          boxes,
                                                                          axis=0)

    for index, image_obj in enumerate(images_with_boxes):
        numbox = image_obj['total_boxes'].shape[0]
        if numbox > 0:
            h = images[index].shape[0]
            w = images[index].shape[1]
            pick = nms(image_obj['total_boxes'].copy(), 0.7, 'Union')
            image_obj['total_boxes'] = image_obj['total_boxes'][pick, :]
            regw = image_obj['total_boxes'][:, 2] - image_obj['total_boxes'][:, 0]
            regh = image_obj['total_boxes'][:, 3] - image_obj['total_boxes'][:, 1]
            qq1 = image_obj['total_boxes'][:, 0] + image_obj['total_boxes'][:, 5] * regw
            qq2 = image_obj['total_boxes'][:, 1] + image_obj['total_boxes'][:, 6] * regh
            qq3 = image_obj['total_boxes'][:, 2] + image_obj['total_boxes'][:, 7] * regw
            qq4 = image_obj['total_boxes'][:, 3] + image_obj['total_boxes'][:, 8] * regh
            image_obj['total_boxes'] = np.transpose(np.vstack([qq1, qq2, qq3, qq4, image_obj['total_boxes'][:, 4]]))
            image_obj['total_boxes'] = rerec(image_obj['total_boxes'].copy())
            image_obj['total_boxes'][:, 0:4] = np.fix(image_obj['total_boxes'][:, 0:4]).astype(np.int32)
            dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(image_obj['total_boxes'].copy(), w, h)

            numbox = image_obj['total_boxes'].shape[0]
            tempimg = np.zeros((24, 24, 3, numbox))

            if numbox > 0:
                for k in range(0, numbox):
                    tmp = np.zeros((int(tmph[k]), int(tmpw[k]), 3))
                    tmp[dy[k] - 1:edy[k], dx[k] - 1:edx[k], :] = images[index][y[k] - 1:ey[k], x[k] - 1:ex[k], :]
                    if tmp.shape[0] > 0 and tmp.shape[1] > 0 or tmp.shape[0] == 0 and tmp.shape[1] == 0:
                        tempimg[:, :, :, k] = imresample(tmp, (24, 24))
                    else:
                        return np.empty()

                tempimg = (tempimg - 127.5) * 0.0078125
                image_obj['rnet_input'] = np.transpose(tempimg, (3, 1, 0, 2))

    # # # # # # # # # # # # #
    # second stage - refinement of face candidates with rnet
    # # # # # # # # # # # # #

    bulk_rnet_input = np.empty((0, 24, 24, 3))
    for index, image_obj in enumerate(images_with_boxes):
        if 'rnet_input' in image_obj:
            bulk_rnet_input = np.append(bulk_rnet_input, image_obj['rnet_input'], axis=0)

    out = rnet(bulk_rnet_input)
    out0 = np.transpose(out[0])
    out1 = np.transpose(out[1])
    score = out1[1, :]

    i = 0
    for index, image_obj in enumerate(images_with_boxes):
        if 'rnet_input' not in image_obj:
            continue

        rnet_input_count = image_obj['rnet_input'].shape[0]
        score_per_image = score[i:i + rnet_input_count]
        out0_per_image = out0[:, i:i + rnet_input_count]

        ipass = np.where(score_per_image > threshold[1])
        image_obj['total_boxes'] = np.hstack([image_obj['total_boxes'][ipass[0], 0:4].copy(),
                                              np.expand_dims(score_per_image[ipass].copy(), 1)])

        mv = out0_per_image[:, ipass[0]]

        if image_obj['total_boxes'].shape[0] > 0:
            h = images[index].shape[0]
            w = images[index].shape[1]
            pick = nms(image_obj['total_boxes'], 0.7, 'Union')
            image_obj['total_boxes'] = image_obj['total_boxes'][pick, :]
            image_obj['total_boxes'] = bbreg(image_obj['total_boxes'].copy(), np.transpose(mv[:, pick]))
            image_obj['total_boxes'] = rerec(image_obj['total_boxes'].copy())

            numbox = image_obj['total_boxes'].shape[0]

            if numbox > 0:
                tempimg = np.zeros((48, 48, 3, numbox))
                image_obj['total_boxes'] = np.fix(image_obj['total_boxes']).astype(np.int32)
                dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph = pad(image_obj['total_boxes'].copy(), w, h)

                for k in range(0, numbox):
                    tmp = np.zeros((int(tmph[k]), int(tmpw[k]), 3))
                    tmp[dy[k] - 1:edy[k], dx[k] - 1:edx[k], :] = images[index][y[k] - 1:ey[k], x[k] - 1:ex[k], :]
                    if tmp.shape[0] > 0 and tmp.shape[1] > 0 or tmp.shape[0] == 0 and tmp.shape[1] == 0:
                        tempimg[:, :, :, k] = imresample(tmp, (48, 48))
                    else:
                        return np.empty()
                tempimg = (tempimg - 127.5) * 0.0078125
                image_obj['onet_input'] = np.transpose(tempimg, (3, 1, 0, 2))

        i += rnet_input_count

    # # # # # # # # # # # # #
    # third stage - further refinement and facial landmarks positions with onet
    # # # # # # # # # # # # #

    bulk_onet_input = np.empty((0, 48, 48, 3))
    for index, image_obj in enumerate(images_with_boxes):
        if 'onet_input' in image_obj:
            bulk_onet_input = np.append(bulk_onet_input, image_obj['onet_input'], axis=0)

    out = onet(bulk_onet_input)

    out0 = np.transpose(out[0])
    out1 = np.transpose(out[1])
    out2 = np.transpose(out[2])
    score = out2[1, :]
    points = out1

    i = 0
    ret = []
    for index, image_obj in enumerate(images_with_boxes):
        if 'onet_input' not in image_obj:
            ret.append(None)
            continue

        onet_input_count = image_obj['onet_input'].shape[0]

        out0_per_image = out0[:, i:i + onet_input_count]
        score_per_image = score[i:i + onet_input_count]
        points_per_image = points[:, i:i + onet_input_count]

        ipass = np.where(score_per_image > threshold[2])
        points_per_image = points_per_image[:, ipass[0]]

        image_obj['total_boxes'] = np.hstack([image_obj['total_boxes'][ipass[0], 0:4].copy(),
                                              np.expand_dims(score_per_image[ipass].copy(), 1)])
        mv = out0_per_image[:, ipass[0]]

        w = image_obj['total_boxes'][:, 2] - image_obj['total_boxes'][:, 0] + 1
        h = image_obj['total_boxes'][:, 3] - image_obj['total_boxes'][:, 1] + 1
        points_per_image[0:5, :] = np.tile(w, (5, 1)) * points_per_image[0:5, :] + np.tile(
            image_obj['total_boxes'][:, 0], (5, 1)) - 1
        points_per_image[5:10, :] = np.tile(h, (5, 1)) * points_per_image[5:10, :] + np.tile(
            image_obj['total_boxes'][:, 1], (5, 1)) - 1

        if image_obj['total_boxes'].shape[0] > 0:
            image_obj['total_boxes'] = bbreg(image_obj['total_boxes'].copy(), np.transpose(mv))
            pick = nms(image_obj['total_boxes'].copy(), 0.7, 'Min')
            image_obj['total_boxes'] = image_obj['total_boxes'][pick, :]
            points_per_image = points_per_image[:, pick]

