HomoInterpGAN - Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation

Overview

HomoInterpGAN

Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation (CVPR 2019, oral)

Installation

The implementation is based on pytorch. Our model is trained and tested on version 1.0.1.post2. Please install relevant packages based on your own environment.

All other required packages are listed in "requirements.txt". Please run

pip install -r requirements.txt

to install these packages.

Dataset

Download the "Align&Cropped Images" of the CelebA dataset. If the original link is unavailable, you can also download it here.

Training

Firstly, cd to the project directory and run

export PYTHONPATH=./:$PYTHONPATH

before executing any script.

To train a model on CelebA, please run

python run.py train --data_dir CELEBA_ALIGNED_DIR -sp checkpoints/CelebA -bs 128 -gpu 0,1,2,3 

Key arguments

--data_dir: The path of the celeba_aligned images. 
-sp: The trained model and logs, intermediate results are stored in this directory.
-bs: Batch size.
-gpu: The GPU index.
--attr: This specifies the target attributes. Note that we concatenate multiple attributes defined in CelebA as our grouped attribute. We use "@" to group multiple multiple attributes to a grouped one (e.g., Mouth_Slightly_Open@Smiling forms a "expression" attriute). We use "," to split different grouped attributes. See the default argument of "run.py" for details. 

Testing

python run.py attribute_manipulation -mp checkpoints/CelebA -sp checkpoints/CelebA/test/Smiling  --filter_target_attr Smiling -s 1 --branch_idx 0 --n_ref 5 -bs 8

This conducts attribute manipulation with reference samples selected in CelebA dataset. The reference samples are selected based on their attributes (--filter_target_attr), and the interpolation path should be chosen accordingly.

Key arguments:

1, the effect is exaggerated. -bs: the batch size of the testing images. -n_ref: the number of images used as reference. ">
-mp: the model path. The checkpoints of encoder, interpolator and decoder should be stored in this path.
-sp: the save path of the results.
--filter_target_attr: This specifies the attributes of the reference images. The attribute names can be found in "info/attribute_names.txt". We can specify one attribute (e.g., "Smiling") or several attributes (e.g., "Smiling@Mouth_Slightly_Open" will filter mouth open smiling reference images). To filter negative samples, add "NOT" as prefix to the attribute names, such as "NOTSmiling", "NOTSmiling@Mouth_Slightly_Open".
--branch_idx: This specifies the branch index of the interpolator. Each branch handles a group of attribute. Note that the physical meaning of each branch is specified by "--attr" during testing. 
-s: The strength of the manipulation. Range of [0, 2] is suggested. If s>1, the effect is exaggerated.
-bs: the batch size of the testing images. 
-n_ref: the number of images used as reference. 

Testing on unaligned images

Note the the performance could degenerate if the testing image is not well aligned. Thus we also provide a tool for face alignment. Please place all your testing images to a folder (e.g., examples/original), then run

python facealign/align_all.py examples/original examples/aligned

to align testing images to an samples in CelebA. Then you can run manipulation by

python run.py attribute_manipulation -mp checkpoints/CelebA -sp checkpoints/CelebA/test/Smiling  --filter_target_attr Smiling -s 1 --branch_idx 0 --n_ref 5 -bs 8 --test_folder examples/aligned

Note that an additional argument "--test_folder" is specified.

Pretrained model

We have also provided a pretrained model here. It is trained with default parameters. The meaning of each branch of the interpolator is listed bellow.

Branch index Grouped attribute Corresponding labels on CelebA
1 Expression Mouth_Slightly_Open, Smiling
2 Gender trait Male, No_Beard, Mustache, Goatee, Sideburns
3 Hair color Black_Hair, Blond_Hair, Brown_Hair, Gray_Hair
4 Hair style Bald, Receding_Hairline, Bangs
5 Age Young

Updates

  • Jun 17, 2019: It is observed that the face alignment tool is not perfect, and the results of "Testing on unaligned images" does not perform as well as results in CelebA dataset. To make the model less sensitive of the alignment issue, we add random shifting in center_crop during training. The shifting range can be controlled by "--random_crop_bias". We have updated the pretarined model by fine-tuning it with "random_crop_bias=10", which leads to better results in unaligned images.

