Inference model is based on Resnet101 backbone and is pre-trained on MS COCO dataset.
Code is intended to work with Python 3.6.x
, it hasn't been tested with previous version. This code can run on CPU/GPU backend.
pip install -r requirements.txt
python3 mask_generate.py --image_dir ./images --out_dir ./masks
You can also specify which type of objects to segment out here object_list = ['car', 'truck'].
Code is heavily borrowed from this repository : https://github.com/matterport/Mask_RCNN
I merely created a simple wrapper around it.