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Repository: Blade6570/icface
Branch: master
Commit: 3b9fad8560dd
Files: 66
Total size: 7.4 MB
Directory structure:
gitextract_iiz0daxt/
├── License
├── README.md
├── test_code_released_new/
│ ├── 00116.csv
│ ├── 00296.csv
│ ├── checkpoints/
│ │ └── gpubatch_resnet/
│ │ └── opt.txt
│ ├── data/
│ │ ├── __init__.py
│ │ ├── aligned_dataset.py
│ │ ├── aligned_dataset.py~
│ │ ├── base_data_loader.py
│ │ ├── base_dataset.py
│ │ ├── custom_dataset_data_loader.py
│ │ ├── data_loader.py
│ │ ├── image_folder.py
│ │ └── image_folder.py~
│ ├── image_crop.py
│ ├── models/
│ │ ├── __init__.py
│ │ ├── base_model.py
│ │ ├── models.py
│ │ ├── networks.py
│ │ ├── networks.py~
│ │ ├── pix2pix_model.py
│ │ ├── pix2pix_model.py~
│ │ └── test_model.py
│ ├── options/
│ │ ├── __init__.py
│ │ ├── base_options.py
│ │ ├── test_options.py
│ │ └── train_options.py
│ ├── test.py
│ └── util/
│ ├── __init__.py
│ ├── get_data.py
│ ├── html.py
│ ├── image_pool.py
│ ├── util.py
│ └── visualizer.py
└── test_code_released_old/
├── 00116.csv
├── 00296.csv
├── checkpoints/
│ └── gpubatch_resnet/
│ └── opt.txt
├── data/
│ ├── __init__.py
│ ├── aligned_dataset.py
│ ├── aligned_dataset.py~
│ ├── base_data_loader.py
│ ├── base_dataset.py
│ ├── custom_dataset_data_loader.py
│ ├── data_loader.py
│ ├── image_folder.py
│ └── image_folder.py~
├── image_crop.py
├── models/
│ ├── __init__.py
│ ├── base_model.py
│ ├── models.py
│ ├── networks.py
│ ├── networks.py~
│ ├── pix2pix_model.py
│ ├── pix2pix_model.py~
│ └── test_model.py
├── options/
│ ├── __init__.py
│ ├── base_options.py
│ ├── test_options.py
│ └── train_options.py
├── test.py
└── util/
├── __init__.py
├── get_data.py
├── html.py
├── image_pool.py
├── util.py
└── visualizer.py
================================================
FILE CONTENTS
================================================
================================================
FILE: License
================================================
Copyright (C) 2018. Soumya Tripathy, JUho Kannala, Esa Rahtu.
All rights reserved.
Permission to use, copy, modify, and distribute this software and its documentation
for any non-commercial purpose is hereby granted without fee, provided that the above
copyright notice appear in all copies and that both that copyright notice and this
permission notice appear in supporting documentation, and that the name of the author
not be used in advertising or publicity pertaining to distribution of the software
without specific, written prior permission.
THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR ANY PARTICULAR PURPOSE.
IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL
DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING
OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
--------------------------------------LICENSE FOR pytorch-CycleGAN-and-pix2pix------------------------------------------------
Copyright (c) 2017, Jun-Yan Zhu and Taesung Park
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
BSD License
For pix2pix software
Copyright (c) 2016, Phillip Isola and Jun-Yan Zhu
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
================================================
FILE: README.md
================================================
## ICface: Interpretable and Controllable Face Reenactment Using GANs ##
<span style="color:red">**Accepted WACV-2020**</span>
[**Project**](https://tutvision.github.io/icface/) | [**Youtube**](https://www.youtube.com/watch?v=VhWrAjI6z0M) | [**Arxiv**](https://arxiv.org/abs/1904.01909)
***
**Single Image Animation**
Source Image-1 | Animation-1|Source Image-2 | Animation-2
:---------:|:----------:|:---------:|:----------:
 | |  |
This is the part of the implementation of "ICface: Interpretable and Controllable Face Reenactment Using GANs" (https://arxiv.org/abs/1904.01909).
~~_The test code is released now!_~~
:white_check_mark: **_test_code is updated_**
`**Note**: The implementation and results have improved with the current modifications. The codes are updated in /test_code_released_new/. The checkpoints are also updated and added. Feel free to raise an issue if you face any difficulties in running the updated files.`
**Prerequisites**
1. Python 3.5.4
2. Pytorch 0.4.1
3. Visdom and dominate
4. Natsort
*The code is tested on Ubuntu 16.04 LTS*
**Download the Pretrained Weights of ICface**
[Google Drive Link](https://drive.google.com/drive/folders/1jvD8R-Ggo3Seg2tF-JsqlOjwropVwN1S?usp=sharing).
**Testing ICface**
1. Clone the ICface repository and change the working directory to *'/test_code_released_new'*
2. Keep the pretrained weights inside the path: *./checkpoints/gpubatch_resnet*.
3. For the driving video, you can select any video file from *voxceleb* dataset, extract the action units in a .csv file using Openface and store the .csv file in the working folder. We have provided two such .csv files and thier corresponding driving videos.
4. For the source image, we have selected images from *voxceleb* test set. Three exampes are given in the folder *./new_crop*. More can be obtained from [here](http://www.robots.ox.ac.uk/~vgg/research/CMBiometrics/). In particular the "Cropped Face Images extracted at 1fps" (7.8Gb). The test identities can be downloaded <a href="http://www.robots.ox.ac.uk/~vgg/research/unsup_learn_watch_faces/x2face.html">here</a> under the data section.
5. Run in terminal : *python test.py --dataroot ./ --model pix2pix --which_model_netG resnet_6blocks --which_direction AtoB --dataset_mode aligned --norm batch --display_id 0 --batchSize 1 --loadSize 128 --fineSize 128 --no_flip --name gpubatch_resnet --how_many 1 --ndf 256 --ngf 128 --which_ref ./new_crop/1.png --gpu_ids 1 --csv_path 00116.csv --results_dir results_video*
6. The resuting video will be found in *'/test_code_released_new'* under the name *'movie.mp4'*
**If you are not using *voxceleb* test set**
1. In the python file *'image_crop.py'*, add your image path and run it.
2. It will create a new cropped version of your image and will store in *'./new_crop'* folder. Then follow the above steps to create youe video file.