Reference

Ying-Cong Chen, Xiaogang Xu, Zhuotao Tian, Jiaya Jia, "Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation" , Computer Vision and Pattern Recognition (CVPR), 2019 PDF

@inproceedings{chen2019Homomorphic,
  title={Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation},
  author={Chen, Ying-Cong and Xu, Xiaogang and Tian, Zhuotao and Jia, Jiaya},
  booktitle={CVPR},
  year={2019}
}

Contect

Please contact [email protected] if you have any question or suggestion.

Comments
  • Interpolation between dogs and cats

    Interpolation between dogs and cats

    Hello! I am very interested in your work, especially the interpolation between dogs and cats. I saw this result at supplementary material. I want to interpolate without attribute, because there is no label or attribute in my dataset. So could you please tell me how to do?

    opened by ligaozhe 7
  • Questions about the results in supplementary material

    Questions about the results in supplementary material

    Thanks for sharing the nice work!

    I have a few questions about the results of testing RaFD model on wild images:

    1. As the images in RaFD dataset are well aligned, I am wondering whether you take any alignment steps there? Or just simply crop the face -> transform the expression -> place it back to the original image?
    2. May I know whether you use all the images in RaFD to train the model or only the images under frontal camera (90 degree)?

    Looking forward to your reply. Thanks.

    opened by RegisWu 5
  • Why we need

    Why we need "Rigorous Training" for attribute classifier ?

    First of all, congratulation for this outstanding work, but I still have two small questions:

    • Why we need "Rigorous Training" for attribute classifier ? Can you give a more exactly example?
    • Can I consider T^k in interpolator as a "fliter" used to get rid of variables which are not related to correspond attribute from "feature code" F ?

    Thanks!

    opened by LeoXing1996 2
  • Bump pillow from 6.0.0 to 9.0.1

    Bump pillow from 6.0.0 to 9.0.1

    Bumps pillow from 6.0.0 to 9.0.1.

    Release notes

    Sourced from pillow's releases.

    9.0.1

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html

    Changes

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk]
    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.1 (2022-02-03)

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [radarhere, hugovk]

    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    ... (truncated)

    Commits
    • 6deac9e 9.0.1 version bump
    • c04d812 Update CHANGES.rst [ci skip]
    • 4fabec3 Added release notes for 9.0.1
    • 02affaa Added delay after opening image with xdg-open
    • ca0b585 Updated formatting
    • 427221e In show_file, use os.remove to remove temporary images
    • c930be0 Restrict builtins within lambdas for ImageMath.eval
    • 75b69dd Dont need to pin for GHA
    • cd938a7 Autolink CWE numbers with sphinx-issues
    • 2e9c461 Add CVE IDs
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    opened by dependabot[bot] 1
  • Bump pillow from 6.0.0 to 9.0.0

    Bump pillow from 6.0.0 to 9.0.0

    Bumps pillow from 6.0.0 to 9.0.0.

    Release notes

    Sourced from pillow's releases.

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

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    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    • Added ImageShow support for xdg-open #5897 [m-shinder, radarhere]

    • Support 16-bit grayscale ImageQt conversion #5856 [cmbruns, radarhere]

    • Convert subsequent GIF frames to RGB or RGBA #5857 [radarhere]

    ... (truncated)

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  • Bump opencv-python from 4.1.0.25 to 4.1.1.26

    Bump opencv-python from 4.1.0.25 to 4.1.1.26

    Bumps opencv-python from 4.1.0.25 to 4.1.1.26.

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    4.1.1.26

    OpenCV version 4.1.1.

