CV-Badminton-Matches

AI CUP 2023 - Teaching Computers to Watch Badminton Matches

Awards: https://global.turingcerts.com/en/co/cert?hash=0x542087a0cba32a7e5cd03330a9bb02c46ba0fe8a437f0ec52ecf60b1274260780000

Model Architecture

Install

1. Run install_pytorch.sh or install the version you like
2. Run install_mm.sh or manually install MMDetection and MMPose
3. Run install_tracknetv2.sh or manually install TrackNetv2

Training Procedure

1. Background Extraction (1_background_extraction.py)
2. Background Clustering (2_background_clustering.py)
3. Ball Detection (3_ball_processing.py)
4. Player Pose Detection (4_pose_detection_*.py)
5. Train models for each columns (5_train_*.py)

Predicting Procedure

Predict answers of each columns by each models (6_predict_*.py) step by step

Ideas

Court Detection

(turned out to be unnecessary)

1. Edge detection (Canny): X
2. Homography: X
3. DIY: O

Background Extraction

1. DIY - "average_method": X
2. DIY - "mode_method": X
3. DIY - "average_method_with_masked_players": O

Ball Detection

1. Blob detection: X
2. TrackNetv2: X
3. TrackNetv2 + postprocess: O

Player Pose Detection

(Backgound Extraction finished needed)

• MMDetection + MMPose

Others

More content in my report but in Chinese version