-**_If you are using this implementation for your research work then please cite us as:_**
```
#Citation
@article{tripathy+kannala+rahtu,
title={ICface: Interpretable and Controllable Face Reenactment Using GANs},
author={Tripathy, Soumya and Kannala, Juho and Rahtu, Esa},
journal={arXiv preprint arXiv:1904.01909},
year={2019}
}
```
*NOTE:* Code framework is based on [pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)
================================================
FILE: test_code_released_new/00116.csv
================================================
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Z_58, Z_59, Z_60, Z_61, Z_62, Z_63, Z_64, Z_65, Z_66, Z_67, p_scale, p_rx, p_ry, p_rz, p_tx, p_ty, p_0, p_1, p_2, p_3, p_4, p_5, p_6, p_7, p_8, p_9, p_10, p_11, p_12, p_13, p_14, p_15, p_16, p_17, p_18, p_19, p_20, p_21, p_22, p_23, p_24, p_25, p_26, p_27, p_28, p_29, p_30, p_31, p_32, p_33, AU01_r, AU02_r, AU04_r, AU05_r, AU06_r, AU07_r, AU09_r, AU10_r, AU12_r, AU14_r, AU15_r, AU17_r, AU20_r, AU23_r, AU25_r, AU26_r, AU45_r, AU01_c, AU02_c, AU04_c, AU05_c, AU06_c, AU07_c, AU09_c, AU10_c, AU12_c, AU14_c, AU15_c, AU17_c, AU20_c, AU23_c, AU25_c, AU26_c, AU28_c, AU45_c
1, 0, 0.000, 0.98, 1, 0.095270, 0.229416, -0.968655, -0.145073, 0.218756, -0.964935, -0.026, 0.228, 79.9, 81.9, 86.0, 89.9, 91.2, 89.6, 85.1, 81.3, 74.8, 77.2, 80.6, 85.0, 89.3, 92.7, 94.9, 92.0, 88.1, 84.0, 80.2, 76.9, 83.8, 85.5, 87.3, 88.1, 87.6, 85.9, 84.1, 83.2, 130.9, 132.8, 137.0, 141.1, 142.6, 140.6, 136.4, 132.1, 126.7, 129.5, 133.3, 137.9, 142.2, 145.4, 147.4, 145.1, 141.7, 137.8, 133.6, 129.6, 134.7, 136.5, 138.3, 139.2, 138.5, 136.7, 134.9, 134.1, 49.8, 45.8, 44.4, 46.3, 50.5, 54.8, 55.9, 54.0, 51.5, 49.2, 47.8, 47.3, 48.3, 50.5, 53.3, 54.6, 54.8, 54.8, 54.3, 53.3, 52.0, 52.8, 52.2, 50.5, 48.6, 47.8, 48.4, 50.2, 53.2, 49.1, 47.7, 49.8, 54.1, 58.2, 59.6, 57.9, 55.4, 53.0, 51.4, 51.0, 52.1, 54.0, 56.5, 58.0, 58.5, 58.4, 57.8, 57.1, 55.5, 56.4, 55.8, 54.0, 52.1, 51.2, 51.8, 53.6, -33.2, -31.3, -26.9, -22.9, -21.4, -23.1, -27.6, -31.7, -39.4, -36.4, -32.4, -27.7, -23.2, -19.9, -17.7, -20.6, -24.5, -28.7, -32.8, -36.6, -29.3, -27.5, -25.6, -24.7, -25.4, -27.2, -29.0, -29.9, 18.9, 20.9, 25.2, 29.3, 30.8, 28.7, 24.4, 20.0, 14.7, 17.5, 21.2, 25.8, 30.2, 33.9, 36.5, 33.6, 29.8, 25.6, 21.4, 17.5, 22.8, 24.6, 26.5, 27.4, 26.7, 24.9, 23.0, 22.1, -64.4, -68.7, -70.2, -67.9, -63.4, -58.8, -57.7, -59.9, -64.1, -65.7, -66.3, -66.4, -65.3, -63.4, -60.8, -59.1, -58.5, -58.6, -59.5, -61.3, -62.2, -61.3, -61.9, -63.7, -65.8, -66.7, -66.1, -64.2, -58.7, -63.0, -64.8, -62.8, -58.3, -53.9, -52.2, -53.9, -56.7, -58.9, -60.2, -60.7, -60.1, -59.0, -57.1, -54.8, -53.6, -53.2, -53.7, -54.7, -56.6, -55.8, -56.5, -58.4, -60.4, -61.3, -60.5, -58.6, 211.6, 212.1, 211.9, 211.2, 210.3, 210.0, 210.0, 210.7, 216.3, 213.5, 210.9, 209.3, 209.4, 210.3, 211.6, 210.1, 209.0, 209.1, 210.6, 213.3, 211.6, 211.3, 211.2, 211.5, 211.8, 212.2, 212.2, 212.0, 203.7, 204.7, 205.6, 206.0, 205.5, 204.5, 203.6, 203.4, 204.7, 203.6, 202.8, 203.0, 204.7, 207.5, 210.3, 207.2, 204.4, 202.7, 202.4, 203.4, 204.8, 204.9, 205.4, 205.8, 206.0, 205.8, 205.4, 205.0, -3.7, -30.9, 238.4, 0.070, 0.064, 0.063, 55.8, 54.9, 55.5, 57.2, 61.5, 69.0, 78.3, 89.6, 104.0, 119.5, 134.2, 147.7, 157.6, 163.9, 167.6, 170.2, 171.9, 63.9, 71.2, 81.5, 92.1, 101.5, 121.9, 133.2, 144.4, 154.6, 160.9, 110.9, 109.7, 108.5, 107.3, 95.9, 101.4, 106.9, 113.1, 118.7, 74.6, 81.1, 89.0, 95.1, 88.1, 80.1, 126.5, 133.7, 141.6, 147.7, 141.6, 133.8, 85.8, 93.8, 101.6, 106.3, 111.9, 119.9, 127.9, 119.1, 111.0, 105.1, 99.8, 92.5, 89.1, 101.2, 106.1, 111.7, 124.1, 111.3, 105.6, 100.7, 53.4, 70.0, 86.8, 103.0, 118.0, 130.9, 141.3, 149.6, 152.6, 151.3, 144.3, 134.3, 121.5, 106.2, 90.2, 74.3, 58.4, 39.1, 31.4, 28.9, 30.6, 34.9, 36.0, 33.4, 33.6, 37.6, 45.9, 49.8, 58.7, 67.4, 76.7, 86.5, 88.6, 90.5, 89.5, 88.3, 51.5, 47.7, 48.3, 53.3, 54.8, 54.5, 55.4, 51.2, 52.1, 56.5, 58.5, 57.9, 109.5, 104.5, 102.3, 104.1, 103.1, 106.5, 111.7, 117.8, 119.4, 119.5, 118.7, 115.9, 109.6, 107.9, 108.6, 108.5, 111.5, 112.1, 112.2, 111.4, -81.8, -83.1, -82.3, -79.2, -71.6, -59.1, -44.4, -27.9, -9.8, 9.3, 28.6, 47.5, 61.6, 70.1, 75.2, 78.7, 81.4, -62.2, -51.3, -37.1, -23.5, -12.1, 11.3, 24.4, 38.0, 50.9, 59.6, -1.2, -2.6, -3.7, -4.8, -17.8, -11.6, -5.5, 