https://github.com/retkowsky/colorizer
DeOldify is a projet to colorize and restore old images and film footage
https://github.com/retkowsky/colorizer
ai azure azure-ml computer-vision deoldify
Last synced: 6 months ago
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DeOldify is a projet to colorize and restore old images and film footage
- Host: GitHub
- URL: https://github.com/retkowsky/colorizer
- Owner: retkowsky
- Created: 2022-10-21T10:10:46.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-24T09:48:30.000Z (almost 3 years ago)
- Last Synced: 2025-02-08T03:38:55.198Z (8 months ago)
- Topics: ai, azure, azure-ml, computer-vision, deoldify
- Language: Jupyter Notebook
- Homepage:
- Size: 45.5 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# DeOldify is a projet to colorize and restore old images and film footage.
> All credits: https://github.com/jantic/DeOldify
DeOldify is a **Black and White image Colorizing library created by Jason Antic**. DeOldify introduced the NoGAN technique to solve some of the key problems to make hyper-realistic colorization images and video. DeOldify provides **three primary models for different use case**.
## Some colorized images
## A colorized video
Demo Video
## Python notebook
Image Colorizer.ipynb
## Models
Each of these has some limitations and benefit:
#### Artistic Model
This model achieves **vibrant color and detailed images**, but you have to adjust the parameters a lot to get the best results. You have to adjust the rendering resolution and factors to get the most accurate colorize image.
The model uses a **resnet34 backbone on a UNet** with an emphasis on the depth of layers on the decoder side. And it is trained on five critic pretrain/GAN cycle repeats via NoGAN.
#### Stable Model
This model archives the **best results in portraits and landscapes**. It makes sure nothing got too much colored and makes the most part of the image remain gray like faces and limbs. It is less hyper-realistic but it makes sure nothing looks more colored.
It uses a **resnet101 backbone on a UNet** with an emphasis on the width of layers on the decoder side.
#### Video Model
As the name suggests, it is a model used to **color the videos** and we are going to see each of these models working in a python environment. It gives smooth, consistent, and flicker-free Video. This model is the same as a stable model in the case of architecture but different in training. **DeOldify is trained on 2.2% of Imagenet dataset once at 192px, using only the initial generator/critic pretrain/GAN NoGAN training.**