39 lines
2.7 KiB
Markdown
39 lines
2.7 KiB
Markdown
# SOLOv2 for instance segmentation
|
|
|
|
## Introduction
|
|
|
|
SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framework with strong performance. We reproduced the model of the paper, and improved and optimized the accuracy and speed of the SOLOv2.
|
|
|
|
**Highlights:**
|
|
|
|
- Training Time: The training time of the model of `solov2_r50_fpn_1x` on Tesla v100 with 8 GPU is only 10 hours.
|
|
|
|
## Model Zoo
|
|
|
|
| Detector | Backbone | Multi-scale training | Lr schd | Mask AP<sup>val</sup> | V100 FP32(FPS) | GPU | Download | Configs |
|
|
| :-------: | :---------------------: | :-------------------: | :-----: | :--------------------: | :-------------: | :-----: | :---------: | :------------------------: |
|
|
| YOLACT++ | R50-FPN | False | 80w iter | 34.1 (test-dev) | 33.5 | Xp | - | - |
|
|
| CenterMask | R50-FPN | True | 2x | 36.4 | 13.9 | Xp | - | - |
|
|
| CenterMask | V2-99-FPN | True | 3x | 40.2 | 8.9 | Xp | - | - |
|
|
| PolarMask | R50-FPN | True | 2x | 30.5 | 9.4 | V100 | - | - |
|
|
| BlendMask | R50-FPN | True | 3x | 37.8 | 13.5 | V100 | - | - |
|
|
| SOLOv2 (Paper) | R50-FPN | False | 1x | 34.8 | 18.5 | V100 | - | - |
|
|
| SOLOv2 (Paper) | X101-DCN-FPN | True | 3x | 42.4 | 5.9 | V100 | - | - |
|
|
| SOLOv2 | R50-FPN | False | 1x | 35.5 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0/configs/solov2/solov2_r50_fpn_1x_coco.yml) |
|
|
| SOLOv2 | R50-FPN | True | 3x | 38.0 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0/configs/solov2/solov2_r50_fpn_3x_coco.yml) |
|
|
|
|
**Notes:**
|
|
|
|
- SOLOv2 is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
|
|
- SOLOv2 training performace is dependented on Paddle develop branch, performance reproduction shoule based on [Paddle daily version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) or Paddle 2.0.1(will be published on 2021.03), performace will loss slightly is training base on Paddle 2.0.0
|
|
|
|
## Citations
|
|
```
|
|
@article{wang2020solov2,
|
|
title={SOLOv2: Dynamic, Faster and Stronger},
|
|
author={Wang, Xinlong and Zhang, Rufeng and Kong, Tao and Li, Lei and Shen, Chunhua},
|
|
journal={arXiv preprint arXiv:2003.10152},
|
|
year={2020}
|
|
}
|
|
```
|