    Changes:

    • FFmpeg has been compiled with https support on Linux builds #229
    • CI build logic related changes #197, #227, #228
    • Custom libjepg-turbo removed because it's provided by OpenCV #231
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  • Bump pillow from 6.0.0 to 8.3.2

    Bump pillow from 6.0.0 to 8.3.2

    Bumps pillow from 6.0.0 to 8.3.2.

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    8.3.2

    https://pillow.readthedocs.io/en/stable/releasenotes/8.3.2.html

    Security

    • CVE-2021-23437 Raise ValueError if color specifier is too long [hugovk, radarhere]

    • Fix 6-byte OOB read in FliDecode [wiredfool]

    Python 3.10 wheels

    • Add support for Python 3.10 #5569, #5570 [hugovk, radarhere]

    Fixed regressions

    • Ensure TIFF RowsPerStrip is multiple of 8 for JPEG compression #5588 [kmilos, radarhere]

    • Updates for ImagePalette channel order #5599 [radarhere]

    • Hide FriBiDi shim symbols to avoid conflict with real FriBiDi library #5651 [nulano]

    8.3.1

    https://pillow.readthedocs.io/en/stable/releasenotes/8.3.1.html

    Changes

    8.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/8.3.0.html

    Changes

    ... (truncated)

    Changelog

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    8.3.2 (2021-09-02)

    • CVE-2021-23437 Raise ValueError if color specifier is too long [hugovk, radarhere]

    • Fix 6-byte OOB read in FliDecode [wiredfool]

    • Add support for Python 3.10 #5569, #5570 [hugovk, radarhere]

    • Ensure TIFF RowsPerStrip is multiple of 8 for JPEG compression #5588 [kmilos, radarhere]

    • Updates for ImagePalette channel order #5599 [radarhere]

    • Hide FriBiDi shim symbols to avoid conflict with real FriBiDi library #5651 [nulano]

    8.3.1 (2021-07-06)

    • Catch OSError when checking if fp is sys.stdout #5585 [radarhere]

    • Handle removing orientation from alternate types of EXIF data #5584 [radarhere]

    • Make Image.array take optional dtype argument #5572 [t-vi, radarhere]

    8.3.0 (2021-07-01)

    • Use snprintf instead of sprintf. CVE-2021-34552 #5567 [radarhere]

    • Limit TIFF strip size when saving with LibTIFF #5514 [kmilos]

    • Allow ICNS save on all operating systems #4526 [baletu, radarhere, newpanjing, hugovk]

    • De-zigzag JPEG's DQT when loading; deprecate convert_dict_qtables #4989 [gofr, radarhere]

    • Replaced xml.etree.ElementTree #5565 [radarhere]

    ... (truncated)

    Commits
    • 8013f13 8.3.2 version bump
    • 23c7ca8 Update CHANGES.rst
    • 8450366 Update release notes
    • a0afe89 Update test case
    • 9e08eb8 Raise ValueError if color specifier is too long
    • bd5cf7d FLI tests for Oss-fuzz crash.
    • 94a0cf1 Fix 6-byte OOB read in FliDecode
    • cece64f Add 8.3.2 (2021-09-02) [CI skip]
    • e422386 Add release notes for Pillow 8.3.2
    • 08dcbb8 Pillow 8.3.2 supports Python 3.10 [ci skip]
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    opened by dependabot[bot] 1
  • Bump pillow from 6.0.0 to 8.2.0

    Bump pillow from 6.0.0 to 8.2.0

    Bumps pillow from 6.0.0 to 8.2.0.

