GameUp-TSCUNet
Purpose: Compression Removal, General Upscaler, Restoration
This is my first video model! It's aimed at restoring compressed video game footage, like what you'd get from Twitch or Youtube. I've attached an example below.
It's trained on TSCUNet using lossless game recordings, and degraded with my video destroyer. The degradations include resizing, and H264, H265, and AV1 compression.
IMPORTANT: You cannot use this model with chaiNNer or any other tool. You need to use this.
You just run test_vsr.py after installing the requirements. Use the example command from the readme.
You can also use the ONNX version of the model with test_onnx.py
If you want to train a TSCUNet model yourself, use traiNNer-redux. I've included scripts in the SCUNet repository to convert your own models to ONNX if desired.
Showcase: Watch in a Chrome based browser: https://video.yellowmouse.workers.dev/?key=Fvxw482Nsv8=
| Architecture | TSCUNet |
|---|---|
| Scale | 2x |
| Color Mode | |
| License | CC-BY-NC-SA-4.0 Private use Distribution Modifications Credit required Same License State Changes No Liability & Warranty |
| Date | 2025-03-26 |
| Dataset | Custom game dataset |
| Dataset size | 11150 |
| Training iterations | 160000 |
| Training batch size | 8 |