# PanopticSegmentation

**Repository Path**: itking666/PanopticSegmentation

## Basic Information

- **Project Name**: PanopticSegmentation
- **Description**: PKU_360 Team's fuse code! This code is used to fuse the semantic segmentation result and instance segmentation result. We won the third place in COCO2018 panoptic segmentation.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-25
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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](https://github.com/cocodataset/panopticapi), 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](http://presentations.cocodataset.org/ECCV18/COCO18-Panoptic-PKU_360.pdf). 


## 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](https://github.com/cocodataset/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!**