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.gitignore
.gitignore
 
 
.gitkeep
.gitkeep
 
 
.pre-commit-config.yaml
.pre-commit-config.yaml
 
 
.pylintrc
.pylintrc
 
 
.travis.yml
.travis.yml
 
 
ColorFIDBenchmarkArtistic.ipynb
ColorFIDBenchmarkArtistic.ipynb
 
 
ColorizeTrainingArtistic.ipynb
ColorizeTrainingArtistic.ipynb
 
 
ColorizeTrainingStable.ipynb
ColorizeTrainingStable.ipynb
 
 
ColorizeTrainingStableLargeBatch.ipynb
ColorizeTrainingStableLargeBatch.ipynb
 
 
ColorizeTrainingVideo.ipynb
ColorizeTrainingVideo.ipynb
 
 
ColorizeTrainingWandb.ipynb
ColorizeTrainingWandb.ipynb
 
 
ImageColorizer.ipynb
ImageColorizer.ipynb
 
 
ImageColorizerArtisticTests.ipynb
ImageColorizerArtisticTests.ipynb
 
 
ImageColorizerColab.ipynb
ImageColorizerColab.ipynb
 
 
ImageColorizerColabStable.ipynb
ImageColorizerColabStable.ipynb
 
 
ImageColorizerStableTests.ipynb
ImageColorizerStableTests.ipynb
 
 
LICENSE
LICENSE
 
 
MANIFEST.in
MANIFEST.in
 
 
QA.md
QA.md
 
 
README.md
README.md
 
 
RRDBNet_arch.cpython-312.pyc
RRDBNet_arch.cpython-312.pyc
 
 
RRDBNet_arch.py
RRDBNet_arch.py
 
 
VideoColorizer.ipynb
VideoColorizer.ipynb
 
 
VideoColorizerColab.ipynb
VideoColorizerColab.ipynb
 
 
app1.py
app1.py
 
 
colorization_deploy_v2.prototxt
colorization_deploy_v2.prototxt
 
 
colorize.py
colorize.py
 
 
download_model.py
download_model.py
 
 
environment.yml
environment.yml
 
 
net_interp.py
net_interp.py
 
 
requirements-colab.txt
requirements-colab.txt
 
 
requirements-dev.txt
requirements-dev.txt
 
 
requirements.txt
requirements.txt
 
 
setup.py
setup.py
 
 
test.py
test.py
 
 
tox.ini
tox.ini
 
 
transer_RRDB_models.py
transer_RRDB_models.py
 
 

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Place pretrained models here.

We provide two pretrained models:

  1. RRDB_ESRGAN_x4.pth: the final ESRGAN model we used in our paper.
  2. RRDB_PSNR_x4.pth: the PSNR-oriented model with high PSNR performance.

Note that the pretrained models are trained under the MATLAB bicubic kernel. If the downsampled kernel is different from that, the results may have artifacts.

About

A Streamlit app that colorizes black-and-white images using deep learning and enhances them with ESRGAN for improved resolution and clarity.

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