1.2, 7.4, -46.6, -37.8, -27.9, -20.4, -28.9, -38.9, 17.2, 25.7, 35.1, 42.7, 35.0, 25.7, -31.2, -20.4, -11.4, -6.1, -0.1, 8.8, 18.5, 7.9, -1.0, -7.5, -13.3, -21.9, -26.9, -11.9, -6.5, -0.3, 13.9, -0.7, -6.9, -12.5, -85.3, -61.2, -36.7, -13.0, 8.5, 26.1, 38.6, 46.8, 49.4, 48.6, 41.6, 29.6, 12.8, -7.9, -29.5, -51.0, -72.9, -94.2, -101.3, -101.1, -95.9, -88.8, -86.4, -90.5, -92.0, -88.9, -80.5, -70.9, -58.7, -47.2, -36.1, -28.2, -25.5, -23.2, -24.4, -26.0, -75.5, -78.7, -77.1, -70.6, -69.1, -70.2, -67.1, -71.9, -71.0, -66.5, -63.1, -63.7, -3.0, -8.4, -10.6, -8.6, -9.7, -6.2, -0.4, 6.4, 8.1, 8.1, 7.3, 4.4, -2.8, -4.5, -3.8, -3.8, -0.5, 0.1, 0.2, -0.7, 297.3, 297.5, 297.1, 295.3, 289.6, 281.0, 269.0, 254.4, 248.4, 252.4, 262.8, 271.4, 275.5, 275.9, 276.2, 276.1, 277.5, 263.8, 256.5, 248.4, 240.7, 235.2, 231.9, 235.1, 239.6, 243.9, 248.8, 232.6, 224.6, 216.5, 208.7, 226.3, 222.9, 220.4, 221.5, 223.6, 254.8, 249.9, 247.2, 245.5, 246.5, 249.1, 242.2, 241.6, 241.9, 244.7, 241.0, 240.6, 242.6, 229.5, 223.1, 221.9, 222.1, 227.5, 237.9, 227.3, 221.9, 221.5, 222.9, 229.4, 239.7, 224.8, 223.4, 224.0, 235.3, 223.6, 222.9, 224.6, 0.835, 0.018, 0.114, 0.060, 109.024, 85.151, -8.880, 7.084, -11.781, 10.370, -6.909, -4.882, -0.845, -7.403, -1.630, -4.368, -5.367, 0.925, -1.645, -4.888, 1.159, -3.330, -1.646, -4.081, -1.647, 0.525, 0.100, 0.196, -0.484, 0.958, 0.046, -0.296, 0.321, 0.003, -0.181, -0.084, -0.053, -0.041, -0.033, -0.001, 0.24, 0.26, 0.00, 0.00, 0.00, 0.11, 0.02, 0.00, 0.00, 0.00, 0.00, 0.35, 0.11, 0.13, 0.00, 1.07, 0.00, 0.00, 1.00, 0.00, 1.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00
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gitextract_iiz0daxt/
├── License
├── README.md
├── test_code_released_new/
│ ├── 00116.csv
│ ├── 00296.csv
│ ├── checkpoints/
│ │ └── gpubatch_resnet/
│ │ └── opt.txt
│ ├── data/
│ │ ├── __init__.py
│ │ ├── aligned_dataset.py
│ │ ├── aligned_dataset.py~
│ │ ├── base_data_loader.py
│ │ ├── base_dataset.py
│ │ ├── custom_dataset_data_loader.py
│ │ ├── data_loader.py
│ │ ├── image_folder.py
│ │ └── image_folder.py~
│ ├── image_crop.py
│ ├── models/
│ │ ├── __init__.py
│ │ ├── base_model.py
│ │ ├── models.py
│ │ ├── networks.py
│ │ ├── networks.py~
│ │ ├── pix2pix_model.py
│ │ ├── pix2pix_model.py~
│ │ └── test_model.py
│ ├── options/
│ │ ├── __init__.py
│ │ ├── base_options.py
│ │ ├── test_options.py
│ │ └── train_options.py
│ ├── test.py
│ └── util/
│ ├── __init__.py
│ ├── get_data.py
│ ├── html.py
│ ├── image_pool.py
│ ├── util.py
│ └── visualizer.py
└── test_code_released_old/
├── 00116.csv
├── 00296.csv
├── checkpoints/
│ └── gpubatch_resnet/
│ └── opt.txt
├── data/
│ ├── __init__.py
│ ├── aligned_dataset.py
│ ├── aligned_dataset.py~
│ ├── base_data_loader.py
│ ├── base_dataset.py
│ ├── custom_dataset_data_loader.py
│ ├── data_loader.py
│ ├── image_folder.py
│ └── image_folder.py~
├── image_crop.py
├── models/
│ ├── __init__.py
│ ├── base_model.py
│ ├── models.py
│ ├── networks.py
│ ├── networks.py~
│ ├── pix2pix_model.py
│ ├── pix2pix_model.py~
│ └── test_model.py
├── options/
│ ├── __init__.py
│ ├── base_options.py
│ ├── test_options.py
│ └── train_options.py
├── test.py
└── util/
├── __init__.py
├── get_data.py
├── html.py
├── image_pool.py
├── util.py
└── visualizer.py
SYMBOL INDEX (271 symbols across 39 files)
FILE: test_code_released_new/data/aligned_dataset.py
class AlignedDataset (line 22) | class AlignedDataset(BaseDataset):
method initialize (line 23) | def initialize(self, opt):
method __getitem__ (line 30) | def __getitem__(self, index):
method __len__ (line 64) | def __len__(self):
method name (line 67) | def name(self):
FILE: test_code_released_new/data/base_data_loader.py
class BaseDataLoader (line 1) | class BaseDataLoader():
method __init__ (line 2) | def __init__(self):
method initialize (line 5) | def initialize(self, opt):
method load_data (line 9) | def load_data():
FILE: test_code_released_new/data/base_dataset.py
class BaseDataset (line 6) | class BaseDataset(data.Dataset):
method __init__ (line 7) | def __init__(self):
method name (line 10) | def name(self):
method initialize (line 13) | def initialize(self, opt):
function get_transform (line 18) | def get_transform(opt):
function __scale_width (line 43) | def __scale_width(img, target_width):
