Skip to content
This repository has been archived by the owner on Oct 20, 2022. It is now read-only.

Winners of the 2022 DeepSportRadar human instance segmentation challenge

License

Notifications You must be signed in to change notification settings

DeepSportradar/2022-winners-instance-segmentation-challenge

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

The code for ACM MMSports'22 Instance Segmentation challenge. The details are presented in our technical report.

The code is based on mmdetection and CBNetV2.

ACM MMSports'22 Instance Segmentation second challenge

setup environments

sh pre.sh

train model with multi-gpus

nohup bash tools/dist_train.sh configs/mmsports2022/exp02.py 4 >> /lengyu.yb/logs/mmsports2022/exp07.log 2>&1 &

swa model with multi-gpus

nohup bash tools/dist_train.sh configs/mmsports2022/exp02_swa.py 4 >> /lengyu.yb/logs/mmsports2022/exp07_swa.log 2>&1 &

Our training logs and config are shown in weights folder

inference

bash tools/dist_test.sh configs/mmsports2022/exp02.py /lengyu.yb/logs/mmsports2022/exp07_swa/swa_model_148_mms.pth 4

generate standard submission format

python scripts/gen_standard_submission.py

evaluate on test set

python evaluate.py /lengyu.yb/datasets/segmentation/MMSports22/basketball-instants-dataset/annotations/test.json ./submission/submission.segm json ./

About

Winners of the 2022 DeepSportRadar human instance segmentation challenge

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 65.0%
  • Jupyter Notebook 34.3%
  • C++ 0.2%
  • Cython 0.2%
  • C 0.2%
  • Shell 0.1%