Sports Gesture Classification on Docker

Overview

• This is an API for sports gesture image classification

• Features

  • The model use Swin Transformer (accuracy = 80% on validation dataset)
  • Run training and flask API on Docker container
  • Provide onnx (CPU device)

• Demo https://youtu.be/2DWbemtVgis

Run

• Build a docker based on DockerFile
• Train: bash train.sh
• Flask api: bash api.sh
  • Browser: http://localhost:12000/

Dataset

Kaggle Sports Gesture

• Classes: 100
• Size: 224 X224 X 3
• Format: .jpg
• Number of images: 14572 (train: 4572 , valid: 500, test: 500)

Train

The training code is from Kaggle Sports Gesture Competition: SwinTransformer from Timm

python3 train.py --config {config_file}

• Check the process on Tensorboard: tensorboard --logdir = sports_api

Run on Docker

Steps about Run on Docker

Refer

1. Inspired from sportsnoma classification: https://www.youtube.com/watch?v=Kzrfw-tAZew https://github.com/abhishekkrthakur/sportsnoma-deep-learning
2. Kaggle: Sports Gesture Classification
3. Kaggle Sports Gesture Competition: SwinTransformer from Timm
4. Pytest on Flask API