Normal RG0
Good for
A 4x upscaler for uncompressed normal maps with a zeroed-out B channel. The input is required to have no alpha and constant-zero blue channel. The model can handle some light compression artifacts but has trouble with quantization artifacts. The output normals will also have a constant-zero B channel. Use external software or image editing plugins to properly normalize the generated normals and generate the Z component (if necessary). E.g. chaiNNer can do this with Normalize Normal Map node. Do not rely on this network producing unit vectors.
More information: https://github.com/RunDevelopment/ESRGAN-models/blob/main/normals/README.md
Training details (8)
- Date
- 2022-04-02
- Dataset
- Custom. See description
- Dataset size
- 577
- Training iterations
- 100000
- Training epochs
- 89
- Training batch size
- 8
- Training HR size
- 128
- Training OTF
- No

