karoly-hars/GAN_image_colorizing

Image colorization with generative adversarial networks on the CIFAR10 dataset.

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Emerging

This project helps researchers and developers explore image colorization techniques using Generative Adversarial Networks (GANs). It takes a grayscale image as input and outputs a colorized version, allowing comparison between different colorization approaches. This is primarily for those studying or experimenting with advanced image processing and machine learning models.

No commits in the last 6 months.

Use this if you are researching or developing new methods for automatically adding color to black and white images, especially within the context of GANs.

Not ideal if you need a production-ready tool for high-quality, precise image colorization on diverse datasets outside of the CIFAR10 dataset.

image-processing computer-vision-research generative-models deep-learning-experimentation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

11

Forks

3

Language

Python

License

MIT

Last pushed

Feb 07, 2020

Commits (30d)

0

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