Releases: chairc/Integrated-Design-Diffusion-Model
Releases · chairc/Integrated-Design-Diffusion-Model
IDDM v1.3.1
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
Assets 2
IDDM v1.3.0
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
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
Assets 5
IDDM v1.2.3
What's Changed
- feat: add new sample dpm2 by @RachelElizaUK in #159
- feat: Update samples by @chairc in #160
- refactor: Refactor dpm2 and add sample loop fn. by @RachelElizaUK in #161
- feat: Add dpmpp sample. by @RachelElizaUK in #162
- chore: Update the get_activation_function. by @chairc in #163
- feat: Update PR to support multiple functions. by @chairc in #164
- feat(docker): Add docker file running test. by @chairc in #165
- docs: Update next steps. by @chairc in #166
- chore: Update the version[v1.2.3]. by @chairc in #167
Full Changelog: v1.2.2...v1.2.3
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 and RachelElizaUK
Assets 2
IDDM v1.2.2
What's Changed
- feat: Update about attention. by @chairc in #155
- chore: Optimized flash-attn. by @chairc in #156
- fix: Fix the issue of ddpm generation noise in Latent mode. by @chairc in #157
- chore: Update version and README by @chairc in #158
Full Changelog: v1.2.1...v1.2.2
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
Assets 2
IDDM v1.2.2-beta.1
What's Changed
Full Changelog: v1.2.1...v1.2.2-beta.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
Assets 2
IDDM v1.2.1
What's Changed
- docs: Update the VAE name. by @chairc in #150
- feat: Integrate the latent diffusion. by @chairc in #151
- chore: Remove redundant latent diffusion models code. by @chairc in #152
- Update deploy. by @chairc in #153
- chore: Update the pip version[v1.2.1]. by @chairc in #154
Full Changelog: v1.2.0...v1.2.1
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
Assets 3
IDDM v1.2.0
What's Changed
- docs: Add the README in weights. by @chairc in #144
- Refactor model samples and trainer by @chairc in #146
- feat: Add Latent Diffusion Models, Support generate 512*512 images and reduce GPU memory usage. by @chairc in #147
- Update some tiny thing. by @chairc in #148
- Update pip and download link by @chairc in #149
Full Changelog: v1.1.9...v1.2.0
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)
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
Assets 4
IDDM v1.1.9
What's Changed
- refactor: Refactor and add some old code. by @chairc in #129
- docs: Add new docs dir. by @chairc in #130
- docs: Update new README. by @chairc in #131
- chore: Update installation scripts and documentation. by @chairc in #132
- feat: Test new network and self-attention. by @chairc in #133
- docs: Update running locally in README. by @chairc in #134
- chore: Update the new version 1.1.9. by @chairc in #136
- chore: Update the pip upload. by @chairc in #138
Full Changelog: v1.1.8-beta.3...v1.1.9
Weights
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)
Contributors
chairc
Assets 2
IDDM v1.1.8-beta.3
What's Changed
Full Changelog: v1.1.8-beta.2...v1.1.8-beta.3
Weights
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)
Contributors
chairc
Assets 2
IDDM v1.1.8-beta.2
What's Changed
- fix: Patch interface post image to solve the MEAN and STD not to work. by @bestl1fe in #104
- fix: Fix MEAN and STD bug and update organization logo. by @chairc in #105
- chore: MEAN and STD params setting by @chairc in #108
- feat: Parameters decomposed into methods; Added PSNR and SSIM calculators; Update requirements.txt. by @chairc in #109
- chore: Update model list by @chairc in #110
- chore: Add use_gpu params. by @chairc in #111
- refactor: Refactor trainer and update README by @chairc in #113
- fix: Patch pip and server by @BestChenA in #114
- fix: Fix import package safety alerts; Fix the bug that the Flask API could only be called once in the server mode by @chairc in #115
- fix: Fix the bug where the pixels of the image exceed 255 or less than 0. by @chairc in #117
- feat: Update the short name trigger parameter. by @chairc in #119
- docs: Fix neu-120-weight.pt pre-training model download link. by @BestChenA in #121
- docs: Update README. by @chairc in #122
- docs: Update username. by @BestChenA in #123
- docs: Update username. by @chairc in #124
New Contributors
- @BestChenA made their first contribution in #114
Full Changelog: v1.1.7...v1.1.8-beta.2
Weights
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)
Contributors
chairc, RachelElizaUK, and chaircbot