mmdetection/configs/panoptic_fpn/README.md

# Panoptic feature pyramid networks
## Introduction

<!-- [ALGORITHM] -->
The base method for panoptic segmentation task.

```
@inproceedings{kirillov2018panopticfpn,
  author = {
    Alexander Kirillov,
    Ross Girshick,
    Kaiming He,
    Piotr Dollar,
  },
  title = {Panoptic Feature Pyramid Networks},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019}
}
```

## Dataset

PanopticFPN requires COCO and [COCO-panoptic](http://images.cocodataset.org/annotations/panoptic_annotations_trainval2017.zip) dataset for training and evaluation. You need to download and extract it in the COCO dataset path.
The directory should be like this.

```none
mmdetection
├── mmdet
├── tools
├── configs
├── data
│   ├── coco
│   │   ├── annotations
│   │   │   ├── panoptic_train2017.json
│   │   │   ├── panoptic_train2017
│   │   │   ├── panoptic_val2017.json
│   │   │   ├── panoptic_val2017
│   │   ├── train2017
│   │   ├── val2017
│   │   ├── test2017
```

## Results and Models

| Backbone      | style      | Lr schd | Mem (GB) | Inf time (fps) | PQ   |  SQ  |  RQ  | PQ_th | SQ_th | RQ_th | PQ_st | SQ_st | RQ_st | Config | Download |
|:-------------:|:----------:|:-------:|:--------:|:--------------:|:----:|:----:|:----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:------:|:--------:|
| R-50-FPN      | pytorch    | 1x      |   4.7    |                | 40.2 | 77.8 | 49.3 | 47.8  | 80.9  | 57.5  | 28.9  | 73.1  | 37.0  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/panoptic_fpn/panoptic_fpn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r50_fpn_1x_coco/panoptic_fpn_r50_fpn_1x_coco_20210821_101153-9668fd13.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r50_fpn_1x_coco/panoptic_fpn_r50_fpn_1x_coco_20210821_101153.log.json) |
| R-50-FPN      | pytorch    | 3x      |   -      |     -          | 42.5 | 78.1 | 51.7 | 50.3  | 81.5  | 60.3  | 30.7  | 73.0  | 38.8  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/panoptic_fpn/panoptic_fpn_r50_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r50_fpn_mstrain_3x_coco/panoptic_fpn_r50_fpn_mstrain_3x_coco_20210824_171155-5650f98b.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r50_fpn_mstrain_3x_coco/panoptic_fpn_r50_fpn_mstrain_3x_coco_20210824_171155.log.json) |
| R-101-FPN     | pytorch    | 1x      |   6.7    |                | 42.2 | 78.3 | 51.4 | 50.1  | 81.4  | 59.9  | 30.3  | 73.6  | 38.5  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/panoptic_fpn/panoptic_fpn_r101_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r101_fpn_1x_coco/panoptic_fpn_r101_fpn_1x_coco_20210820_193950-ab9157a2.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r101_fpn_1x_coco/panoptic_fpn_r101_fpn_1x_coco_20210820_193950.log.json) |
| R-101-FPN     | pytorch    | 3x      |   -      |     -          | 44.1 | 78.9 | 53.6 | 52.1  | 81.7  | 62.3  | 32.0  | 74.6  | 40.3  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/panoptic_fpn/panoptic_fpn_r101_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r101_fpn_mstrain_3x_coco/panoptic_fpn_r101_fpn_mstrain_3x_coco_20210823_114712-9c99acc4.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/panoptic_fpn/panoptic_fpn_r101_fpn_mstrain_3x_coco/panoptic_fpn_r101_fpn_mstrain_3x_coco_20210823_114712.log.json) |