Release IDDM v1.3.0 · chairc/Integrated-Design-Diffusion-Model

What's Changed

docs: Add zread ai badge for asking question of LLM. by @chairc in #168
docs: Update README deepwiki badge. by @chairc in #169
docs: Update README and add iddm logo. by @chairc in #170
docs: Update logo, add new Acknowledgement. by @chairc in #171
docs: remove href. by @chairc in #172
docs: Update docs. by @chairc in #174
docs: Update LICENSE. by @chairc in #175
fix: Fix the issue where installation packages (tensorboard and transformers) are not found when installing requirements.txt with pip. by @chairc in #176
chore: Performance Analysis & Optimization [20251206] by @chairc in #177
chore: pip package update by @chairc in #178
fix: Potential fix for code scanning alert no. 3: Information exposure through an exception by @chairc in #179
refactor: Structure update by @chairc in #180
feat: Major update about trainer device, move parse image size and add new logger. by @chairc in #181
feat: Model update and docs update. by @chairc in #182
chore: Bump package version from 1.2.3 to 1.3.0 by @chairc in #183

Full Changelog: v1.2.3...v1.3.0

Note: The weight include model, ema_model and optimizer.

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)

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)

neu-64-latent-weight.pt: Trained on a dataset of 1,800 defect, and image size is 64 (neu-64-latent-weight.pt)