FILE: test_code_released_new/data/custom_dataset_data_loader.py
function CreateDataset (line 5) | def CreateDataset(opt):
class CustomDatasetDataLoader (line 24) | class CustomDatasetDataLoader(BaseDataLoader):
method name (line 25) | def name(self):
method initialize (line 28) | def initialize(self, opt):
method load_data (line 37) | def load_data(self):
method __len__ (line 40) | def __len__(self):
method __iter__ (line 43) | def __iter__(self):
FILE: test_code_released_new/data/data_loader.py
function CreateDataLoader (line 1) | def CreateDataLoader(opt):
FILE: test_code_released_new/data/image_folder.py
function is_image_file (line 21) | def is_image_file(filename):
function make_dataset (line 25) | def make_dataset(dir):
function make_grouped_dataset (line 40) | def make_grouped_dataset(dir):
function default_loader (line 54) | def default_loader(path):
class ImageFolder (line 58) | class ImageFolder(data.Dataset):
method __init__ (line 60) | def __init__(self, root, transform=None, return_paths=False,
method __getitem__ (line 74) | def __getitem__(self, index):
method __len__ (line 84) | def __len__(self):
FILE: test_code_released_new/models/base_model.py
class BaseModel (line 5) | class BaseModel():
method name (line 6) | def name(self):
method initialize (line 9) | def initialize(self, opt):
method set_input (line 16) | def set_input(self, input):
method forward (line 19) | def forward(self):
method test (line 23) | def test(self):
method get_image_paths (line 26) | def get_image_paths(self):
method optimize_parameters (line 29) | def optimize_parameters(self):
method get_current_visuals (line 32) | def get_current_visuals(self):
method get_current_errors (line 35) | def get_current_errors(self):
method save (line 38) | def save(self, label):
method save_network (line 42) | def save_network(self, network, network_label, epoch_label, gpu_ids):
method load_network (line 50) | def load_network(self, network, network_label, epoch_label,optimizer):
method update_learning_rate (line 58) | def update_learning_rate(self):
FILE: test_code_released_new/models/models.py
function create_model (line 1) | def create_model(opt):
FILE: test_code_released_new/models/networks.py
function weights_init_normal (line 14) | def weights_init_normal(m):
function weights_init_xavier (line 26) | def weights_init_xavier(m):
function weights_init_kaiming (line 38) | def weights_init_kaiming(m):
function weights_init_orthogonal (line 50) | def weights_init_orthogonal(m):
function init_weights (line 62) | def init_weights(net, init_type='normal'):
function get_norm_layer (line 76) | def get_norm_layer(norm_type='instance'):
function get_scheduler (line 88) | def get_scheduler(optimizer, opt):
function define_G (line 104) | def define_G(input_nc, output_nc, ngf, which_model_netG, norm='batch', u...
function define_D (line 124) | def define_D(input_nc, ndf, which_model_netD,
function print_network (line 147) | def print_network(net):
class GANLoss (line 164) | class GANLoss(nn.Module):
method __init__ (line 165) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
method get_target_tensor (line 180) | def get_target_tensor(self, input, target_is_real):
method __call__ (line 198) | def __call__(self, input, target_is_real):
class VGGLoss (line 202) | class VGGLoss(nn.Module):
method __init__ (line 203) | def __init__(self, gpu_ids):
method forward (line 209) | def forward(self, x, y):
class ResnetGenerator (line 219) | class ResnetGenerator(nn.Module):
method __init__ (line 220) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
method forward (line 264) | def forward(self, input):
class ResnetBlock (line 272) | class ResnetBlock(nn.Module):
method __init__ (line 273) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
method build_conv_block (line 277) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
method forward (line 309) | def forward(self, x):
class NLayerDiscriminator (line 315) | class NLayerDiscriminator(nn.Module):
method __init__ (line 316) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
method forward (line 375) | def forward(self, input):
class PixelDiscriminator (line 387) | class PixelDiscriminator(nn.Module):
method __init__ (line 388) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d, use_si...