            ret.append((image_obj['total_boxes'], points_per_image))
        else:
            ret.append(None)

        i += onet_input_count

    return ret


# function [boundingbox] = bbreg(boundingbox,reg)
def bbreg(boundingbox,reg):
    # calibrate bounding boxes
    if reg.shape[1]==1:
        reg = np.reshape(reg, (reg.shape[2], reg.shape[3]))

    w = boundingbox[:,2]-boundingbox[:,0]+1
    h = boundingbox[:,3]-boundingbox[:,1]+1
    b1 = boundingbox[:,0]+reg[:,0]*w
    b2 = boundingbox[:,1]+reg[:,1]*h
    b3 = boundingbox[:,2]+reg[:,2]*w
    b4 = boundingbox[:,3]+reg[:,3]*h
    boundingbox[:,0:4] = np.transpose(np.vstack([b1, b2, b3, b4 ]))
    return boundingbox
 
def generateBoundingBox(imap, reg, scale, t):
    # use heatmap to generate bounding boxes
    stride=2
    cellsize=12

    imap = np.transpose(imap)
    dx1 = np.transpose(reg[:,:,0])
    dy1 = np.transpose(reg[:,:,1])
    dx2 = np.transpose(reg[:,:,2])
    dy2 = np.transpose(reg[:,:,3])
    y, x = np.where(imap >= t)
    if y.shape[0]==1:
        dx1 = np.flipud(dx1)
        dy1 = np.flipud(dy1)
        dx2 = np.flipud(dx2)
        dy2 = np.flipud(dy2)
    score = imap[(y,x)]
    reg = np.transpose(np.vstack([ dx1[(y,x)], dy1[(y,x)], dx2[(y,x)], dy2[(y,x)] ]))
    if reg.size==0:
        reg = np.empty((0,3))
    bb = np.transpose(np.vstack([y,x]))
    q1 = np.fix((stride*bb+1)/scale)
    q2 = np.fix((stride*bb+cellsize-1+1)/scale)
    boundingbox = np.hstack([q1, q2, np.expand_dims(score,1), reg])
    return boundingbox, reg
 
# function pick = nms(boxes,threshold,type)
def nms(boxes, threshold, method):
    if boxes.size==0:
        return np.empty((0,3))
    x1 = boxes[:,0]
    y1 = boxes[:,1]
    x2 = boxes[:,2]
    y2 = boxes[:,3]
    s = boxes[:,4]
    area = (x2-x1+1) * (y2-y1+1)
    I = np.argsort(s)
    pick = np.zeros_like(s, dtype=np.int16)
    counter = 0
    while I.size>0:
        i = I[-1]
        pick[counter] = i
        counter += 1
        idx = I[0:-1]
        xx1 = np.maximum(x1[i], x1[idx])
        yy1 = np.maximum(y1[i], y1[idx])
        xx2 = np.minimum(x2[i], x2[idx])
        yy2 = np.minimum(y2[i], y2[idx])
        w = np.maximum(0.0, xx2-xx1+1)
        h = np.maximum(0.0, yy2-yy1+1)
        inter = w * h
        if method is 'Min':
            o = inter / np.minimum(area[i], area[idx])
        else:
            o = inter / (area[i] + area[idx] - inter)
        I = I[np.where(o<=threshold)]
    pick = pick[0:counter]
    return pick

# function [dy edy dx edx y ey x ex tmpw tmph] = pad(total_boxes,w,h)
def pad(total_boxes, w, h):
    # compute the padding coordinates (pad the bounding boxes to square)
    tmpw = (total_boxes[:,2]-total_boxes[:,0]+1).astype(np.int32)
    tmph = (total_boxes[:,3]-total_boxes[:,1]+1).astype(np.int32)
    numbox = total_boxes.shape[0]

    dx = np.ones((numbox), dtype=np.int32)
    dy = np.ones((numbox), dtype=np.int32)
    edx = tmpw.copy().astype(np.int32)
    edy = tmph.copy().astype(np.int32)

    x = total_boxes[:,0].copy().astype(np.int32)
    y = total_boxes[:,1].copy().astype(np.int32)
    ex = total_boxes[:,2].copy().astype(np.int32)
    ey = total_boxes[:,3].copy().astype(np.int32)

    tmp = np.where(ex>w)
    edx.flat[tmp] = np.expand_dims(-ex[tmp]+w+tmpw[tmp],1)
    ex[tmp] = w
    
    tmp = np.where(ey>h)
    edy.flat[tmp] = np.expand_dims(-ey[tmp]+h+tmph[tmp],1)
    ey[tmp] = h

    tmp = np.where(x<1)
    dx.flat[tmp] = np.expand_dims(2-x[tmp],1)
    x[tmp] = 1

    tmp = np.where(y<1)
    dy.flat[tmp] = np.expand_dims(2-y[tmp],1)
    y[tmp] = 1
    
    return dy, edy, dx, edx, y, ey, x, ex, tmpw, tmph

# function [bboxA] = rerec(bboxA)
def rerec(bboxA):
    # convert bboxA to square
    h = bboxA[:,3]-bboxA[:,1]
    w = bboxA[:,2]-bboxA[:,0]
    l = np.maximum(w, h)
    bboxA[:,0] = bboxA[:,0]+w*0.5-l*0.5
    bboxA[:,1] = bboxA[:,1]+h*0.5-l*0.5
    bboxA[:,2:4] = bboxA[:,0:2] + np.transpose(np.tile(l,(2,1)))
    return bboxA

def imresample(img, sz):
    im_data = cv2.resize(img, (sz[1], sz[0]), interpolation=cv2.INTER_AREA) #@UndefinedVariable
    return im_data

    # This method is kept for debugging purpose
#     h=img.shape[0]
#     w=img.shape[1]
#     hs, ws = sz
#     dx = float(w) / ws
#     dy = float(h) / hs
#     im_data = np.zeros((hs,ws,3))
#     for a1 in range(0,hs):
#         for a2 in range(0,ws):
#             for a3 in range(0,3):
#                 im_data[a1,a2,a3] = img[int(floor(a1*dy)),int(floor(a2*dx)),a3]
#     return im_data



================================================
FILE: UtilsAlign/bbox.py
================================================
import tensorflow as tf
import numpy as np
from scipy import misc
from .base import detect
from .common import Inputs2ArrayImage, SelectLargest

def _LoadAndAlign(input, pnet, rnet, onet, image_size, margin):
    minsize = 20 # minimum size of face
    threshold = [ 0.6, 0.7, 0.7 ]  # three steps's threshold
    factor = 0.709 # scale factor
    img = Inputs2ArrayImage(input)
    img_size = np.asarray(img.shape)[0:2]
    bounding_boxes, _ = detect.detect_face(img, minsize, pnet, rnet, onet, threshold, factor)
    num_faces = bounding_boxes.shape[0]
    if num_faces == 0:
        print('Unable to align')
        return
    #det = bounding_boxes[0]
    idx = SelectLargest(bounding_boxes, img_size)
    det = bounding_boxes[idx, 0:4]
    bb = np.zeros(4, dtype=np.int32)
    bb[0] = np.maximum(det[0]-margin/2, 0)
    bb[1] = np.maximum(det[1]-margin/2, 0)
    bb[2] = np.minimum(det[2]+margin/2, img_size[1])
    bb[3] = np.minimum(det[3]+margin/2, img_size[0])
    cropped = img[bb[1]:bb[3],bb[0]:bb[2],:]
    aligned_images = misc.imresize(cropped, (image_size, image_size), interp='bilinear')
    return  aligned_images

def GetAlignFuncByBoundingBox(output_size=160, margin=44):
    with tf.Graph().as_default():
        gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=1.0)
        sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options, log_device_placement=False))
        with sess.as_default():
            pnet, rnet, onet = detect.create_mtcnn(sess, None)
    return lambda input : _LoadAndAlign(input, pnet, rnet, onet, output_size, margin)
    



