olaviinha / neuralimagesuperresolution

Colabs for Neural Image Enhancement.

Neural Image Super-Resolution (Colabs)

This is a collection of simplified Colab Notebooks for various neural image enhancers in an attempt to enlarge low resolution images with restored details in high quality. All notebooks support batch processing of an entire directory. All notebooks were made to run in Google Colaboratory, using Google Drive as data source and storage.

Latent Diffusion + FBCNN

Colab for: Latent Diffusion + FBCNN
Papers: High-Resolution Image Synthesis with Latent Diffusion Models https://arxiv.org/abs/2112.10752; Towards Flexible Blind JPEG Artifacts Removal https://arxiv.org/abs/2109.14573

Upscale by Latent Diffusion:

Sharpen by Latent Diffusion & remove JPEG artifacts by FBCNN (this notebook does not increase image resolution):

ESRGAN

Works in Jun 2021.

Colab for: JoeyBallentine's fork of BlueAmulet's fork of ESRGAN by Xinntao.
Paper: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks https://arxiv.org/abs/1809.00219

You can add more pretrained models from upscale.wiki, probably.

Older

Older notebooks are probably inferior and possibly outdated.

Colab for: uperresolution_gan.
Paper: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network https://arxiv.org/abs/1609.04802

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Colab for: Neural Enhance
Papers: See original repository

neuralimagesuperresolution's Issues

Help, i cant start the model because of the path

i have an issue when i specify the input path.

**_FAIL! Input should be a path to an image file or a directory of image files.
An exception has occurred, use %tb to see the full traceback.

SystemExit: Input not understood._**

I tried everything, from google drive, from local, just the image and nothing works. How i can fix it?

Super resolution model

Thanks for the good work. Just wondering which dataset was used to train "the small bsr light model" in your notebook (or referred from Latent_DIffusion repo) for super-resolution? OpenImages as mentioned in the original paper? Thanks.