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martindgr/make_masks
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Current workflow to make masks:
1. Run slice_no_repeats.py to cut up large images with random crops
2. Run make_NN_dataset.py to randomly select some of those images and sort them into directories for NN input
3. Run draw_mask.py (annotate_dir() to do a dataset directory) to make labels for images and save them in correct folders with correct names
4. (train neural net)
5. Run find_centroids.py to get PMT and bolt locations
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Colour in masks with capacity for 3 classes
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