================================================
FILE: UtilsAlign/common.py
================================================
import numpy as np
from sklearn.metrics import pairwise as kernels
import os
from PIL import Image

STRATEGY_ALL = 0
STRATEGY_LARGEST = 1
STRATEGY_CLOSE_TO_CENTER = 2
STRATEGY_PROBABILITY = 3

def SelectLargest(bounding_boxes, img_size, strategy=STRATEGY_ALL):
    assert bounding_boxes.shape[1] ==5
    boxes = bounding_boxes[:,0:4]

    if strategy == STRATEGY_LARGEST or strategy == STRATEGY_ALL:
        areas = (boxes[:,2]-boxes[:,0])*(boxes[:,3]-boxes[:,1])
        scores_area = areas/(np.sum(areas))

    if strategy == STRATEGY_PROBABILITY or strategy == STRATEGY_ALL:
        probabilities = bounding_boxes[:,-1]
        scores_prob = probabilities/(np.sum(probabilities))

    if strategy == STRATEGY_CLOSE_TO_CENTER or strategy == STRATEGY_ALL:
        center_img = (img_size/2).reshape(1, -1)
        normalized_center_img = center_img / img_size
        center_boxes = np.vstack([(boxes[:,0]+boxes[:,2])/2, (boxes[:,1]+boxes[:,3])/2]).T
        normalized_center_boxes = center_boxes / img_size
        similarities = kernels.rbf_kernel(X=normalized_center_boxes, Y=normalized_center_img, gamma=5).reshape(-1)
        scores_dist = similarities/(np.sum(similarities))

    if strategy == STRATEGY_LARGEST:
        final_scores = scores_area
    if strategy == STRATEGY_PROBABILITY:
        final_scores = scores_prob
    if strategy == STRATEGY_CLOSE_TO_CENTER:
        final_scores = scores_dist
    if strategy == STRATEGY_ALL:
        final_scores = np.log(scores_area) + np.log(scores_prob) + np.log(scores_dist)
    
    larggest_idx = final_scores.argmax()
    return larggest_idx

'''
convert an input to PIL image or numpy array image
inputs could be (1)string (2)PIL Image (3) numpy array image
'''    
def Inputs2ArrayImage(inputs, output_type=np.ndarray, dtype='uint8', size=None):
    assert output_type in [np.ndarray, Image.Image]

    img = None
    if isinstance(inputs, str): # input is a path
        img = Image.open(os.path.expanduser(inputs))
    elif isinstance(inputs, Image.Image): # input is a PIL image
        pass
    elif isinstance(inputs, np.ndarray): # input is a numpy array
        img = Image.fromarray(np.uint8(inputs))
    else:
        msg = 'unexpected type of input! '
        msg += 'expect str, PIL or ndarray image, '
        msg += 'but got {}'
        raise TypeError(msg.format(type(inputs)))
        
    if size is not None:
        img = img.resize((size, size))
        
    if output_type==np.ndarray:
        img = np.array(img).astype(dtype)
        if len(img.shape)==2:
            img = _Gray2RGB(img)
        
    return img
    
'''
def Inputs2ArrayImage(inputs):
    img = None
    if isinstance(inputs, str): # input is a path
        img = Image.open(os.path.expanduser(inputs))
        img = np.array(img)
        # img = misc.imread(os.path.expanduser(input))
    elif isinstance(inputs, Image.Image): # input is a PIL image
        img = np.array(inputs)
    elif isinstance(inputs, (np.ndarray, np.generic)): # input is a numpy array
        img = inputs.astype('uint8')
    else:
        msg = 'unexpected type of input! '
        msg += 'expect str, PIL or ndarray image, '
        msg += 'but got {}'
        raise TypeError(msg.format(type(inputs)))
        
    if len(img.shape)==2:
        img = _Gray2RGB(img)
        
    return img
'''
    
def _Gray2RGB(img):
    assert len(img.shape)==2
    R = np.expand_dims(img, axis=-1)
    G = np.expand_dims(img, axis=-1)
    B = np.expand_dims(img, axis=-1)
    return np.concatenate([R,G,B],axis=-1)

    
    

================================================
FILE: UtilsAlign/database.py
================================================
import os
from scipy import misc

#for each img in folder_source, align it and store the aligned img in folder_target
def _AlignFolder(folder_source, folder_target, align_func):
    unable = []
    for item in os.listdir(folder_source):
        input_path = os.path.join(folder_source, item)
        cond1 = os.path.isfile(input_path)
        cond2 = input_path.find('.jpeg') != (-1) or input_path.find('.jpg') != (-1) or input_path.find('.bmp') != (-1) or input_path.find('.tif') != (-1)
        if not cond1 or not cond2:
            continue
        img = align_func(input_path)
        if img is None:
            unable.append(input_path)
            continue
        if not os.path.exists(folder_target):
            os.makedirs(folder_target)
        output_path = os.path.join(folder_target, item)
        misc.imsave(output_path, img)
    return unable
    
'''
return value is a list containing all imgs that are not able to align
source is a image folder, which should have structure similar to the following:
Aaron_Eckhart
    Aaron_Eckhart_0001.jpg

Aaron_Guiel
    Aaron_Guiel_0001.jpg

Aaron_Patterson
    Aaron_Patterson_0001.jpg

Aaron_Peirsol
    Aaron_Peirsol_0001.jpg
    Aaron_Peirsol_0002.jpg
    Aaron_Peirsol_0003.jpg
    Aaron_Peirsol_0004.jpg
'''
def AlignDatabase(source, target, align_func):
    unables = []
    for item in os.listdir(source):
        print('working on directory {}'.format(item))
        folder_source = os.path.join(source, item)
        folder_target = os.path.join(target, item)
        if not os.path.isdir(folder_source):
            print(folder_source)
            continue
        unable = _AlignFolder(folder_source, folder_target, align_func)
        unables = unables + unable
    
    print('{} images are unable to align......'.format(len(unables)))
    for path in unables:
        print(path)
    return unables

================================================
FILE: UtilsAlign/landmarks.py
================================================
import tensorflow as tf
import numpy as np
from .base import detect
from PIL import Image
from .common import Inputs2ArrayImage, SelectLargest
 
