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Platygator/mmsegmentation

 
 

Train a deeplabV3+ model on the simulated boulder data set

Starting from scratch

python pipeline/train_boulder_segmentation.py -f

Loading a specific checkpoint version

python pipeline/train_boulder_segmentation.py -c /path/to/.pth

If no argument is given the training continues from "workdir/latest.pth"

Testing all images in the test set

python pipeline/test_boulder_segementation.py --show-dir /data/results
 --eval mIou -p /path/to/.pth

all arguments optional. If no checkpoint file (-p) is given "workdir/latest.pth" is used.

Infering for a single image (hardcoded as this is a template and shall be used in ROS later)

python pipeline/test_boulder_segementation.py --show-dir /data/results
 --eval mIou -p /path/to/.pth

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OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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