Training on custom dataset with (multi/unique class) of a Mask RCNN
python3
pycocotools
matplotlib
mrcnn
tqdm
numpy
pylab
skimage
Note: installation for mrcnn will be explained in the medium article linked in the repo.
- dataset: folder where you put the train and val folders (read inside to know what to put)
- logs: folder where we store the intermediate/checkpoints and final weights after training
- weights: weights for the model, we fetch the weights from here for the test script
- detect_segment_test.py: test script for the segmentation, displays mask on top of input image, usage given by --h argument
- train.py: main script for this section, read medium article to know what to modify
First training usage, more options showed in the train.py script as comment:
python3 train.py train --dataset=./dataset --weights=coco