# convert a path to traing or testing image
def Convert(inputs, landmark_func, output_size, ec_y):
    F = landmark_func
    img = Inputs2ArrayImage(inputs)
    img = Image.fromarray(np.uint8(img))
    landmark = F(img)
    img = _HorizontalEyes(img, landmark)
    img = _Resize(img, landmark, ec_mc_y=48)
    landmark_new = F(img)
    img = _Crop(img, landmark_new, output_size, ec_y)
    # img = img.convert('L') # convert to gray style
    return np.asarray(img) # convert to ndarray
    
def GetAlignFuncByLandmarks(output_size, ec_y):
    F = GetLargestLandmark()
    return lambda inputs: Convert(inputs, F, output_size, ec_y)

def _GetLargestLandmark_impl(inputs, pnet, rnet, onet):
    minsize = 20 # minimum size of face
    threshold = [ 0.6, 0.7, 0.7 ]  # three steps's threshold
    factor = 0.709 # scale factor
    img = Inputs2ArrayImage(inputs)
    img_size = np.asarray(img.shape)[0:2]
    bounding_boxes, landmarks = detect.detect_face(img, minsize, pnet, rnet, onet, threshold, factor)
    num_faces = bounding_boxes.shape[0]
    if num_faces == 0:
        print('Unable to align')
        return
    idx = SelectLargest(bounding_boxes, img_size)
    landmarks = [point[idx] for point in landmarks]
    return landmarks
    
def _GetLandmarks_impl(inputs, pnet, rnet, onet):
    minsize = 20 # minimum size of face
    threshold = [ 0.6, 0.7, 0.7 ]  # three steps's threshold
    factor = 0.709 # scale factor
    img = Inputs2ArrayImage(inputs)
    bounding_boxes, landmarks = detect.detect_face(img, minsize, pnet, rnet, onet, threshold, factor)
    return bounding_boxes, landmarks
     
def _LandmarkFunc(F):
    with tf.Graph().as_default():
        gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=1.0)
        sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options, log_device_placement=False))
        with sess.as_default():
            pnet, rnet, onet = detect.create_mtcnn(sess, None)
    return lambda inputs: F(inputs, pnet, rnet, onet)
    
def GetLargestLandmark():
    return _LandmarkFunc(_GetLargestLandmark_impl)
    
def GetLandmarks():
    return _LandmarkFunc(_GetLandmarks_impl)
    
def _Path2PIL(path):
    with open(path, 'rb') as f:
        with Image.open(f) as img:
            return img.convert('RGB')
            
# rotate image so that eyes are set to be horizontal
def _HorizontalEyes(PILImg, pts):
    k = (pts[6]-pts[5]) / (pts[1]-pts[0])
    angle = np.arctan(k)/np.pi*180
    return PILImg.rotate(angle)
    
#set the distance between the midpoint of eyes and the midpoint of mouth to <ec_mc_y>
def _Resize(PILImg, pts, ec_mc_y):
    midpoint_eye_x = (pts[0] + pts[1])/2
    midpoint_eye_y = (pts[5] + pts[6])/2
    midpoint_mouth_x = (pts[3] + pts[4])/2
    midpoint_mouth_y = (pts[8] + pts[9])/2

    distance = np.sqrt((midpoint_mouth_y - midpoint_eye_y)**2 + (midpoint_mouth_x - midpoint_eye_x)**2)
    w = int(PILImg.size[0] / distance * ec_mc_y)
    h = int(PILImg.size[1] / distance * ec_mc_y)
    return PILImg.resize((w, h), Image.BILINEAR)


# crop the image so that the y axis of midpoint of eyes is <ec_y>      
def _Crop(PILImg, pts, output_size, ec_y):
    midpoint_eye_x = (pts[0] + pts[1])/2
    midpoint_eye_y = (pts[5] + pts[6])/2
    size = output_size
    x = midpoint_eye_x - int(size/2)
    y = midpoint_eye_y - ec_y
    return PILImg.crop((x, y, x + size, y + size))

================================================
FILE: UtilsData/__init__.py
================================================
from .dataset import *
from .dataloader import *


================================================
FILE: UtilsData/dataloader.py
================================================
from .sampler import SequentialSampler, RandomSampler, BatchSampler
import collections
import numpy as np

def Stack(arrays):
    new_dim_array = [np.expand_dims(array, axis=0) for array in arrays]
    return np.concatenate(new_dim_array, axis=0)

def default_collate(batch):
    "Puts each data field into a tensor with outer dimension batch size"
    if isinstance(batch[0], (np.ndarray, np.generic)):
        return Stack(batch)
    elif isinstance(batch[0], int):
        return np.array(batch, dtype=np.int)
    elif isinstance(batch[0], float):
        return np.array(batch, dtype=np.float)
    elif isinstance(batch[0], (str, bytes)):
        return batch
    elif isinstance(batch[0], collections.Mapping):
        return {key: default_collate([d[key] for d in batch]) for key in batch[0]}
    elif isinstance(batch[0], collections.Sequence):
        transposed = zip(*batch)
        return [default_collate(samples) for samples in transposed]
    
    error_msg = "batch must contain tensors, numbers, dicts or lists; found {}"
    raise TypeError((error_msg.format(type(batch[0]))))

class DataLoaderIter(object):
    "Iterates once over the DataLoader's dataset, as specified by the sampler"

    def __init__(self, loader):
        self.dataset = loader.dataset
        self.collate_fn = loader.collate_fn
        self.batch_sampler = loader.batch_sampler
        self.sample_iter = iter(self.batch_sampler)

    def __len__(self):
        return len(self.batch_sampler)

    def __next__(self):
        indices = next(self.sample_iter)  # may raise StopIteration
        batch = self.collate_fn([self.dataset[i] for i in indices])
        return batch

    next = __next__  # Python 2 compatibility

    def __iter__(self):
        return self

    def _put_indices(self):
        assert self.batches_outstanding < 2 * self.num_workers
        indices = next(self.sample_iter, None)
        if indices is None:
            return
        self.index_queue.put((self.send_idx, indices))
        self.batches_outstanding += 1
        self.send_idx += 1

class DataLoader(object):
    def __init__(self, dataset, batch_size=1, shuffle=False,
                 collate_fn=default_collate, drop_last=False):
        self.dataset = dataset
        self.batch_size = batch_size
        self.collate_fn = collate_fn
        self.drop_last = drop_last

        if shuffle:
            sampler = RandomSampler(dataset)
        else:
            sampler = SequentialSampler(dataset)
        self.sampler = sampler
        self.batch_sampler = BatchSampler(sampler, batch_size, drop_last)
        
    def __iter__(self):
        return DataLoaderIter(self)

    def __len__(self):
        return len(self.batch_sampler)
    

================================================
FILE: UtilsData/dataset.py
================================================
import bisect

class Dataset(object):
    def __getitem__(self, index):
        raise NotImplementedError

    def __len__(self):
        raise NotImplementedError

    def __add__(self, other):
        return ConcatDataset([self, other])


class ConcatDataset(Dataset):
    