    Release notes

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    8.2.0

    https://pillow.readthedocs.io/en/stable/releasenotes/8.2.0.html

    Changes

    Dependencies

    Deprecations

    ... (truncated)

    Changelog

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    8.2.0 (2021-04-01)

    • Added getxmp() method #5144 [UrielMaD, radarhere]

    • Add ImageShow support for GraphicsMagick #5349 [latosha-maltba, radarhere]

    • Do not load transparent pixels from subsequent GIF frames #5333 [zewt, radarhere]

    • Use LZW encoding when saving GIF images #5291 [raygard]

    • Set all transparent colors to be equal in quantize() #5282 [radarhere]

    • Allow PixelAccess to use Python int when parsing x and y #5206 [radarhere]

    • Removed Image._MODEINFO #5316 [radarhere]

    • Add preserve_tone option to autocontrast #5350 [elejke, radarhere]

    • Fixed linear_gradient and radial_gradient I and F modes #5274 [radarhere]

    • Add support for reading TIFFs with PlanarConfiguration=2 #5364 [kkopachev, wiredfool, nulano]

    • Deprecated categories #5351 [radarhere]

    • Do not premultiply alpha when resizing with Image.NEAREST resampling #5304 [nulano]

    • Dynamically link FriBiDi instead of Raqm #5062 [nulano]

    • Allow fewer PNG palette entries than the bit depth maximum when saving #5330 [radarhere]

    • Use duration from info dictionary when saving WebP #5338 [radarhere]

    • Stop flattening EXIF IFD into getexif() #4947 [radarhere, kkopachev]

    ... (truncated)

    Commits
    • e0e353c 8.2.0 version bump
    • ee635be Merge pull request #5377 from hugovk/security-and-release-notes
    • 694c84f Fix typo [ci skip]
    • 8febdad Review, typos and lint
    • fea4196 Reorder, roughly alphabetic
    • 496245a Fix BLP DOS -- CVE-2021-28678
    • 22e9bee Fix DOS in PSDImagePlugin -- CVE-2021-28675
    • ba65f0b Fix Memory DOS in ImageFont
    • bb6c11f Fix FLI DOS -- CVE-2021-28676
    • 5a5e6db Fix EPS DOS on _open -- CVE-2021-28677
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    opened by dependabot[bot] 1
  • Bump pillow from 6.0.0 to 8.1.1

    Bump pillow from 6.0.0 to 8.1.1

    Bumps pillow from 6.0.0 to 8.1.1.

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    8.1.1

    https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html

    8.1.0

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    Changelog

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    8.1.1 (2021-03-01)

    • Use more specific regex chars to prevent ReDoS. CVE-2021-25292 [hugovk]

    • Fix OOB Read in TiffDecode.c, and check the tile validity before reading. CVE-2021-25291 [wiredfool]

    • Fix negative size read in TiffDecode.c. CVE-2021-25290 [wiredfool]

    • Fix OOB read in SgiRleDecode.c. CVE-2021-25293 [wiredfool]

    • Incorrect error code checking in TiffDecode.c. CVE-2021-25289 [wiredfool]

    • PyModule_AddObject fix for Python 3.10 #5194 [radarhere]

    8.1.0 (2021-01-02)

    • Fix TIFF OOB Write error. CVE-2020-35654 #5175 [wiredfool]

    • Fix for Read Overflow in PCX Decoding. CVE-2020-35653 #5174 [wiredfool, radarhere]

    • Fix for SGI Decode buffer overrun. CVE-2020-35655 #5173 [wiredfool, radarhere]

    • Fix OOB Read when saving GIF of xsize=1 #5149 [wiredfool]

    • Makefile updates #5159 [wiredfool, radarhere]

    • Add support for PySide6 #5161 [hugovk]

    • Use disposal settings from previous frame in APNG #5126 [radarhere]

    • Added exception explaining that repr_png saves to PNG #5139 [radarhere]

    • Use previous disposal method in GIF load_end #5125 [radarhere]

    ... (truncated)

    Commits
    • 741d874 8.1.1 version bump
    • 179cd1c Added 8.1.1 release notes to index
    • 7d29665 Update CHANGES.rst [ci skip]
    • d25036f Credits
    • 973a4c3 Release notes for 8.1.1
    • 521dab9 Use more specific regex chars to prevent ReDoS
    • 8b8076b Fix for CVE-2021-25291
    • e25be1e Fix negative size read in TiffDecode.c
    • f891baa Fix OOB read in SgiRleDecode.c
    • cbfdde7 Incorrect error code checking in TiffDecode.c
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 1
  • Bump pillow from 6.0.0 to 6.2.0

    Bump pillow from 6.0.0 to 6.2.0

    Bumps pillow from 6.0.0 to 6.2.0.

