superres-gan

Here we propose a two-pronged approach towards super resolution of videos, analyzing the efficiencies of both GANs and CNNs.

Name		Name	Last commit message	Last commit date
Latest commit History 45 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Training Functions		Training Functions
Utils		Utils
__pycache__		__pycache__
config		config
data		data
models		models
.gitignore		.gitignore
README.md		README.md
download_videos.py		download_videos.py
loss_cross_entropy.py		loss_cross_entropy.py
model_image_show.ipynb		model_image_show.ipynb
output.jpg		output.jpg
reds_dataset.py		reds_dataset.py
requirements.txt		requirements.txt
resnet_backbone.py		resnet_backbone.py
super_resolution.py		super_resolution.py
test.jpg		test.jpg
test_training.py		test_training.py
testbig.jpg		testbig.jpg
train.py		train.py
urls.txt		urls.txt

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