Skip to content

Latest commit

 

History

History
88 lines (69 loc) · 3.22 KB

README.md

File metadata and controls

88 lines (69 loc) · 3.22 KB
Raw

SOLOv2: Dynamic and Fast Instance Segmentation

SOLOv2: Dynamic and Fast Instance Segmentation,
Xinlong Wang, Rufeng Zhang, Tao Kong, Lei Li, Chunhua Shen
In: Proc. Advances in Neural Information Processing Systems (NeurIPS), 2020
arXiv preprint (arXiv 2003.10152)

Installation & Quick Start

First, follow the default instruction to install the project and datasets/README.md set up the datasets (e.g., MS-COCO).

For demo, run the following command lines:

wget https://cloudstor.aarnet.edu.au/plus/s/chF3VKQT4RDoEqC/download -O SOLOv2_R50_3x.pth
python demo/demo.py \
    --config-file configs/SOLOv2/R50_3x.yaml \
    --input input1.jpg input2.jpg \
    --opts MODEL.WEIGHTS SOLOv2_R50_3x.pth

For training on COCO, run:

OMP_NUM_THREADS=1 python tools/train_net.py \
    --config-file configs/SOLOv2/R50_3x.yaml \
    --num-gpus 8 \
    OUTPUT_DIR training_dir/SOLOv2_R50_3x

For evaluation on COCO, run:

OMP_NUM_THREADS=1 python tools/train_net.py \
    --config-file configs/SOLOv2/R50_3x.yaml \
    --eval-only \
    --num-gpus 8 \
    OUTPUT_DIR training_dir/SOLOv2_R50_3x \
    MODEL.WEIGHTS training_dir/SOLOv2_R50_3x/model_final.pth

Models

COCO Instance Segmentation Baselines with SOLOv2

Name inf. time train. time Mem box AP mask AP download
SOLOv2_R50_3x 47ms ~25h(36 epochs) 3.7GB - 37.6 model
SOLOv2_R101_3x 61ms ~30h(36 epochs) 4.7GB - 39.0 model

Disclaimer:

  • All models are trained with multi-scale data augmentation.
  • Inference time is measured on a single V100 GPU. Training time is measured on 8 V100 GPUs.
  • This is a reimplementation. Thus, the numbers are slightly different from our original paper (within 0.3% in mask AP).
  • The implementation on mmdetection is available at https://github.com/WXinlong/SOLO.

Citations

Please consider citing our papers in your publications if the project helps your research. BibTeX reference is as follows.

@inproceedings{wang2020solo,
  title     =  {{SOLO}: Segmenting Objects by Locations},
  author    =  {Wang, Xinlong and Kong, Tao and Shen, Chunhua and Jiang, Yuning and Li, Lei},
  booktitle =  {Proc. Eur. Conf. Computer Vision (ECCV)},
  year      =  {2020}
}

@inproceedings{wang2020solov2,
  title   =  {{SOLOv2}: Dynamic and Fast Instance Segmentation},
  author  =  {Wang, Xinlong and Zhang, Rufeng and Kong, Tao and Li, Lei and Shen, Chunhua},
  booktitle =  {Proc. Advances in Neural Information Processing Systems (NeurIPS)},
  year    =  {2020}
}
@article{wang2021solo,
  title   =  {{SOLO}: A Simple Framework for Instance Segmentation},
  author  =  {Wang, Xinlong and Zhang, Rufeng and Shen, Chunhua and Kong, Tao and Li, Lei},
  journal =  {IEEE T. Pattern Analysis and Machine Intelligence (TPAMI)},
  year    =  {2021}
}