PanopticSegmentation

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.

Requirements

• Anaconda3 (we highly recommend！)
• pycocotools

File Organization

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

Usage

Generate Two-Channel-Pngs

• for val dataset

python tools/cal_panoptic.py

• for test dataset

python tools/cal_panoptic.py -t

Evaluation

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!