vm7608/ai4life

Apply VideoMAE for gym workout/exercise video classification (4th place in AI4LIFE 2024 - Personal Trainer Competition)

11

stars

6

commits

Python

primary language

May 12, 2024

updated

README

Team KIKIKIKI - AI4LIFE 2024 - Personal Trainer Solution (Updating...)

A video classification project that aims to classify different types of workouts or exercises performed by a person in a video. Our project got the consolation prize (4th place) in the AI4LIFE 2024 competition organized by the Da Nang University of Science and Technology (DUT).

Solution Description:

  • Model: VideoMAE.
  • Training is supported by Hugging Face.
  • Data: You can download our data from Kaggle dataset here.
  • Detail solution: will be updated soon at my blog here.

Project Structure:

  • data/: contains the tsv files for training.
  • scripts/: contains the scripts for dowloading model and test data.
  • notebooks/: contains the notebooks for submitting the project.
  • src/: contains the source code of the project (training, evaluation, inference, etc.).
  • streamlit/: contains the streamlit app for the project.
  • tools/: contains the tools for the project (data processing, labeling, etc.).

Team Members:

  • Cao Kieu Van Manh
  • Tran Dinh Minh Khoa

Contributors

mkhoatd

4 commits

vm7608

2 commits

vm7608/ai4life

Apply VideoMAE for gym workout/exercise video classification (4th place in AI4LIFE 2024 - Personal Trainer Competition)

11

stars

6

commits

Python

primary language

May 12, 2024

updated

README

Team KIKIKIKI - AI4LIFE 2024 - Personal Trainer Solution (Updating...)

A video classification project that aims to classify different types of workouts or exercises performed by a person in a video. Our project got the consolation prize (4th place) in the AI4LIFE 2024 competition organized by the Da Nang University of Science and Technology (DUT).

Solution Description:

  • Model: VideoMAE.
  • Training is supported by Hugging Face.
  • Data: You can download our data from Kaggle dataset here.
  • Detail solution: will be updated soon at my blog here.

Project Structure:

  • data/: contains the tsv files for training.
  • scripts/: contains the scripts for dowloading model and test data.
  • notebooks/: contains the notebooks for submitting the project.
  • src/: contains the source code of the project (training, evaluation, inference, etc.).
  • streamlit/: contains the streamlit app for the project.
  • tools/: contains the tools for the project (data processing, labeling, etc.).

Team Members:

  • Cao Kieu Van Manh
  • Tran Dinh Minh Khoa

Contributors

mkhoatd

4 commits

vm7608

2 commits

Languages

Python

75.8%

Jupyter Notebook

23.8%