    @staticmethod
    def cumsum(sequence):
        r, s = [], 0
        for e in sequence:
            l = len(e)
            r.append(l + s)
            s += l
        return r

    def __init__(self, datasets):
        super(ConcatDataset, self).__init__()
        assert len(datasets) > 0, 'datasets should not be an empty iterable'
        self.datasets = list(datasets)
        self.cummulative_sizes = self.cumsum(self.datasets)

    def __len__(self):
        return self.cummulative_sizes[-1]

    def __getitem__(self, idx):
        dataset_idx = bisect.bisect_right(self.cummulative_sizes, idx)
        if dataset_idx == 0:
            sample_idx = idx
        else:
            sample_idx = idx - self.cummulative_sizes[dataset_idx - 1]
        return self.datasets[dataset_idx][sample_idx]

================================================
FILE: UtilsData/sampler.py
================================================
import numpy as np

class Sampler(object):
    def __init__(self, data_source):
        pass

    def __iter__(self):
        raise NotImplementedError

    def __len__(self):
        raise NotImplementedError


class SequentialSampler(Sampler):

    def __init__(self, data_source):
        self.data_source = data_source

    def __iter__(self):
        return iter(range(len(self.data_source)))

    def __len__(self):
        return len(self.data_source)


class RandomSampler(Sampler):

    def __init__(self, data_source):
        self.data_source = data_source

    def __iter__(self):
        return iter(np.random.permutation(len(self.data_source)))

    def __len__(self):
        return len(self.data_source)


class BatchSampler(object):
    """Wraps another sampler to yield a mini-batch of indices.

    Args:
        sampler (Sampler): Base sampler.
        batch_size (int): Size of mini-batch.
        drop_last (bool): If ``True``, the sampler will drop the last batch if
            its size would be less than ``batch_size``

    Example:
        >>> list(BatchSampler(range(10), batch_size=3, drop_last=False))
        [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]
        >>> list(BatchSampler(range(10), batch_size=3, drop_last=True))
        [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
    """

    def __init__(self, sampler, batch_size, drop_last):
        self.sampler = sampler
        self.batch_size = batch_size
        self.drop_last = drop_last

    def __iter__(self):
        batch = []
        for idx in self.sampler:
            batch.append(idx)
            if len(batch) == self.batch_size:
                yield batch
                batch = []
        if len(batch) > 0 and not self.drop_last:
            yield batch

    def __len__(self):
        if self.drop_last:
            return len(self.sampler) // self.batch_size
        else:
            return (len(self.sampler) + self.batch_size - 1) // self.batch_size


================================================
FILE: cfg.py
================================================
from os.path import join
image_size = 224
batch_size = 16


_dir_models = 'E:\\DM\\Faces_origin\\Models'
dir_model = join(_dir_models, 'vgg-face-keras-fc-tensorflow.h5')
dir_model_v2 = join(_dir_models, 'vgg-face-keras-fc-tensorflow-v2.h5')



path_LFW = 'E:\\DM\\Faces\\Data\\LFW\\aligned'
path_AR = 'E:\\DM\\Faces\\Data\\ARFace\\aligned'
path_PCD = 'E:\\DM\\Faces\\Data\\PCD\\aligned'
path_Pose = 'E:\\DM\\Faces\\Data\\PEAL_Pose'
path_Accessory = 'E:\\DM\\Faces\\Data\\PEAL_Accessory'

================================================
FILE: data.py
================================================
'''
Note: All images should be aligend first
'''
import numpy as np
import os
from os import listdir
from os.path import join, exists, isdir
from PIL import Image
import matplotlib.pyplot as plt
from abc import ABCMeta,abstractmethod

from vggface import preprocess_input
import cfg


def _CountFiles(root):
    count = 0
    subfolders = [join(root, subfolder) for subfolder in listdir(root)]
    mask = [isdir(subfolder) for subfolder in subfolders]
    count = len(subfolders) - np.sum(mask)
    subfolders = np.array(subfolders)[mask]

    for subfolder in subfolders:
        count += _CountFiles(subfolder)
    return count
       
class DataSetReader:
    __metaclass__ = ABCMeta

    def __init__(self, dir_images):
        self.root = dir_images
        self.data_size = _CountFiles(self.root)
        
    @abstractmethod
    def GetTriplet(self):
        pass
      
    def GetDataSize(self):
        return self.data_size
    
class PCDReader(DataSetReader):
    def __init__(self, dir_images):
        super().__init__(dir_images)
        paths = os.listdir(self.root)
        paths = [join(self.root, path) for path in paths]
        self.num_class = len(paths)
        self.num_per_person = [len(os.listdir(path)) for path in paths]
                       
    @staticmethod
    def CreateName(root, personID, imageID):
        p = '%03d'%personID
        i = '%02d'%imageID + '.jpg'
        return join(root, p, i)
          
    def GetTriplet(self):
        path_anchor, path_pos, path_neg = '', '', ''
        idx_person_pos = np.random.randint(low=0, high=self.num_class)
        L = self.num_per_person
        
        while not exists(path_anchor):
            idx_img_anchor = np.random.randint(low=0, high=L[idx_person_pos])
            path_anchor = PCDReader.CreateName(self.root, idx_person_pos, idx_img_anchor)
            
            
        idx_img_pos=-1
        while (not exists(path_pos)) or  idx_img_pos==idx_img_anchor:
            idx_img_pos = np.random.randint(low=0, high=L[idx_person_pos])
            path_pos = PCDReader.CreateName(self.root, idx_person_pos, idx_img_pos)
        
        idx_person_neg=-1
        while (not exists(path_neg)) or idx_person_neg==idx_person_pos:
            idx_person_neg = np.random.randint(low=0, high=self.num_class)
            idx_img_neg = np.random.randint(low=0, high=L[idx_person_neg])
            path_neg = PCDReader.CreateName(self.root, idx_person_neg, idx_img_neg)
    
        return path_anchor, path_pos, path_neg
       
class PEALReader(DataSetReader):
    def __init__(self, dir_images):
        super().__init__(dir_images)
        paths = os.listdir(self.root)
        self.dir_sex_list=[path[:1] for path in paths]
        paths = [join(self.root, path) for path in paths]
        self.dir=paths
        self.num_class = len(paths)
        self.num_per_person = [len(os.listdir(path)) for path in paths]
        
    @staticmethod
    def CreateName(root, dir, imageID):
        files=[file for file in os.listdir(dir)]
        return (dir+'\\'+files[imageID])
        
    def GetTriplet(self):
        path_anchor, path_pos, path_neg = '', '', ''
        idx_sex = 'M' if np.random.random() > 0.5 else 'F'
        dir_sex=''
        while(idx_sex!=dir_sex):
            idx_person_pos = np.random.randint(low=0, high=self.num_class)
            dir=self.dir[idx_person_pos]
            dir_sex=self.dir_sex_list[idx_person_pos]
        L = self.num_per_person
        
        for file in os.listdir(dir):
            if file[2:8]=='NORMAL':
                path_anchor=(dir+'\\'+file)
        
        while not exists(path_anchor):
            idx_img_anchor = np.random.randint(low=0, high=L[idx_person_pos])
            path_anchor = PEALReader.CreateName(self.root, dir, idx_img_anchor)
            
            
        while (not exists(path_pos)) or  path_anchor==path_pos:
            idx_img_pos = np.random.randint(low=0, high=L[idx_person_pos])
            path_pos = PEALReader.CreateName(self.root, dir, idx_img_pos)
        
        idx_person_neg=-1
        while (not exists(path_neg)) or idx_person_neg==idx_person_pos or self.dir_sex_list[idx_person_neg]!=idx_sex:
            idx_person_neg = np.random.randint(low=0, high=self.num_class)
            idx_img_neg = np.random.randint(low=0, high=L[idx_person_neg])
            path_neg = PEALReader.CreateName(self.root, self.dir[idx_person_neg], idx_img_neg)
    
        return path_anchor, path_pos, path_neg
        
class ARFaceReader(DataSetReader):

