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This project forked from elifkcontar/proj
Code for extraction of asymmetry, border and other features is already available in Matlab (ask Veronika), needs to be translated to Python so that we can reproduce the results
Create functions which allow switching to different features. In bad pseudocode:
function train_network(feature_type)
% feature_type is a string, like "none", "asymmetry", "border", etc.
% For "none", a classification only network is trained
% For any others, load the .csv file with the required feature values, and train a multi-task network.
% Save the trained model
end
Same for test_network(feature_type). Load model, test it and save the predictions (probabilities per image).
The issue is done when at least: 1. all parts have the new layout, 2. for each part a Jupyter notebook with documentation is present, and 3. the code able to produce the results described in Elif’s report
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