method forward (line 409) | def forward(self, input):
class Vgg19 (line 416) | class Vgg19(torch.nn.Module):
method __init__ (line 417) | def __init__(self, requires_grad=False):
method forward (line 439) | def forward(self, X):
FILE: test_code_released_new/models/pix2pix_model.py
class Estimate (line 18) | class Estimate(nn.Module):
method __init__ (line 19) | def __init__(self):
method forward (line 32) | def forward(self, x):
class Pix2PixModel (line 37) | class Pix2PixModel(BaseModel):
method name (line 38) | def name(self):
method _compute_loss_smooth (line 40) | def _compute_loss_smooth(self, mat):
method initialize (line 43) | def initialize(self, opt):
method set_input (line 111) | def set_input(self, input):
method test (line 129) | def test(self):
method get_image_paths (line 175) | def get_image_paths(self):
method _compute_loss_D (line 178) | def _compute_loss_D(self, estim, is_real):
FILE: test_code_released_new/models/test_model.py
class TestModel (line 8) | class TestModel(BaseModel):
method name (line 9) | def name(self):
method initialize (line 12) | def initialize(self, opt):
method set_input (line 27) | def set_input(self, input):
method test (line 35) | def test(self):
method get_image_paths (line 40) | def get_image_paths(self):
method get_current_visuals (line 43) | def get_current_visuals(self):
FILE: test_code_released_new/options/base_options.py
class BaseOptions (line 7) | class BaseOptions():
method __init__ (line 8) | def __init__(self):
method initialize (line 12) | def initialize(self):
method parse (line 46) | def parse(self):
FILE: test_code_released_new/options/test_options.py
class TestOptions (line 4) | class TestOptions(BaseOptions):
method initialize (line 5) | def initialize(self):
FILE: test_code_released_new/options/train_options.py
class TrainOptions (line 4) | class TrainOptions(BaseOptions):
method initialize (line 5) | def initialize(self):
FILE: test_code_released_new/test.py
function main (line 23) | def main():
FILE: test_code_released_new/util/get_data.py
class GetData (line 11) | class GetData(object):
method __init__ (line 29) | def __init__(self, technique='cyclegan', verbose=True):
method _print (line 37) | def _print(self, text):
method _get_options (line 42) | def _get_options(r):
method _present_options (line 48) | def _present_options(self):
method _download_data (line 58) | def _download_data(self, dataset_url, save_path):
method get (line 81) | def get(self, save_path, dataset=None):
FILE: test_code_released_new/util/html.py
class HTML (line 6) | class HTML:
method __init__ (line 7) | def __init__(self, web_dir, title, reflesh=0):
method get_image_dir (line 22) | def get_image_dir(self):
method add_header (line 25) | def add_header(self, str):
method add_table (line 29) | def add_table(self, border=1):
method add_images (line 33) | def add_images(self, ims, txts, links, width=400):
method save (line 45) | def save(self):
FILE: test_code_released_new/util/image_pool.py
class ImagePool (line 6) | class ImagePool():
method __init__ (line 7) | def __init__(self, pool_size):
method query (line 13) | def query(self, images):
FILE: test_code_released_new/util/util.py
function tensor2im (line 10) | def tensor2im(image_tensor, imtype=np.uint8):
function diagnose_network (line 18) | def diagnose_network(net, name='network'):
function save_image (line 31) | def save_image(image_numpy, image_path):
function print_numpy (line 36) | def print_numpy(x, val=True, shp=False):
function mkdirs (line 46) | def mkdirs(paths):
function mkdir (line 54) | def mkdir(path):
FILE: test_code_released_new/util/visualizer.py
class Visualizer (line 10) | class Visualizer():
method __init__ (line 11) | def __init__(self, opt):
method reset (line 33) | def reset(self):
method display_current_results (line 37) | def display_current_results(self, visuals, epoch, save_result):
method plot_current_errors (line 101) | def plot_current_errors(self, epoch, counter_ratio, opt, errors):
method print_current_errors (line 117) | def print_current_errors(self, epoch, i, errors, t):
method save_images (line 127) | def save_images(self, webpage, visuals, image_path, aspect_ratio=1.0):
FILE: test_code_released_old/data/aligned_dataset.py
class AlignedDataset (line 22) | class AlignedDataset(BaseDataset):
method initialize (line 23) | def initialize(self, opt):
method __getitem__ (line 30) | def __getitem__(self, index):
method __len__ (line 64) | def __len__(self):
method name (line 67) | def name(self):
FILE: test_code_released_old/data/base_data_loader.py
class BaseDataLoader (line 1) | class BaseDataLoader():
method __init__ (line 2) | def __init__(self):
method initialize (line 5) | def initialize(self, opt):
method load_data (line 9) | def load_data():
FILE: test_code_released_old/data/base_dataset.py
class BaseDataset (line 6) | class BaseDataset(data.Dataset):
method __init__ (line 7) | def __init__(self):
method name (line 10) | def name(self):
method initialize (line 13) | def initialize(self, opt):
function get_transform (line 18) | def get_transform(opt):
function __scale_width (line 43) | def __scale_width(img, target_width):
FILE: test_code_released_old/data/custom_dataset_data_loader.py
function CreateDataset (line 5) | def CreateDataset(opt):
class CustomDatasetDataLoader (line 24) | class CustomDatasetDataLoader(BaseDataLoader):
method name (line 25) | def name(self):
method initialize (line 28) | def initialize(self, opt):
method load_data (line 37) | def load_data(self):
method __len__ (line 40) | def __len__(self):
method __iter__ (line 43) | def __iter__(self):
FILE: test_code_released_old/data/data_loader.py
function CreateDataLoader (line 1) | def CreateDataLoader(opt):
FILE: test_code_released_old/data/image_folder.py
function is_image_file (line 21) | def is_image_file(filename):
function make_dataset (line 25) | def make_dataset(dir):
function make_grouped_dataset (line 40) | def make_grouped_dataset(dir):
function default_loader (line 54) | def default_loader(path):
class ImageFolder (line 58) | class ImageFolder(data.Dataset):
method __init__ (line 60) | def __init__(self, root, transform=None, return_paths=False,
method __getitem__ (line 74) | def __getitem__(self, index):
method __len__ (line 84) | def __len__(self):
FILE: test_code_released_old/models/base_model.py
class BaseModel (line 5) | class BaseModel():
method name (line 6) | def name(self):
method initialize (line 9) | def initialize(self, opt):
method set_input (line 16) | def set_input(self, input):
method forward (line 19) | def forward(self):
method test (line 23) | def test(self):
method get_image_paths (line 26) | def get_image_paths(self):
method optimize_parameters (line 29) | def optimize_parameters(self):
method get_current_visuals (line 32) | def get_current_visuals(self):
method get_current_errors (line 35) | def get_current_errors(self):
method save (line 38) | def save(self, label):
method save_network (line 42) | def save_network(self, network, network_label, epoch_label, gpu_ids):
method load_network (line 50) | def load_network(self, network, network_label, epoch_label):
method update_learning_rate (line 56) | def update_learning_rate(self):
FILE: test_code_released_old/models/models.py
function create_model (line 1) | def create_model(opt):
FILE: test_code_released_old/models/networks.py
function weights_init_normal (line 14) | def weights_init_normal(m):
function weights_init_xavier (line 26) | def weights_init_xavier(m):
function weights_init_kaiming (line 38) | def weights_init_kaiming(m):
function weights_init_orthogonal (line 50) | def weights_init_orthogonal(m):
function init_weights (line 62) | def init_weights(net, init_type='normal'):
function get_norm_layer (line 76) | def get_norm_layer(norm_type='instance'):
function get_scheduler (line 88) | def get_scheduler(optimizer, opt):
function define_G (line 104) | def define_G(input_nc, output_nc, ngf, which_model_netG, norm='batch', u...
