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Topic recognition #443
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base: topic-recognition
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Topic recognition #443
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Didn't make any changes yet but these files were apparently changed after only cloning
Generating the files and preparing to get started after choosing my topic
…nd including the VQ-VAE based heavily on the cited GitHub. Started work on the README.MD
…oader for numpy arrays
…reconstructed vs original images
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This is an initial inspection, no action is required at this point
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Good Practice (Design/Commenting, TF/Torch Usage)Adequate use and implementation (some errors prevented it from working, partially working) -3 Recognition ProblemSolves problem (some outputs missing) -2 Commit LogMeaningful commit messages DocumentationReadMe acceptable Pull RequestSuccessful Pull Request (Working Algorithm Delivered on Time in Correct Branch) |
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I see that I need to undo/revert changes to other student files. I don't remember making those changes I think it might have happened from having some kind of inconsistency between my version and the public version when I submitted the pull request. For fixing these changes should I just edit the files so they are identical to the other students ones? |
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I've attempted to get rid of my changes to other students read me and even after copying and pasting from origin and attempting |
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Seems the student files still showing up as changed. Can you check again. I will grant the Feedback marks, because you did attempt to solve it, but can't merge until you do fix it. |
Hiya,
This pull request is for an implementation of problem 8 (Create a generative model of one of the OASIS brain,
ADNI brain or the OAI AKOA knee data set(see Appendix for links) using a VQVAE [11] or VQVAE2 [12] that has a “reasonably clear image” and a Structured Similarity (SSIM) of over 0.6)Please find contained within
interface.ipynbcontaining the main interface for interacting with my modelsREADME.mdcontaining information on how the models work together including how to use the models yourselfdataset.pycontaining the code used to implement the various datasets and data loaders used throughoutpredict.pycontaining the code for generating new imagestrain.pycontaining the code used for the training loops for the various modelsenvironment.ymlcontaining the environment used during the creation of this projectimages/*.pngcontaining the images used in the READMEmodules/*.pycontaining the various models used in this projectmodules.decoder.pydecoder implementationmodules.encoder.pyencoder implementationmodules.quantizer.pyvector quantizer implementationmodules.stack.pyimplementation for the stacked residual layers used by other modulesmodules.vqvae.pyVQ-VAE implementationmodules.pixelcnn.pypixel cnn implementationThank you for your time taken to review and hope for feedback.
Alex Viller,
45375325