    Release notes

    Sourced from pillow's releases.

    6.2.0

    https://pillow.readthedocs.io/en/stable/releasenotes/6.2.0.html

    6.1.0

    https://pillow.readthedocs.io/en/stable/releasenotes/6.1.0.html

    Changelog

    Sourced from pillow's changelog.

    6.2.0 (2019-10-01)

    • Catch buffer overruns #4104 [radarhere]

    • Initialize rows_per_strip when RowsPerStrip tag is missing #4034 [cgohlke, radarhere]

    • Raise error if TIFF dimension is a string #4103 [radarhere]

    • Added decompression bomb checks #4102 [radarhere]

    • Fix ImageGrab.grab DPI scaling on Windows 10 version 1607+ #4000 [nulano, radarhere]

    • Corrected negative seeks #4101 [radarhere]

    • Added argument to capture all screens on Windows #3950 [nulano, radarhere]

    • Updated warning to specify when Image.frombuffer defaults will change #4086 [radarhere]

    • Changed WindowsViewer format to PNG #4080 [radarhere]

    • Use TIFF orientation #4063 [radarhere]

    • Raise the same error if a truncated image is loaded a second time #3965 [radarhere]

    • Lazily use ImageFileDirectory_v1 values from Exif #4031 [radarhere]

    • Improved HSV conversion #4004 [radarhere]

    • Added text stroking #3978 [radarhere, hugovk]

    • No more deprecated bdist_wininst .exe installers #4029 [hugovk]

    • Do not allow floodfill to extend into negative coordinates #4017 [radarhere]

    ... (truncated)
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    dependencies 
    opened by dependabot[bot] 1
  • TypeError: 'NoneType' object has no attribute 'getitem'

    TypeError: 'NoneType' object has no attribute 'getitem'

    loading default VGG /mnt/backup/project/ycchen/datasets/face/images/celeba_aligned/185954.jpg Traceback (most recent call last): File "run.py", line 192, in engine.run() File "run.py", line 187, in run exec ('self.{}()'.format(self.args.command)) File "", line 1, in File "run.py", line 156, in attribute_manipulation img_out = [tmp for tmp in ref_loader] File "/usr/local/lib/python2.7/dist-packages/torch/utils/data/dataloader.py", line 615, in next batch = self.collate_fn([self.dataset[i] for i in indices]) File "/content/HomoInterpGAN/data/attributeDataset.py", line 163, in getitem img = util.readRGB(self.files[index]).astype(np.float32) File "/content/HomoInterpGAN/util/util.py", line 144, in readRGB return img[:, :, [2, 1, 0]] TypeError: 'NoneType' object has no attribute 'getitem'

    at python run.py attribute_manipulation -mp checkpoints/CelebA -sp checkpoints/CelebA/test/Smiling --filter_target_attr Smiling -s 1 --branch_idx 0 --n_ref 5 -bs 8 --test_folder examples/aligned

    opened by ak9250 1
  • Bump pillow from 6.0.0 to 9.3.0

    Bump pillow from 6.0.0 to 9.3.0

    Bumps pillow from 6.0.0 to 9.3.0.

    Release notes

    Sourced from pillow's releases.

