This repo provides the code to combine the semantic and instance segmentation predictions for panoptic segmentation two-channel-pngs output. Compared with the official version, it tries to solve occlusion problems and takes some object relationships into account, according to the method of the third place winner in the COCO2018 panoptic segmentation competition. A detailed description can be found here.
- Anaconda3 (we highly recommend！)
- pycocotools
I advise you to organize you file in the following ways.
PanopticSegmentation
├─files
├─annotations
|─detresults
You can form the file organization by the tools generate_file_organization.py. It will generate the file structure automatically.
cd REPO_ROOT_DIR
python tools/generate_file_organization.py
- annotations: store annotation files like panoptic_val2017.json and instances_val2017.json
- detresults: store instance segmentation result which is stored in a json file
- for val dataset
python tools/cal_panoptic.py
- for test dataset
python tools/cal_panoptic.py -t
The evaluation code is from the official panopticapi
If you want to evaluate the result after generating two-channel-pngs automatically, just need to add '-e'. If the two-channel-pngs have been generated and you only want to evaluate, then just add '-sc'.
- for val dataset
python tools/cal_panoptic.py -e # generate two-channel-pngs and automatically evaluate the result.
- for test dataset
python tools/cal_panoptic.py -sc # only run evaluation.
If you have any question, just leave an issue!