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--- |
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license: mit |
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language: |
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- en |
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metrics: |
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- accuracy |
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pipeline_tag: unconditional-image-generation |
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tags: |
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- art |
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--- |
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# Photo Regenerator w/Diffusion Denoiser Model |
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Incrementally adds noise over a series of steps via a noise scheduler, and feeds images through |
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a CNN to learn features/patterns to then "regenerate" the image. |
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The `.ipynb` holds the tests and download of the dataset if needed. |
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## Goals: |
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- **Denoise a 25-step noisy image (Blurry)** |
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- Denoise a 100-step noisy image |
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- Denoise a 500-step noisy image |
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- Denoise a 1000-step noisy image |
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**Dataset Used: COCO 2017** |
