Hey!
Instructions to run the code:
Requires numpy, opecv-python, imutils. These can be installed by:
pip install numpy
pip install opencv-python
pip install imutils
To run:
python yolo_opencv.py -i hockey-1.png -c yolo.cfg -w yolov3.weights -cl classes.txt
python yolo_video_opencv.py -i cv-hockey-1.mp4 -y .\ -o test.mp4
https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2
./darknet detector train cfg/player6-obj.data cfg/player6-yolov3-tiny.cfg darknet53.conv.74
- "an open source platform that can injest broadcast footage of hockey games and output player mappings as well as other useful information harvested from these frames."
Fast and Reliable Detection of Hockey Players
Self-Learning for Player Localization in Sports Video
Learning to Track and Identify Players from Broadcast Sports Videos
Automatic Acquisition of Motion Trajectories: Tracking Hockey Players
Pose Estimation of Players in Hockey Videos using Convolutional Neural Networks