    @staticmethod
    def CreateName(root, sex, personID, imageID):
        name = sex + '-' + '%03d'%personID + '-' + '%02d'%imageID
        name = name + '.bmp'
        return join(root, name)
        
    def GetTriplet(self):
        path_anchor, path_pos, path_neg = '', '', ''
        idx_sex = 'M' if np.random.random() > 0.5 else 'W'
        
        while not exists(path_anchor):
            idx_person_pos = np.random.randint(low=1, high=51)
            path_anchor = ARFaceReader.CreateName(self.root, idx_sex, idx_person_pos, 1)
            
        while not exists(path_pos):
            idx_img_pos = np.random.randint(low=2, high=27)
            path_pos = ARFaceReader.CreateName(self.root, idx_sex, idx_person_pos, idx_img_pos)
        
        idx_person_neg=0
        while (not exists(path_neg)) or idx_person_neg==idx_person_pos:
            idx_person_neg = np.random.randint(low=1, high=51)
            idx_img_neg = np.random.randint(low=1, high=27)
            path_neg = ARFaceReader.CreateName(self.root, idx_sex, idx_person_neg, idx_img_neg)
    
        return path_anchor, path_pos, path_neg
        
class LFWReader(DataSetReader):
    def __init__(self, dir_images):
        super().__init__(dir_images)
        self.list_classes = os.listdir(self.root)
        self.not_single = [c for c in self.list_classes if len(listdir(join(self.root, c)))>1]
        self.list_classes_idx = range(len(self.list_classes))
        self.not_single_idx = range(len(self.not_single))
        
        self.weights_not_single = [len(listdir(join(self.root, c))) for c in self.not_single]
        self.weights_not_single = np.array(self.weights_not_single)
        self.weights_not_single = self.weights_not_single / np.sum(self.weights_not_single)
        
        self.weights = [len(listdir(join(self.root, c))) for c in self.list_classes]
        self.weights = np.array(self.weights)
        self.weights = self.weights / np.sum(self.weights)
         
    def GetTriplet(self):
        # positive and anchor classes are selected from folders where have more than two pictures
        idx_class_pos = np.random.choice(self.not_single_idx, 1 ,p=self.weights_not_single)[0]
        name_pos = self.not_single[idx_class_pos]
        dir_pos = join(self.root, name_pos)
        [idx_img_anchor, idx_img_pos]= np.random.choice(range(len(listdir(dir_pos))), 2, replace=False)
        
        # negative classes are selected from all folders
        while True:
            idx_class_neg = np.random.choice(self.list_classes_idx, 1, p=self.weights)[0]
            if idx_class_neg != idx_class_pos:
                break
        name_neg = self.list_classes[idx_class_neg]
        dir_neg = join(self.root, name_neg)
        idx_img_neg = np.random.choice(range(len(listdir(dir_neg))), 1)[0]
        
        # picture names starts from 1, not 0
        idx_img_anchor += 1
        idx_img_pos += 1
        idx_img_neg += 1
        
        path_anchor = join(dir_pos, name_pos+'_'+'%04d' % idx_img_anchor + '.jpg')
        path_pos = join(dir_pos, name_pos+'_'+'%04d' % idx_img_pos + '.jpg')
        path_neg = join(dir_neg, name_neg+'_'+'%04d' % idx_img_neg + '.jpg')

        return path_anchor, path_pos, path_neg

'''
mix a list of readers together
usage:
    reader_PCD = PCDReader(dir_images=cfg.path_PCD)
    reader_AR = ARFaceReader(dir_images=cfg.path_AR)
    reader_LFW = LFWReader(dir_images=cfg.path_LFW)
    reader = MixedReader([reader_PCD, reader_AR, reader_LFW])
'''
class MixedReader(DataSetReader):
    def __init__(self, list_readers):
        self.readers = list_readers
        
    def GetTriplet(self):
        sizes = np.array([reader.GetDataSize() for reader in self.readers])
        p = sizes/np.sum(sizes)
        idx = np.random.choice(range(len(self.readers)), size=1 ,p=p)[0]
        path_anchor, path_pos, path_neg = self.readers[idx].GetTriplet()
        return path_anchor, path_pos, path_neg
        
    def GetDataSize(self):
        return np.sum([reader.GetDataSize() for reader in self.readers])
        
def _ReadAndResize(filepath):
    im = Image.open((filepath)).convert('RGB')
    im = im.resize((cfg.image_size, cfg.image_size))
    return np.array(im, dtype="float32")

def _Flip(im_array):
    if np.random.uniform(0, 1) > 0.7:
        im_array = np.fliplr(im_array)
    return im_array
    
# create triplet example from LFW dataset
def TripletGenerator(reader):
    while True:
        list_pos = []
        list_anchor = []
        list_neg = []

        for _ in range(cfg.batch_size):
            path_anchor, path_pos, path_neg = reader.GetTriplet()
            img_anchor = _Flip(_ReadAndResize(path_anchor))
            img_pos = _Flip(_ReadAndResize(path_pos))
            img_neg = _Flip(_ReadAndResize(path_neg))
            list_pos.append(img_pos)
            list_anchor.append(img_anchor)
            list_neg.append(img_neg)

        A = preprocess_input(np.array(list_anchor))
        P = preprocess_input(np.array(list_pos))
        N = preprocess_input(np.array(list_neg))
        label = None
        
        yield ({'anchor_input': A, 'positive_input': P, 'negative_input': N}, label)        

def _ShowImg(img):
    plt.figure()
    plt.imshow(img.astype('uint8'))
    plt.show()
    plt.close()
    
def _TestTripletGenerator(reader):  
    gen = TripletGenerator(reader)
    data = next(gen)
    imgs_anchor = data[0]['anchor_input']
    imgs_pos = data[0]['positive_input']
    imgs_neg = data[0]['negative_input']
    print(imgs_anchor.shape)
    print(imgs_pos.shape)
    print(imgs_neg.shape)
    imgs_anchor = imgs_anchor.transpose([0,2,3,1])
    imgs_pos = imgs_pos.transpose([0,2,3,1])
    imgs_neg = imgs_neg.transpose([0,2,3,1])
    
    for idx_img in range(cfg.batch_size):
        anchor = imgs_anchor[idx_img]
        pos = imgs_pos[idx_img]
        neg = imgs_neg[idx_img]
        print(anchor.shape)
        print(pos.shape)
        print(neg.shape)
        _ShowImg(anchor)
        _ShowImg(pos)
        _ShowImg(neg)
        break
    
    print('data size is {}'.format(reader.GetDataSize()))


def TestLFW():
    reader = LFWReader(dir_images=cfg.path_LFW)
    _TestTripletGenerator(reader)
    
def TestARFace():
    reader = ARFaceReader(dir_images=cfg.path_AR)
    _TestTripletGenerator(reader)
    
def TestPCD():
    reader = PCDReader(dir_images=cfg.path_PCD)
    _TestTripletGenerator(reader)
    
def TestPEAL():
    #reader1 = PEALReader(dir_images=path_Pose)
    #TestTripletGenerator(reader1)
    reader2 = PEALReader(dir_images=cfg.path_Accessory)
    _TestTripletGenerator(reader2)
    
def TestMix():
    reader_PCD = PCDReader(dir_images=cfg.path_PCD)
    reader_AR = ARFaceReader(dir_images=cfg.path_AR)
    reader_LFW = LFWReader(dir_images=cfg.path_LFW)
    reader_Pose = PEALReader(dir_images=cfg.path_Pose)
    reader_Accessory = PEALReader(dir_images=cfg.path_Accessory)
    reader = MixedReader([reader_PCD, reader_AR, reader_LFW, reader_Pose, reader_Accessory])
    _TestTripletGenerator(reader)
    
if __name__=='__main__':
    pass
    # TestLFW()
    # TestARFace()
    # TestPCD()
    # TestMix()
    TestPEAL()