    9.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.3.0 (2022-10-29)

    • Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [wiredfool]

    • Initialize libtiff buffer when saving #6699 [radarhere]

    • Inline fname2char to fix memory leak #6329 [nulano]

    • Fix memory leaks related to text features #6330 [nulano]

    • Use double quotes for version check on old CPython on Windows #6695 [hugovk]

    • Remove backup implementation of Round for Windows platforms #6693 [cgohlke]

    • Fixed set_variation_by_name offset #6445 [radarhere]

    • Fix malloc in _imagingft.c:font_setvaraxes #6690 [cgohlke]

    • Release Python GIL when converting images using matrix operations #6418 [hmaarrfk]

    • Added ExifTags enums #6630 [radarhere]

    • Do not modify previous frame when calculating delta in PNG #6683 [radarhere]

    • Added support for reading BMP images with RLE4 compression #6674 [npjg, radarhere]

    • Decode JPEG compressed BLP1 data in original mode #6678 [radarhere]

    • Added GPS TIFF tag info #6661 [radarhere]

    • Added conversion between RGB/RGBA/RGBX and LAB #6647 [radarhere]

    • Do not attempt normalization if mode is already normal #6644 [radarhere]

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 0
  • Bump numpy from 1.16.3 to 1.22.0

    Bump numpy from 1.16.3 to 1.22.0

    Bumps numpy from 1.16.3 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 0
  • Bump opencv-python from 4.1.0.25 to 4.2.0.32

    Bump opencv-python from 4.1.0.25 to 4.2.0.32

    Bumps opencv-python from 4.1.0.25 to 4.2.0.32.

    Release notes

    Sourced from opencv-python's releases.

    4.2.0.32

    OpenCV version 4.2.0.

    Changes:

    • macOS environment updated from xcode8.3 to xcode 9.4
    • macOS uses now Qt 5 instead of Qt 4
    • Nasm version updated to Docker containers
    • multibuild updated

    Fixes:

    • don't use deprecated brew tap-pin, instead refer to the full package name when installing #267
    • replace get_config_var() with get_config_vars() in setup.py #274
    • add workaround for DLL errors in Windows Server #264

    4.1.2.30

    OpenCV version 4.1.2.

    Changes:

    • Python 3.8 builds added to the build matrix
    • Support for Python 3.4 builds dropped (Python 3.4 is in EOL)
    • multibuild updated
    • minor build logic changes
    • Docker images rebuilt

    Notes:

    Please note that Python 2.7 enters into EOL phase in January 2020. opencv-python Python 2.7 wheels won't be provided after that.

    4.1.1.26

    OpenCV version 4.1.1.

    Changes:

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 0
  • Bump pyyaml from 5.1.1 to 5.4

    Bump pyyaml from 5.1.1 to 5.4

    Bumps pyyaml from 5.1.1 to 5.4.

    Changelog

    Sourced from pyyaml's changelog.

    5.4 (2021-01-19)

    5.3.1 (2020-03-18)

    • yaml/pyyaml#386 -- Prevents arbitrary code execution during python/object/new constructor

    5.3 (2020-01-06)

    5.2 (2019-12-02)

    • Repair incompatibilities introduced with 5.1. The default Loader was changed, but several methods like add_constructor still used the old default yaml/pyyaml#279 -- A more flexible fix for custom tag constructors yaml/pyyaml#287 -- Change default loader for yaml.add_constructor yaml/pyyaml#305 -- Change default loader for add_implicit_resolver, add_path_resolver
    • Make FullLoader safer by removing python/object/apply from the default FullLoader yaml/pyyaml#347 -- Move constructor for object/apply to UnsafeConstructor
    • Fix bug introduced in 5.1 where quoting went wrong on systems with sys.maxunicode <= 0xffff yaml/pyyaml#276 -- Fix logic for quoting special characters
    • Other PRs: yaml/pyyaml#280 -- Update CHANGES for 5.1

    5.1.2 (2019-07-30)

