Tennis Court Registration

Tennis Registration v3 Prepare the environment DeepSORT environment cd YOLOv9_DeepSORT pip install -r requirements.txt YOLOv9 environment cd yolov9 pip install -r requirements.txt UI environment (cpp-OpenCV & sysv_ipc) cpp-OpenCV v4.7.0 in Ubuntu (Here is the tutorial) pip install sysv_ipc Demo You can use the code below to simply run the demo. python tennis_registration.py After running all frames, you will see the result in the terminal. This is the position of every player in the image coordinate. [[ 31.76 8.2214] [ 22.868 10.646] [ 11.693 7.4278] [ 6.3028 9.9999]] Or if you want to see the result, you can run the ui at the same time. cd ui ./shr_tennis_ui Then you will see like the image below. Usage You can use your own params to run the program with the code below. python tennis_registration.py --video <str> --conf <float 0~1> --blur_id <int> --class_id <int> --cam_id <int> Params If you just simply test its performance in different perspectives, just change its video and cam_id params. Params Function Default video Path to input video or video stream (input ‘0’) ‘./data/video_3.mp4’ conf confidence threshold 0.50 blur_id class ID to apply Gaussian Blur None class_id class ID to track 0 cam_id camera perspective ID to track 3 Supplements ① Stream Mode If you need to use Stream Mode, pls apply this two code in tennis_registration.py after you connect the camera. Then input ‘0’ to video param. And don’t forget to change a correct camera index to calculate homography matrix. (You can rewrite cam_dict in object_tracking_stream to fix the correspondence between cameras and indexs) # from YOLOv9_DeepSORT.yolov9.object_tracking_stream import person_track_stream # person_track_stream(FLAGS) Because I cannot connect my computer with cameras in the stadium, I commented them out while debugging the code. (If there are bugs when using Stream Mode, pls contact me…) ② Differences between object_tracking_stream and object_tracking The code of video stream is in object_tracking_stream.py, and the code of video file is in object_tracking.py They use different methods to get frames: class PYLON_SHM and VideoCapture function in OpenCV. ③ Video samples and cam_id The indexs of videos in the data folder are corresponding to the indexs of cameras. video: video_0.mp4 -> cam_id: 0 video: video_1.mp4 -> cam_id: 1 video: video_2.mp4 -> cam_id: 2 video: video_3.mp4 -> cam_id: 3 References YOLOv9_DeepSORT Learn Homography: 相机标定系列（二）单应矩阵 Homography Applcation: OpenCV-Python单应矩阵（Homography Matrix）应用——更换广告牌

Aug 5, 2024