What's Changed
- fix: Fix check_parse_image_size_type method by @chairc in #184
- feat(logger): Logger support distributed training. by @chairc in #185
- chore: Optimize the trainer training logic. by @chairc in #186
- chore: Optimize the trainer output information and PSNR. by @chairc in #187
- chore: Bump package version from 1.3.0 to 1.3.1 by @chairc in #188
Full Changelog: v1.3.0...v1.3.1
Weights
Note: The weight include model, ema_model and optimizer.
Diffusion Models
celebahq-120-weight.pt: Trained on a dataset of 30,000 people face, and image size is 120 (celebahq-120-weight.pt)animate-ganyu-120-weight.pt: Trained on a dataset of 500 animate ganyu face, and image size is 120 (animate-ganyu-120-weight.pt)neu-cls-64-weight.pt: Trained on a dataset of 7,226 defect, and image size is 64 (neu-cls-64-weight.pt)neu-120-weight.pt: Trained on a dataset of 1,800 defect, and image size is 120 (neu-120-weight.pt)cifar-64-weight.pt: Trained on a dataset of 60,000 images, and image size is 64 (cifar10-64-weight.pt)animate-face-64-weight.pt: Trained on a dataset of 63,565 animate face, and image size is 64 (animate-face-64-weight.pt)
Autoencoder Models
neu-autoencoder-512-weight.pt: Trained on a dataset of 1,800 defect, and image size is 512 (neu-autoencoder-512-weight.pt)voc-autoencoder-512-weight.pt: Trained on a dataset of 33,240 images, and image size is 512 (voc-autoencoder-512-weight.pt)
Latent Diffusion Models
neu-64-latent-weight.pt: Trained on a dataset of 1,800 defect, and image size is 64 (neu-64-latent-weight.pt)
Contributors
chairc