    • Re-release of 5.1 with regenerated Cython sources to build properly for Python 3.8b2+
    Commits
    • 58d0cb7 5.4 release
    • a60f7a1 Fix compatibility with Jython
    • ee98abd Run CI on PR base branch changes
    • ddf2033 constructor.timezone: _copy & deepcopy
    • fc914d5 Avoid repeatedly appending to yaml_implicit_resolvers
    • a001f27 Fix for CVE-2020-14343
    • fe15062 Add 3.9 to appveyor file for completeness sake
    • 1e1c7fb Add a newline character to end of pyproject.toml
    • 0b6b7d6 Start sentences and phrases for capital letters
    • c976915 Shell code improvements
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 0
  • Is it possible to generate an image without reference image ?

    Is it possible to generate an image without reference image ?

    Hi,

    I would like to thank you first for your amazing work !

    As the title said it, I would like to know if is there any way to generate an image without reference image at all ? For example, generate a Woman face with only a Man face (without a Man face as reference).

    test_selected_curve & attribute_manipulation need both as well a reference image to generate the interpolation (correct me if I''m wrong)

    Thank you in advance !

    opened by cyiheng 0
  • TypeError: '>' not supported between instances of 'str' and 'int'

    TypeError: '>' not supported between instances of 'str' and 'int'

    I encountered this error when I tried to execute the training script. The line of code that caused the exception is seen here url. I am looking forward to your help.

    Below is the detailed error message:

    /home/shhs/anaconda3/envs/torch_1_0_py3_6/bin/python /home.bak/shhs/soft/pycharm-2019.1.1/helpers/pydev/pydevd.py --multiproc --qt-support=auto --client 127.0.0.1 --port 46783 --file /media/shhs/Peterou2/user/code/HomoInterpGAN/run.py attribute_manipulation -bs 8 -gpu 0 pydev debugger: process 6843 is connecting

    Connected to pydev debugger (build 191.6605.12) loading default VGG

    • Total Images: 162770 Traceback (most recent call last): File "/home.bak/shhs/soft/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1741, in main() File "/home.bak/shhs/soft/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1735, in main globals = debugger.run(setup['file'], None, None, is_module) File "/home.bak/shhs/soft/pycharm-2019.1.1/helpers/pydev/pydevd.py", line 1135, in run pydev_imports.execfile(file, globals, locals) # execute the script File "/home.bak/shhs/soft/pycharm-2019.1.1/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "/media/shhs/Peterou2/user/code/HomoInterpGAN/run.py", line 205, in engine.run() File "/media/shhs/Peterou2/user/code/HomoInterpGAN/run.py", line 200, in run exec ('self.{}()'.format(self.args.command)) File "", line 1, in File "/media/shhs/Peterou2/user/code/HomoInterpGAN/run.py", line 161, in attribute_manipulation _, test_dataset = self.load_dataset() File "/media/shhs/Peterou2/user/code/HomoInterpGAN/run.py", line 106, in load_dataset csv_path='info/celeba-with-orientation.csv') File "/media/shhs/Peterou2/user/code/HomoInterpGAN/data/attributeDataset.py", line 220, in init f3 = self.frame.iloc[:, 1:] > 0 File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 2108, in f res = self._combine_const(other, func) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/frame.py", line 5120, in _combine_const return ops.dispatch_to_series(self, other, func) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1157, in dispatch_to_series new_data = expressions.evaluate(column_op, str_rep, left, right) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/computation/expressions.py", line 208, in evaluate return _evaluate(op, op_str, a, b, **eval_kwargs) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/computation/expressions.py", line 68, in _evaluate_standard return op(a, b) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1128, in column_op for i in range(len(a.columns))} File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1128, in for i in range(len(a.columns))} File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1766, in wrapper res = na_op(values, other) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1625, in na_op result = _comp_method_OBJECT_ARRAY(op, x, y) File "/home/shhs/anaconda3/envs/torch_1_0_py3_6/lib/python3.6/site-packages/pandas/core/ops.py", line 1603, in _comp_method_OBJECT_ARRAY result = libops.scalar_compare(x, y, op) File "pandas/_libs/ops.pyx", line 97, in pandas._libs.ops.scalar_compare TypeError: '>' not supported between instances of 'str' and 'int'
    opened by PeterouZh 6
Owner
Ying-Cong Chen
Ying-Cong Chen
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

