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@jordancorser
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Keras implementation of the VQ-VAE algorithm, using a PixelCNN to provide generative capacity. Trained to operate on the OASIS dataset, with SSIM of approx. 0.9 for all tested images.

…tent space size, adjusted epochs and implemented plotting of training losses and of the latent space for test images.
…ng to train new models, copied an open-source PixelCNN implementation - yet to optimise or adjust
…ll input sizes, however cannot be trained on the full train set
…ision. Trained PixelCNN, but sampling is unimplemented
@SiyuLiu0329
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This is an initial inspection, no action is required at this point

  • commit messages: OK
  • reconstruction: OK
  • image gen: OK
  • code commenting: OK

@shakes76
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Good Practice (Design/Commenting, TF/Torch Usage)

Adequate use and implementation
Good spacing and comments
Header blocks missing -1

Recognition Problem

Solves problem (poor generations) -1
Driver Script present
File structure present
Shows Usage & Demo & Visualisation & Data usage
Module present
Commenting
No Data leakage
Difficulty: Hard

Commit Log

Meaningful commit messages
Progressive commits used

Documentation

ReadMe acceptable/good
Good Description and Comments
Markdown used PDF submitted

Pull Request

Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch)
Feedback required, remove model weights and checkpoints. Undo changes to other students files -2
Request Description OK, could use more info -1

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4 participants