{"id":19086707,"url":"https://github.com/abhroroy365/tennis-tracker","last_synced_at":"2025-04-14T01:51:45.101Z","repository":{"id":233250944,"uuid":"786354687","full_name":"abhroroy365/Tennis-Tracker","owner":"abhroroy365","description":"This project utilizes OpenCV, YOLO and CNN to track the position, movement of players in a video. YOLOv8 is used to track the players. YOLOv5 is used to track the position of tennis ball at every frame of the video. ResNet34 is fine-tuned to detect the court keypoints.","archived":false,"fork":false,"pushed_at":"2024-04-14T08:06:34.000Z","size":38488,"stargazers_count":10,"open_issues_count":0,"forks_count":5,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-14T01:51:40.176Z","etag":null,"topics":["computer-vision","deep-learning","opencv","pytorch","tennis-game","yolov5"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/abhroroy365.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-04-14T07:39:12.000Z","updated_at":"2025-04-07T19:59:28.000Z","dependencies_parsed_at":"2024-04-15T07:29:59.562Z","dependency_job_id":null,"html_url":"https://github.com/abhroroy365/Tennis-Tracker","commit_stats":null,"previous_names":["abhroroy365/tennis-tracker"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhroroy365%2FTennis-Tracker","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhroroy365%2FTennis-Tracker/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhroroy365%2FTennis-Tracker/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhroroy365%2FTennis-Tracker/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abhroroy365","download_url":"https://codeload.github.com/abhroroy365/Tennis-Tracker/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248809023,"owners_count":21164895,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-vision","deep-learning","opencv","pytorch","tennis-game","yolov5"],"created_at":"2024-11-09T03:00:19.160Z","updated_at":"2025-04-14T01:51:45.067Z","avatar_url":"https://github.com/abhroroy365.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Tennis Match Tracker\n\nThis project utilizes OpenCV, YOLO and CNN to track the position, movement of players in a video. YOLOv8 is used to track the players. YOLOv5 is used to track the position of tennis ball at every frame of the video. ResNet34 is fine-tuned to detect the court keypoints. \n\n# Weights\n\nDownload the pretrained weights\n\nhttps://drive.google.com/file/d/11oPP9h-lVfuOv09RFt0mmvydy4-maTjV/view?usp=sharing, \n\nhttps://drive.google.com/file/d/1iGQMabajjVm_MbUlCXJDnslnLmYvgleX/view?usp=sharing, \n\nhttps://drive.google.com/file/d/1ihueDeTl2XiYDiVMYBKpGygnBMG91pIW/view?usp=sharing\n\n\n## Screenshots\n\n![Demo output](https://github.com/abhroroy365/Tennis-Tracker/blob/master/output/output_video.gif)\n\n\n## Run Locally\n\nClone the project\n\n```bash\n  git clone https://github.com/abhroroy365/Tennis-Tracker.git\n```\n\nGo to the project directory\n\n```bash\n  cd Tennis-Tracker\n```\n\nCreate virtual environment\n\n```bash\n  python -m venv env\n```\nActivate the virtual environment\n\n```bash\n  env\\Scripts\\activate\n```\n\nInstall dependencies\n```bash\n  pip install -r requirements.txt\n```\n\nFor training (no need, weights alrady provided)\n\n```bash\n  python .\\training\\train.py\n```\n\nFor running the tracker on your video\n```bash\n  python run-tracker.py\n```\n\n## 🛠 Skills\nPytorch, OpenCV, YOLO, Python, Computer Vision\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhroroy365%2Ftennis-tracker","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhroroy365%2Ftennis-tracker","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhroroy365%2Ftennis-tracker/lists"}