Photo Regenerator
Incrementally adds noise over a series of steps via a noise scheduler, and feeds images through a CNN to learn features/patterns to then "regenerate" the image.
Model source
- Kind
- Other
- File size
- 3.47 MB
- Version
- vRevision c04ece4
- Updated
- Sep 26, 2026
- Downloads
- 0
- Source
- Hugging Face
Source description
Photo Regenerator w/Diffusion Denoiser Model
Incrementally adds noise over a series of steps via a noise scheduler, and feeds images through a CNN to learn features/patterns to then "regenerate" the image.
The .ipynb holds the tests and download of the dataset if needed.
Goals:
- Denoise a 25-step noisy image (Blurry)
- Denoise a 100-step noisy image
- Denoise a 500-step noisy image
- Denoise a 1000-step noisy image
Dataset Used: COCO 2017
Sources
1 source
Sources
1 sourceVerified Sep 26
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: mit language: - en metrics: - accuracy pipeline_tag: unconditional-image-generation tags: - art --- # Photo Regenerator w/Diffusion Denoiser Model Incrementally adds noise over a series of steps via a noise scheduler, and feeds images through a CNN to learn features/patterns to then "regenerate" the image. The `.ipynb` holds the tests and download of the dataset if needed. ## Goals: - **Denoise a 25-step noisy image (Blurry)** - Denoise a 100-step noisy image - Denoise a 500-step noisy image - Denoise a 1000-step noisy image **Dataset Used: COCO 2017**
Source context: 0 downloads · 0 likes · Pipeline unconditional-image-generation · Repo reeeemo/photo-regenerator
