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https://github.com/chychen/basketballgan

Basketball coaches often sketch plays on a whiteboard to help players get the ball through the net. A new AI model predicts how opponents would respond to these tactics.

https://github.com/chychen/basketballgan

Science Score: 10.0%

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
    Links to: arxiv.org
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    Scientific vocabulary similarity
    Low similarity (8.3%) to scientific vocabulary

Keywords

acmmm2019 ai basketball deep-learning gan human-computer-interaction sport
Last synced: 5 months ago · JSON representation

Repository

Basketball coaches often sketch plays on a whiteboard to help players get the ball through the net. A new AI model predicts how opponents would respond to these tactics.

Basic Info
Statistics
  • Stars: 51
  • Watchers: 6
  • Forks: 5
  • Open Issues: 3
  • Releases: 0
Topics
acmmm2019 ai basketball deep-learning gan human-computer-interaction sport
Created over 6 years ago · Last pushed almost 3 years ago
Metadata Files
Readme

README.md

BasketballGAN

Generate the ghosting defensive strategies given offensive sketch.


Paper | CGVLab
Video | Supplemental

BasketballGAN: Generating Basketball Play Simulation through Sketching

Hsin-Ying Hsieh1, Chieh-Yu Chen2, Yu-Shuen Wang1 and Jung-Hong Chuang1

1National Chiao Tung University,

2NVIDIA Corporation

Accepted paper in ACMMM 2019.

Prerequisites

Getting Stated

bash ~$ git clone https://github.com/chychen/BasketballGAN.git ~$ cd BasketballGAN BasketballGAN$ docker login nvcr.io BasketballGAN$ docker pull nvcr.io/nvidia/tensorflow:19.06-py2 BasketballGAN$ docker run --runtime=nvidia -it --rm -v $PWD:$PWD --net host nvcr.io/nvidia/tensorflow:19.06-py2 bash root@c63207c81408:~/BasketballGAN$ apt update root@c63207c81408:~/BasketballGAN$ apt install ffmpeg

Download Dataset

  • create 'data' folder
  • save dataset under folder 'data'

bash BasketballGAN$ mkdir data

Training

bash BasketballGAN$ cd src BasketballGAN/src$ python Train_Triple.py --folder_path='tmp' --data_path='data'

Logs/Samples/Checkpoints

bash - "BasketballGAN/src/tmp/Log": training summary for tensorboard. - "BasketballGAN/src/tmp/Samples": generated videos sampled on different epoches. - "BasketballGAN/src/tmp/Checkpoints": tensorflow checkpoints on different iterations.

Monitoring

bash BasketballGAN/src$ python -m http.server 8000

bash BasketballGAN/src$ tensorboard --logdir='tmp/Log'

Public Relations

Citation

If you find this useful for your research, please use the following.

@article{hsieh2019basketballgan, title={BasketballGAN: Generating Basketball Play Simulation Through Sketching}, author={Hsieh, Hsin-Ying and Chen, Chieh-Yu and Wang, Yu-Shuen and Chuang, Jung-Hong}, journal={arXiv preprint arXiv:1909.07088}, year={2019} }

Owner

  • Name: Jay Chen
  • Login: chychen
  • Kind: user
  • Location: Taiwan

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