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Download dataset from Kaggle and place it inside repository directory.
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Launch script for converting wav to jpg (by default it's using all your cpu threads, but you can change it inside code).
python wav2jpg.py
After this you got my_dataset.csv with jpg filename, target. Now you need to split it to train.csv and test.csv
3.1 For training CNN
python train.py
3.2 Make prediction for submission
python inference.py
4 Clusterization binary images with k-means. Got only 0.415. I think, we need to reduce number of features, here i have 1d array with size 128x72 = 9216. Maybe we can apply here linear transformation, just like in neural networks.
python kmeans_images.py