XCL 191 Dec 31, 2022
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search

CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is

Federico Galatolo 172 Dec 22, 2022
Face Identity Disentanglement via Latent Space Mapping [SIGGRAPH ASIA 2020]

Face Identity Disentanglement via Latent Space Mapping Description Official Implementation of the paper Face Identity Disentanglement via Latent Space

null 150 Dec 7, 2022
Navigating StyleGAN2 w latent space using CLIP

Navigating StyleGAN2 w latent space using CLIP an attempt to build sth with the official SG2-ADA Pytorch impl kinda inspired by Generating Images from

Mike K. 55 Dec 6, 2022
Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN

Face Identity Disentanglement via Latent Space Mapping - Implement in pytorch with StyleGAN 2 Description Pytorch implementation of the paper Face Ide

Daniel Roich 58 Dec 24, 2022
Disentangled Face Attribute Editing via Instance-Aware Latent Space Search, accepted by IJCAI 2021.

Instance-Aware Latent-Space Search This is a PyTorch implementation of the following paper: Disentangled Face Attribute Editing via Instance-Aware Lat

null 67 Dec 21, 2022
[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing

InterFaceGAN - Interpreting the Latent Space of GANs for Semantic Face Editing Figure: High-quality facial attributes editing results with InterFaceGA

GenForce: May Generative Force Be with You 1.3k Dec 29, 2022
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models Code accompanying CVPR'20 paper of the same title. Paper lin

Alex Damian 7k Dec 30, 2022
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space

Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte

null 38 Dec 15, 2022
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt

Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt. This is done by

Mehdi Cherti 135 Dec 30, 2022
PyTorch implementation of the WarpedGANSpace: Finding non-linear RBF paths in GAN latent space (ICCV 2021)

Authors official PyTorch implementation of the "WarpedGANSpace: Finding non-linear RBF paths in GAN latent space" [ICCV 2021].

Christos Tzelepis 100 Dec 6, 2022
InterFaceGAN - Interpreting the Latent Space of GANs for Semantic Face Editing

InterFaceGAN - Interpreting the Latent Space of GANs for Semantic Face Editing Figure: High-quality facial attributes editing results with InterFaceGA

GenForce: May Generative Force Be with You 1.3k Jan 9, 2023
Code for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in Deep Latent Space"

SRHEN This is a better and simpler implementation for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in

null 1 Oct 28, 2022
Code to reproduce the results in the paper "Tensor Component Analysis for Interpreting the Latent Space of GANs".

Tensor Component Analysis for Interpreting the Latent Space of GANs [ paper | project page ] Code to reproduce the results in the paper "Tensor Compon

James Oldfield 4 Jun 17, 2022
Visualizer using audio and semantic analysis to explore BigGAN (Brock et al., 2018) latent space.

BigGAN Audio Visualizer Description This visualizer explores BigGAN (Brock et al., 2018) latent space by using pitch/tempo of an audio file to generat

Rush Kapoor 2 Nov 21, 2022
Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

HamasKhan 3 Jul 8, 2022
Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im

Valentin Wolf 86 Nov 16, 2022
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) --> xmodel(xilinx

JiaKui Hu 10 Oct 28, 2022
Unpaired Caricature Generation with Multiple Exaggerations

CariMe-pytorch The official pytorch implementation of the paper "CariMe: Unpaired Caricature Generation with Multiple Exaggerations" CariMe: Unpaired

Gu Zheng 37 Dec 30, 2022