function define_D (line 124) | def define_D(input_nc, ndf, which_model_netD,
function print_network (line 147) | def print_network(net):
class GANLoss (line 164) | class GANLoss(nn.Module):
method __init__ (line 165) | def __init__(self, use_lsgan=True, target_real_label=1.0, target_fake_...
method get_target_tensor (line 180) | def get_target_tensor(self, input, target_is_real):
method __call__ (line 198) | def __call__(self, input, target_is_real):
class VGGLoss (line 202) | class VGGLoss(nn.Module):
method __init__ (line 203) | def __init__(self, gpu_ids):
method forward (line 209) | def forward(self, x, y):
class ResnetGenerator (line 219) | class ResnetGenerator(nn.Module):
method __init__ (line 220) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
method forward (line 264) | def forward(self, input):
class ResnetBlock (line 272) | class ResnetBlock(nn.Module):
method __init__ (line 273) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
method build_conv_block (line 277) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
method forward (line 309) | def forward(self, x):
class NLayerDiscriminator (line 315) | class NLayerDiscriminator(nn.Module):
method __init__ (line 316) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
method forward (line 375) | def forward(self, input):
class PixelDiscriminator (line 387) | class PixelDiscriminator(nn.Module):
method __init__ (line 388) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d, use_si...
method forward (line 409) | def forward(self, input):
class Vgg19 (line 416) | class Vgg19(torch.nn.Module):
method __init__ (line 417) | def __init__(self, requires_grad=False):
method forward (line 439) | def forward(self, X):
FILE: test_code_released_old/models/pix2pix_model.py
class Estimate (line 18) | class Estimate(nn.Module):
method __init__ (line 19) | def __init__(self):
method forward (line 32) | def forward(self, x):
class Pix2PixModel (line 37) | class Pix2PixModel(BaseModel):
method name (line 38) | def name(self):
method _compute_loss_smooth (line 40) | def _compute_loss_smooth(self, mat):
method initialize (line 43) | def initialize(self, opt):
method set_input (line 109) | def set_input(self, input):
method test (line 127) | def test(self):
method get_image_paths (line 173) | def get_image_paths(self):
method _compute_loss_D (line 176) | def _compute_loss_D(self, estim, is_real):
FILE: test_code_released_old/models/test_model.py
class TestModel (line 8) | class TestModel(BaseModel):
method name (line 9) | def name(self):
method initialize (line 12) | def initialize(self, opt):
method set_input (line 27) | def set_input(self, input):
method test (line 35) | def test(self):
method get_image_paths (line 40) | def get_image_paths(self):
method get_current_visuals (line 43) | def get_current_visuals(self):
FILE: test_code_released_old/options/base_options.py
class BaseOptions (line 7) | class BaseOptions():
method __init__ (line 8) | def __init__(self):
method initialize (line 12) | def initialize(self):
method parse (line 46) | def parse(self):
FILE: test_code_released_old/options/test_options.py
class TestOptions (line 4) | class TestOptions(BaseOptions):
method initialize (line 5) | def initialize(self):
FILE: test_code_released_old/options/train_options.py
class TrainOptions (line 4) | class TrainOptions(BaseOptions):
method initialize (line 5) | def initialize(self):
FILE: test_code_released_old/util/get_data.py
class GetData (line 11) | class GetData(object):
method __init__ (line 29) | def __init__(self, technique='cyclegan', verbose=True):
method _print (line 37) | def _print(self, text):
method _get_options (line 42) | def _get_options(r):
method _present_options (line 48) | def _present_options(self):
method _download_data (line 58) | def _download_data(self, dataset_url, save_path):
method get (line 81) | def get(self, save_path, dataset=None):
FILE: test_code_released_old/util/html.py
class HTML (line 6) | class HTML:
method __init__ (line 7) | def __init__(self, web_dir, title, reflesh=0):
method get_image_dir (line 22) | def get_image_dir(self):
method add_header (line 25) | def add_header(self, str):
method add_table (line 29) | def add_table(self, border=1):
method add_images (line 33) | def add_images(self, ims, txts, links, width=400):
method save (line 45) | def save(self):
FILE: test_code_released_old/util/image_pool.py
class ImagePool (line 6) | class ImagePool():
method __init__ (line 7) | def __init__(self, pool_size):
method query (line 13) | def query(self, images):
FILE: test_code_released_old/util/util.py
function tensor2im (line 10) | def tensor2im(image_tensor, imtype=np.uint8):
function diagnose_network (line 18) | def diagnose_network(net, name='network'):
function save_image (line 31) | def save_image(image_numpy, image_path):
function print_numpy (line 36) | def print_numpy(x, val=True, shp=False):
function mkdirs (line 46) | def mkdirs(paths):
function mkdir (line 54) | def mkdir(path):
FILE: test_code_released_old/util/visualizer.py
class Visualizer (line 10) | class Visualizer():
method __init__ (line 11) | def __init__(self, opt):
method reset (line 33) | def reset(self):
method display_current_results (line 37) | def display_current_results(self, visuals, epoch, save_result):
method plot_current_errors (line 101) | def plot_current_errors(self, epoch, counter_ratio, opt, errors):
method print_current_errors (line 117) | def print_current_errors(self, epoch, i, errors, t):
method save_images (line 127) | def save_images(self, webpage, visuals, image_path, aspect_ratio=1.0):
Condensed preview — 66 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (7,792K chars).