    





================================================
FILE: train.py
================================================
import numpy as np
from keras import backend as K
from keras.models import Model
from keras.optimizers import Adam
from keras.layers import Input
# from keras.callbacks import ModelCheckpoint, EarlyStopping
from sklearn.preprocessing import normalize
from vggface import VggFace
import cfg
from data import LFWReader, ARFaceReader, PCDReader, MixedReader, PEALReader
from data import TripletGenerator

def triplet_loss(inputs, dist='sqeuclidean', margin='maxplus'):
    anchor, positive, negative = inputs
    positive_distance = K.square(anchor - positive)
    negative_distance = K.square(anchor - negative)
    if dist == 'euclidean':
        positive_distance = K.sqrt(K.sum(positive_distance, axis=-1, keepdims=True))
        negative_distance = K.sqrt(K.sum(negative_distance, axis=-1, keepdims=True))
    elif dist == 'sqeuclidean':
        positive_distance = K.sum(positive_distance, axis=-1, keepdims=True)
        negative_distance = K.sum(negative_distance, axis=-1, keepdims=True)
    loss = positive_distance - negative_distance
    if margin == 'maxplus':
        loss = K.maximum(0.0, 1 + loss)
    elif margin == 'softplus':
        loss = K.log(1 + K.exp(loss))
    return K.mean(loss)

    
def triplet_loss_np(inputs, dist='sqeuclidean', margin='maxplus'):
    anchor, positive, negative = inputs
    positive_distance = np.square(anchor - positive)
    negative_distance = np.square(anchor - negative)
    if dist == 'euclidean':
        positive_distance = np.sqrt(np.sum(positive_distance, axis=-1, keepdims=True))
        negative_distance = np.sqrt(np.sum(negative_distance, axis=-1, keepdims=True))
    elif dist == 'sqeuclidean':
        positive_distance = np.sum(positive_distance, axis=-1, keepdims=True)
        negative_distance = np.sum(negative_distance, axis=-1, keepdims=True)
    loss = positive_distance - negative_distance
    if margin == 'maxplus':
        loss = np.maximum(0.0, 1 + loss)
    elif margin == 'softplus':
        loss = np.log(1 + np.exp(loss))
    return np.mean(loss)

def check_loss():
    batch_size = 10
    shape = (batch_size, 4096)

    p1 = normalize(np.random.random(shape))
    n = normalize(np.random.random(shape))
    p2 = normalize(np.random.random(shape))
    
    input_tensor = [K.variable(p1), K.variable(n), K.variable(p2)]
    out1 = K.eval(triplet_loss(input_tensor))
    input_np = [p1, n, p2]
    out2 = triplet_loss_np(input_np)

    assert out1.shape == out2.shape
    print(np.linalg.norm(out1))
    print(np.linalg.norm(out2))
    print(np.linalg.norm(out1-out2))

    
def GetModel():
    embedding_model = VggFace(is_origin=True)
    input_shape = (3, cfg.image_size, cfg.image_size)
    anchor_input = Input(input_shape, name='anchor_input')
    positive_input = Input(input_shape, name='positive_input')
    negative_input = Input(input_shape, name='negative_input')
    anchor_embedding = embedding_model(anchor_input)
    positive_embedding = embedding_model(positive_input)
    negative_embedding = embedding_model(negative_input)

    inputs = [anchor_input, positive_input, negative_input]
    outputs = [anchor_embedding, positive_embedding, negative_embedding]
       
    triplet_model = Model(inputs, outputs)
    triplet_model.add_loss(K.mean(triplet_loss(outputs)))
    return embedding_model, triplet_model
    
if __name__=='__main__':
    
    reader_PCD = PCDReader(dir_images=cfg.path_PCD)
    reader_AR = ARFaceReader(dir_images=cfg.path_AR)
    reader_LFW = LFWReader(dir_images=cfg.path_LFW)
    reader_Pose = PEALReader(dir_images=cfg.path_Pose)
    reader_Accessory = PEALReader(dir_images=cfg.path_Accessory)
    reader = MixedReader([reader_PCD, reader_AR, reader_LFW, reader_Pose, reader_Accessory])
    
    reader_tr = MixedReader([reader_LFW, reader_Pose, reader_Accessory])
    reader_te = MixedReader([reader_PCD, reader_AR])

    gen_tr = TripletGenerator(reader_tr)
    gen_te = TripletGenerator(reader_te)
    embedding_model, triplet_model = GetModel()
    
    
    
    
    for layer in embedding_model.layers[-2:]:
        layer.trainable = True
    for layer in embedding_model.layers[:-2]:
        layer.trainable = False
        
    triplet_model.compile(loss=None, optimizer=Adam(0.00002))
    history = triplet_model.fit_generator(gen_tr, 
                              validation_data=gen_te,  
                              epochs=5, 
                              verbose=1, 
                              workers=4,
                              steps_per_epoch=100, 
                              validation_steps=50)
    
    
    
    for layer in embedding_model.layers[30:]:
        layer.trainable = True
    for layer in embedding_model.layers[:30]:
        layer.trainable = False
        
    triplet_model.compile(loss=None, optimizer=Adam(0.000003))
    
    history = triplet_model.fit_generator(gen_tr, 
                              validation_data=gen_te,  
                              epochs=1, 
                              verbose=1, 
                              workers=4,
                              steps_per_epoch=500, 
                              validation_steps=20)
    
    embedding_model.save_weights(cfg.dir_model_tuned)
    '''
    
    

