SYMBOL INDEX (84 symbols across 10 files)

FILE: lib/densenet.py
  function preprocess_input (line 90) | def preprocess_input(x, data_format=None):
  function DenseNet (line 105) | def DenseNet(input_shape=None,
  function DenseNetFCN (line 307) | def DenseNetFCN(input_shape, nb_dense_block=5, growth_rate=16, nb_layers...
  function DenseNetImageNet121 (line 436) | def DenseNetImageNet121(input_shape=None,
  function DenseNetImageNet169 (line 454) | def DenseNetImageNet169(input_shape=None,
  function DenseNetImageNet201 (line 472) | def DenseNetImageNet201(input_shape=None,
  function DenseNetImageNet264 (line 490) | def DenseNetImageNet264(input_shape=None,
  function DenseNetImageNet161 (line 508) | def DenseNetImageNet161(input_shape=None,
  function name_or_none (line 526) | def name_or_none(prefix, name):
  function __conv_block (line 530) | def __conv_block(ip, nb_filter, bottleneck=False, dropout_rate=None, wei...
  function __dense_block (line 583) | def __dense_block(x, nb_layers, nb_filter, growth_rate, bottleneck=False...
  function __transition_block (line 633) | def __transition_block(ip, nb_filter, compression=1.0, weight_decay=1e-4...
  function __transition_up_block (line 680) | def __transition_up_block(ip, nb_filters, type='deconv', weight_decay=1E...
  function __create_dense_net (line 724) | def __create_dense_net(nb_classes, img_input, include_top, depth=40, nb_...
  function __create_fcn_dense_net (line 864) | def __create_fcn_dense_net(nb_classes, img_input, include_top, nb_dense_...

FILE: lib/extract_patches.py
  function get_data_training (line 16) | def get_data_training(DRIVE_train_imgs_original,
  function get_data_testing (line 54) | def get_data_testing(DRIVE_test_imgs_original, DRIVE_test_groudTruth, Im...
  function get_data_testing_overlap (line 94) | def get_data_testing_overlap(DRIVE_test_imgs_original, DRIVE_test_groudT...
  function data_consistency_check (line 127) | def data_consistency_check(imgs,masks):
  function extract_random (line 138) | def extract_random(full_imgs,full_masks, patch_h,patch_w, N_patches, ins...
  function is_patch_inside_FOV (line 175) | def is_patch_inside_FOV(x,y,img_w,img_h,patch_h):
  function extract_ordered (line 187) | def extract_ordered(full_imgs, patch_h, patch_w):
  function paint_border_overlap (line 213) | def paint_border_overlap(full_imgs, patch_h, patch_w, stride_h, stride_w):
  function extract_ordered_overlap (line 240) | def extract_ordered_overlap(full_imgs, patch_h, patch_w,stride_h,stride_w):
  function recompone_overlap (line 263) | def recompone_overlap(preds, img_h, img_w, stride_h, stride_w):
  function recompone (line 297) | def recompone(data,N_h,N_w):
  function paint_border (line 324) | def paint_border(data,patch_h,patch_w):
  function pred_only_FOV (line 345) | def pred_only_FOV(data_imgs,data_masks,original_imgs_border_masks):
  function kill_border (line 366) | def kill_border(data, original_imgs_border_masks):
  function inside_FOV_DRIVE (line 378) | def inside_FOV_DRIVE(i, x, y, DRIVE_masks):

FILE: lib/help_functions.py
  function load_hdf5 (line 6) | def load_hdf5(infile):
  function write_hdf5 (line 10) | def write_hdf5(arr,outfile):
  function rgb2gray (line 15) | def rgb2gray(rgb):
  function group_images (line 23) | def group_images(data,per_row):
  function visualize (line 40) | def visualize(data,filename):
  function masks_Unet (line 54) | def masks_Unet(masks):
  function pred_to_imgs (line 76) | def pred_to_imgs(pred, patch_height, patch_width, mode="original"):

FILE: lib/pre_processing.py
  function my_PreProc (line 16) | def my_PreProc(data):
  function histo_equalized (line 34) | def histo_equalized(imgs):
  function clahe_equalized (line 45) | def clahe_equalized(imgs):
  function dataset_normalized (line 57) | def dataset_normalized(imgs):
  function adjust_gamma (line 69) | def adjust_gamma(imgs, gamma=1.0):

FILE: prepare_datasets_DRIVE.py
  function write_hdf5 (line 14) | def write_hdf5(arr,outfile):
  function get_datasets (line 39) | def get_datasets(imgs_dir,groundTruth_dir,borderMasks_dir,train_test="nu...

FILE: src/LadderNetv65.py
  function conv3x3 (line 7) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 13) | class BasicBlock(nn.Module):
    method __init__ (line 16) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 52) | class Bottleneck(nn.Module):
    method __init__ (line 55) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 68) | def forward(self, x):
  class Initial_LadderBlock (line 90) | class Initial_LadderBlock(nn.Module):
    method __init__ (line 92) | def __init__(self,planes,layers,kernel=3,block=BasicBlock,inplanes = 3):
    method forward (line 124) | def forward(self, x):
  class LadderBlock (line 152) | class LadderBlock(nn.Module):
    method __init__ (line 154) | def __init__(self,planes,layers,kernel=3,block=BasicBlock,inplanes = 3):
    method forward (line 185) | def forward(self, x):
  class Final_LadderBlock (line 214) | class Final_LadderBlock(nn.Module):
    method __init__ (line 216) | def __init__(self,planes,layers,kernel=3,block=BasicBlock,inplanes = 3):
    method forward (line 220) | def forward(self, x):
  class LadderNetv6 (line 224) | class LadderNetv6(nn.Module):
    method __init__ (line 225) | def __init__(self,layers=3,filters=16,num_classes=2,inplanes=3):
    method forward (line 232) | def forward(self,x):

FILE: src/losses.py
  function cuda (line 5) | def cuda(x):
  class LossMulti (line 9) | class LossMulti:
    method __init__ (line 10) | def __init__(self, jaccard_weight=0, class_weights=None, num_classes=1):
    method __call__ (line 20) | def __call__(self, outputs, targets):

FILE: src/retinaNN_predict.py
  class TrainDataset (line 147) | class TrainDataset(Dataset):
    method __init__ (line 150) | def __init__(self, patches_imgs):
    method __len__ (line 153) | def __len__(self):
    method __getitem__ (line 156) | def __getitem__(self, idx):

FILE: src/retinaNN_training.py
  function count_parameters (line 34) | def count_parameters(model):
  class TrainDataset (line 94) | class TrainDataset(Dataset):
    method __init__ (line 97) | def __init__(self, patches_imgs,patches_masks_train):
    method __len__ (line 101) | def __len__(self):
    method __getitem__ (line 104) | def __getitem__(self, idx):
  function train (line 149) | def train(epoch):
  function test (line 177) | def test(epoch, display=False):

FILE: src/subpixel_upscaling.py
  class SubPixelUpscaling (line 15) | class SubPixelUpscaling(Layer):
    method __init__ (line 51) | def __init__(self, scale_factor=2, data_format=None, **kwargs):
    method build (line 57) | def build(self, input_shape):
    method call (line 60) | def call(self, x, mask=None):
    method compute_output_shape (line 64) | def compute_output_shape(self, input_shape):
    method get_config (line 72) | def get_config(self):