[
{
"path": "License",
"chars": 3062,
"preview": "Copyright (C) 2018. Soumya Tripathy, JUho Kannala, Esa Rahtu.\nAll rights reserved. \n\nPermission to use, copy, modify, an"
},
{
"path": "README.md",
"chars": 3841,
"preview": "## ICface: Interpretable and Controllable Face Reenactment Using GANs ##\n<span style=\"color:red\">**Accepted WACV-2020**<"
},
{
"path": "test_code_released_new/00116.csv",
"chars": 2368034,
"preview": "frame, face_id, timestamp, confidence, success, gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_1_z, gaze_angle_x"
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"chars": 1384833,
"preview": "frame, face_id, timestamp, confidence, success, gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_1_z, gaze_angle_x"
},
{
"path": "test_code_released_new/checkpoints/gpubatch_resnet/opt.txt",
"chars": 922,
"preview": "------------ Options -------------\naspect_ratio: 1.0\nbatchSize: 1\ncheckpoints_dir: ./checkpoints\ncsv_path: /home/esa/Dow"
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{
"path": "test_code_released_new/data/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "test_code_released_new/data/aligned_dataset.py",
"chars": 1992,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Mar 13 14:30:12 2019\n\n@author:Soumya\n\"\"\"\nimport os.pat"
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{
"path": "test_code_released_new/data/aligned_dataset.py~",
"chars": 4147,
"preview": "import os.path\nimport random\nimport torchvision.transforms as transforms\nimport torch\nfrom data.base_dataset import Base"
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"path": "test_code_released_new/data/base_data_loader.py",
"chars": 171,
"preview": "class BaseDataLoader():\n def __init__(self):\n pass\n\n def initialize(self, opt):\n self.opt = opt\n "
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{
"path": "test_code_released_new/data/base_dataset.py",
"chars": 1605,
"preview": "import torch.utils.data as data\nfrom PIL import Image\nimport torchvision.transforms as transforms\n\n\nclass BaseDataset(da"
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{
"path": "test_code_released_new/data/custom_dataset_data_loader.py",
"chars": 1457,
"preview": "import torch.utils.data\nfrom data.base_data_loader import BaseDataLoader\n\n\ndef CreateDataset(opt):\n dataset = None\n "
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{
"path": "test_code_released_new/data/data_loader.py",
"chars": 228,
"preview": "def CreateDataLoader(opt):\n from data.custom_dataset_data_loader import CustomDatasetDataLoader\n data_loader = Cus"
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{
"path": "test_code_released_new/data/image_folder.py",
"chars": 2591,
"preview": "###############################################################################\n# Code from\n# https://github.com/pytorch"
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{
"path": "test_code_released_new/data/image_folder.py~",
"chars": 2592,
"preview": "###############################################################################\n# Code from\n# https://github.com/pytorch"
},
{
"path": "test_code_released_new/image_crop.py",
"chars": 1834,
"preview": "#from imutils.face_utils import FaceAligner\nfrom imutils.face_utils import rect_to_bb\nimport imutils\nimport dlib\nimport "
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"preview": ""
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{
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"chars": 701,
"preview": "def create_model(opt):\n model = None\n print(opt.model)\n if opt.model == 'cycle_gan':\n assert(opt.dataset"
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{
"path": "test_code_released_new/models/networks.py",
"chars": 17843,
"preview": "import torch\nimport torch.nn as nn\nfrom torch.nn import init\nimport functools\nfrom torch.autograd import Variable\nfrom t"
},
{
"path": "test_code_released_new/models/networks.py~",
"chars": 31419,
"preview": "import torch\nimport torch.nn as nn\nfrom torch.nn import init\nimport functools\nfrom torch.autograd import Variable\nfrom t"
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{
"path": "test_code_released_new/models/pix2pix_model.py",
"chars": 7438,
"preview": "import torch\nfrom collections import OrderedDict\n#from torch.autograd import Variable\nimport util.util as util\nfrom util"
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{
"path": "test_code_released_new/models/pix2pix_model.py~",
"chars": 28909,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Oct 25 17:51:34 2018\n\n@author: esa\n\"\"\"\n\n#!/usr/bin/env"
},
{
"path": "test_code_released_new/models/test_model.py",
"chars": 1580,
"preview": "from torch.autograd import Variable\nfrom collections import OrderedDict\nimport util.util as util\nfrom .base_model import"
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"preview": ""
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"path": "test_code_released_new/options/test_options.py",
"chars": 1404,
"preview": "from .base_options import BaseOptions\n\n\nclass TestOptions(BaseOptions):\n def initialize(self):\n BaseOptions.in"
},
{
"path": "test_code_released_new/options/train_options.py",
"chars": 3593,
"preview": "from .base_options import BaseOptions\n\n\nclass TrainOptions(BaseOptions):\n def initialize(self):\n BaseOptions.i"
},
{
"path": "test_code_released_new/test.py",
"chars": 1166,
"preview": "import os\nfrom options.test_options import TestOptions\nfrom data.data_loader import CreateDataLoader\nfrom models.models "
},
{
"path": "test_code_released_new/util/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "test_code_released_new/util/get_data.py",
"chars": 3511,
"preview": "from __future__ import print_function\nimport os\nimport tarfile\nimport requests\nfrom warnings import warn\nfrom zipfile im"
},
{
"path": "test_code_released_new/util/html.py",
"chars": 1912,
"preview": "import dominate\nfrom dominate.tags import *\nimport os\n\n\nclass HTML:\n def __init__(self, web_dir, title, reflesh=0):\n "
},
{
"path": "test_code_released_new/util/image_pool.py",
"chars": 1168,
"preview": "import random\nimport torch\nfrom torch.autograd import Variable\n\n\nclass ImagePool():\n def __init__(self, pool_size):\n "
},
{
"path": "test_code_released_new/util/util.py",
"chars": 1482,
"preview": "from __future__ import print_function\nimport torch\nimport numpy as np\nfrom PIL import Image\nimport os\n\n\n# Converts a Ten"
},
{
"path": "test_code_released_new/util/visualizer.py",
"chars": 6500,