================================================
FILE: utils.py
================================================
'''
frequently used implementations that can be used everywhere :P
'''
import numpy as np
from scipy.misc import imresize
from sklearn.preprocessing import normalize
from sklearn import metrics
from os.path import isfile

import cfg
from vggface import preprocess_input
from UtilsAlign import Inputs2ArrayImage

def GetBestThreshold(distance, label):
    def Cost(fpr, tpr):
        return (1-tpr) + fpr

    label_reverse = np.logical_not(label)
    fpr, tpr, thresholds = metrics.roc_curve(label_reverse, distance)
    
    cost = np.inf
    threshold = None
    for idx in range(len(thresholds)):
        current_cost = Cost(fpr[idx], tpr[idx])
        if current_cost < cost:
            cost = current_cost
            threshold = thresholds[idx]
    return threshold, cost
    
def Verify(path1, path2, model):
    assert(isfile(path1))
    assert(isfile(path2))
    img1 = Inputs2ArrayImage(path1, dtype=np.float32, size=cfg.image_size)
    img2 = Inputs2ArrayImage(path2, dtype=np.float32, size=cfg.image_size)
    img1 = np.expand_dims(img1, axis=0)
    img2 = np.expand_dims(img2, axis=0)
    pair = np.concatenate([img1,img2], axis=0)
    pair = preprocess_input(pair)
    embeddings = model.predict_on_batch(pair)
    dist = _DistanceEuclidean(embeddings[0], embeddings[1])
    return dist
        
def _DistanceEuclidean(X, Y):
    X = X.reshape(1, -1)
    Y = Y.reshape(1, -1)
    diff = (normalize(X) - normalize(Y))
    return (diff**2).sum()
    

    
# if u got two imgs with same size, and u wanna show them together in one shot, here is what u got
def MergeImage(img1, img2, how='auto', color=(40,40,40), margin='auto', min_size=600):

    assert how in ['vertical', 'horizontal', 'auto']
    assert img1.shape==img2.shape
    h = img1.shape[0]
    w = img1.shape[1]
    if how == 'auto':
        how = 'horizontal' if h < w else 'vertical'
    color = np.array(color,dtype=np.uint8)
    if margin == 'auto':
        margin = min(h, w)//20

    new_h = h + margin*2 if how=='vertical' else h*2 + margin*3
    new_w = w + margin*2 if how=='horizontal' else w*2 + margin*3
    
    new_img = np.zeros([new_h, new_w, 3], dtype=np.uint8)
    new_img[:,:,:] = color

    new_img[margin:margin+h,margin:margin+w,:] = img1

    if how == 'vertical':
        start = margin*2 + w
        end = margin*2 + w*2
        new_img[margin:margin+h, start:end, :] = img2
    if how == 'horizontal':
        start = margin*2 + h
        end = margin*2 + h*2
        new_img[start:end, margin:margin+w, :] = img2

    size = min(new_w, new_h)
    ratio = 1 if size<= min_size else min_size/size
    new_w = int(new_w*ratio)
    new_h = int(new_h*ratio)
    new_img = imresize(new_img, (new_h, new_w))
    return new_img

================================================
FILE: vggface.py
================================================
from keras.models import Model
from keras.layers import Lambda, Activation, Input, Conv2D, ZeroPadding2D, MaxPooling2D, Flatten, Dense, Dropout
import numpy as np
from keras import backend as K
import cfg
assert cfg.image_size==224

def VggFace(path=cfg.dir_model, is_origin=False):
    img = Input(shape=(3, 224, 224))

    pad1_1 = ZeroPadding2D(padding=(1, 1))(img)
    conv1_1 = Conv2D(64, (3, 3), activation='relu', name='conv1_1')(pad1_1)
    pad1_2 = ZeroPadding2D(padding=(1, 1))(conv1_1)
    conv1_2 = Conv2D(64, (3, 3), activation='relu', name='conv1_2')(pad1_2)
    pool1 = MaxPooling2D((2, 2), strides=(2, 2))(conv1_2)

    pad2_1 = ZeroPadding2D((1, 1))(pool1)
    conv2_1 = Conv2D(128, (3, 3), activation='relu', name='conv2_1')(pad2_1)
    pad2_2 = ZeroPadding2D((1, 1))(conv2_1)
    conv2_2 = Conv2D(128, (3, 3), activation='relu', name='conv2_2')(pad2_2)
    pool2 = MaxPooling2D((2, 2), strides=(2, 2))(conv2_2)
    
    pad3_1 = ZeroPadding2D((1, 1))(pool2)
    conv3_1 = Conv2D(256, (3, 3), activation='relu', name='conv3_1')(pad3_1)
    pad3_2 = ZeroPadding2D((1, 1))(conv3_1)
    conv3_2 = Conv2D(256, (3, 3), activation='relu', name='conv3_2')(pad3_2)
    pad3_3 = ZeroPadding2D((1, 1))(conv3_2)
    conv3_3 = Conv2D(256, (3, 3), activation='relu', name='conv3_3')(pad3_3)
    pool3 = MaxPooling2D((2, 2), strides=(2, 2))(conv3_3)

    pad4_1 = ZeroPadding2D((1, 1))(pool3)
    conv4_1 = Conv2D(512, (3, 3), activation='relu', name='conv4_1')(pad4_1)
    pad4_2 = ZeroPadding2D((1, 1))(conv4_1)
    conv4_2 = Conv2D(512, (3, 3), activation='relu', name='conv4_2')(pad4_2)
    pad4_3 = ZeroPadding2D((1, 1))(conv4_2)
    conv4_3 = Conv2D(512, (3, 3), activation='relu', name='conv4_3')(pad4_3)
    pool4 = MaxPooling2D((2, 2), strides=(2, 2))(conv4_3)

    pad5_1 = ZeroPadding2D((1, 1))(pool4)
    conv5_1 = Conv2D(512, (3, 3), activation='relu', name='conv5_1')(pad5_1)
    pad5_2 = ZeroPadding2D((1, 1))(conv5_1)
    conv5_2 = Conv2D(512, (3, 3), activation='relu', name='conv5_2')(pad5_2)
    pad5_3 = ZeroPadding2D((1, 1))(conv5_2)
    conv5_3 = Conv2D(512, (3, 3), activation='relu', name='conv5_3')(pad5_3)
    pool5 = MaxPooling2D((2, 2), strides=(2, 2))(conv5_3)

    flat = Flatten()(pool5)
    fc6 = Dense(4096, activation='relu', name='fc6')(flat)
    fc6_drop = Dropout(0.5)(fc6)
    fc7 = Dense(4096, activation=None, name='fc7')(fc6_drop)
    
    norm = Lambda(lambda x: K.l2_normalize(x, axis=1))(fc7)
    
    fc7_activation = Activation('relu')(fc7)
    fc7_drop = Dropout(0.5)(fc7_activation)
    out = Dense(2622, activation='softmax', name='fc8')(fc7_drop)

    if is_origin:
        model = Model(inputs=img, outputs=out)
        model.load_weights(path)
        return Model(inputs=model.input, outputs=norm)

    else:
        model = Model(inputs=img, outputs=norm)
        model.load_weights(path)
        return model
        
def preprocess_input(batch_image):
    if not isinstance(batch_image, (np.ndarray, np.generic)):
        error_msg = "data must be 4d numpy array, but found {}"
        raise TypeError(error_msg.format(type(batch_image)))
    shape = batch_image.shape
    if len(shape) != 4:
        error_msg = "data must be shape of (batch, 224, 224, 3), but found {}"
        raise ValueError(error_msg.format(shape))
    (batch, size0, size1, channel) = shape
    if size0 != 224 or size1 != 224 or channel != 3:
        error_msg = "data must be shape of (batch, 224, 224, 3), but found {}"
        raise ValueError(error_msg.format(shape))
        
    batch_image = batch_image.astype(np.float32)
    batch_image = batch_image.transpose([0,3,1,2])
    return batch_image