"preview": "import numpy as np\nimport os\nimport ntpath\nimport time\nfrom . import util\nfrom . import html\nfrom scipy.misc import imre"
},
{
"path": "test_code_released_old/00116.csv",
"chars": 2368034,
"preview": "frame, face_id, timestamp, confidence, success, gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_1_z, gaze_angle_x"
},
{
"path": "test_code_released_old/00296.csv",
"chars": 1384833,
"preview": "frame, face_id, timestamp, confidence, success, gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_1_z, gaze_angle_x"
},
{
"path": "test_code_released_old/checkpoints/gpubatch_resnet/opt.txt",
"chars": 922,
"preview": "------------ Options -------------\naspect_ratio: 1.0\nbatchSize: 1\ncheckpoints_dir: ./checkpoints\ncsv_path: /home/esa/Dow"
},
{
"path": "test_code_released_old/data/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "test_code_released_old/data/aligned_dataset.py",
"chars": 1992,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Mar 13 14:30:12 2019\n\n@author:Soumya\n\"\"\"\nimport os.pat"
},
{
"path": "test_code_released_old/data/aligned_dataset.py~",
"chars": 4147,
"preview": "import os.path\nimport random\nimport torchvision.transforms as transforms\nimport torch\nfrom data.base_dataset import Base"
},
{
"path": "test_code_released_old/data/base_data_loader.py",
"chars": 171,
"preview": "class BaseDataLoader():\n def __init__(self):\n pass\n\n def initialize(self, opt):\n self.opt = opt\n "
},
{
"path": "test_code_released_old/data/base_dataset.py",
"chars": 1605,
"preview": "import torch.utils.data as data\nfrom PIL import Image\nimport torchvision.transforms as transforms\n\n\nclass BaseDataset(da"
},
{
"path": "test_code_released_old/data/custom_dataset_data_loader.py",
"chars": 1457,
"preview": "import torch.utils.data\nfrom data.base_data_loader import BaseDataLoader\n\n\ndef CreateDataset(opt):\n dataset = None\n "
},
{
"path": "test_code_released_old/data/data_loader.py",
"chars": 228,
"preview": "def CreateDataLoader(opt):\n from data.custom_dataset_data_loader import CustomDatasetDataLoader\n data_loader = Cus"
},
{
"path": "test_code_released_old/data/image_folder.py",
"chars": 2591,
"preview": "###############################################################################\n# Code from\n# https://github.com/pytorch"
},
{
"path": "test_code_released_old/data/image_folder.py~",
"chars": 2592,
"preview": "###############################################################################\n# Code from\n# https://github.com/pytorch"
},
{
"path": "test_code_released_old/image_crop.py",
"chars": 1282,
"preview": "#from imutils.face_utils import FaceAligner\nfrom imutils.face_utils import rect_to_bb\nimport imutils\nimport dlib\nimport "
},
{
"path": "test_code_released_old/models/__init__.py",
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"preview": ""
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{
"path": "test_code_released_old/models/base_model.py",
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"preview": "import os\nimport torch\n\n\nclass BaseModel():\n def name(self):\n return 'BaseModel'\n\n def initialize(self, opt"
},
{
"path": "test_code_released_old/models/models.py",
"chars": 701,
"preview": "def create_model(opt):\n model = None\n print(opt.model)\n if opt.model == 'cycle_gan':\n assert(opt.dataset"
},
{
"path": "test_code_released_old/models/networks.py",
"chars": 17843,
"preview": "import torch\nimport torch.nn as nn\nfrom torch.nn import init\nimport functools\nfrom torch.autograd import Variable\nfrom t"
},
{
"path": "test_code_released_old/models/networks.py~",
"chars": 31419,
"preview": "import torch\nimport torch.nn as nn\nfrom torch.nn import init\nimport functools\nfrom torch.autograd import Variable\nfrom t"
},
{
"path": "test_code_released_old/models/pix2pix_model.py",
"chars": 7379,
"preview": "import torch\nfrom collections import OrderedDict\n#from torch.autograd import Variable\nimport util.util as util\nfrom util"
},
{
"path": "test_code_released_old/models/pix2pix_model.py~",
"chars": 28909,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Oct 25 17:51:34 2018\n\n@author: esa\n\"\"\"\n\n#!/usr/bin/env"
},
{
"path": "test_code_released_old/models/test_model.py",
"chars": 1580,
"preview": "from torch.autograd import Variable\nfrom collections import OrderedDict\nimport util.util as util\nfrom .base_model import"
},
{
"path": "test_code_released_old/options/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "test_code_released_old/options/base_options.py",
"chars": 5153,
"preview": "import argparse\nimport os\nfrom util import util\nimport torch\n\n\nclass BaseOptions():\n def __init__(self):\n self"
},
{
"path": "test_code_released_old/options/test_options.py",
"chars": 1404,
"preview": "from .base_options import BaseOptions\n\n\nclass TestOptions(BaseOptions):\n def initialize(self):\n BaseOptions.in"
},
{
"path": "test_code_released_old/options/train_options.py",
"chars": 3593,
"preview": "from .base_options import BaseOptions\n\n\nclass TrainOptions(BaseOptions):\n def initialize(self):\n BaseOptions.i"
},
{
"path": "test_code_released_old/test.py",
"chars": 1087,
"preview": "import os\nfrom options.test_options import TestOptions\nfrom data.data_loader import CreateDataLoader\nfrom models.models "
},
{
"path": "test_code_released_old/util/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "test_code_released_old/util/get_data.py",
"chars": 3511,
"preview": "from __future__ import print_function\nimport os\nimport tarfile\nimport requests\nfrom warnings import warn\nfrom zipfile im"
},
{
"path": "test_code_released_old/util/html.py",
"chars": 1912,
"preview": "import dominate\nfrom dominate.tags import *\nimport os\n\n\nclass HTML:\n def __init__(self, web_dir, title, reflesh=0):\n "
},
{
"path": "test_code_released_old/util/image_pool.py",
"chars": 1168,
"preview": "import random\nimport torch\nfrom torch.autograd import Variable\n\n\nclass ImagePool():\n def __init__(self, pool_size):\n "
},
{
"path": "test_code_released_old/util/util.py",
"chars": 1482,
"preview": "from __future__ import print_function\nimport torch\nimport numpy as np\nfrom PIL import Image\nimport os\n\n\n# Converts a Ten"
},
{
"path": "test_code_released_old/util/visualizer.py",
"chars": 6500,
"preview": "import numpy as np\nimport os\nimport ntpath\nimport time\nfrom . import util\nfrom . import html\nfrom scipy.misc import imre"
}
]
About this extraction
This page contains the full source code of the Blade6570/icface GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 66 files (7.4 MB), approximately 1.9M tokens, and a symbol index with 271 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.