{"id":28563721,"url":"https://github.com/kr1shnasomani/sportiq","last_synced_at":"2026-02-28T11:36:12.129Z","repository":{"id":292370379,"uuid":"977013035","full_name":"kr1shnasomani/Sportiq","owner":"kr1shnasomani","description":"Player and ball tracking map for Tennis.","archived":false,"fork":false,"pushed_at":"2025-09-18T21:49:10.000Z","size":51030,"stargazers_count":4,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-18T23:55:26.144Z","etag":null,"topics":["ball-tracking","computer-vision","deep-learning","neural-network","player-tracking"],"latest_commit_sha":null,"homepage":"","language":"Python","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/kr1shnasomani.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,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-05-03T08:15:22.000Z","updated_at":"2025-09-18T21:49:15.000Z","dependencies_parsed_at":"2025-05-09T15:58:08.645Z","dependency_job_id":null,"html_url":"https://github.com/kr1shnasomani/Sportiq","commit_stats":null,"previous_names":["kr1shnasomani/sportiq"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/kr1shnasomani/Sportiq","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kr1shnasomani%2FSportiq","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kr1shnasomani%2FSportiq/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kr1shnasomani%2FSportiq/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kr1shnasomani%2FSportiq/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kr1shnasomani","download_url":"https://codeload.github.com/kr1shnasomani/Sportiq/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kr1shnasomani%2FSportiq/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29931958,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-28T09:58:13.507Z","status":"ssl_error","status_checked_at":"2026-02-28T09:57:57.047Z","response_time":90,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["ball-tracking","computer-vision","deep-learning","neural-network","player-tracking"],"created_at":"2025-06-10T13:07:55.767Z","updated_at":"2026-02-28T11:36:12.084Z","avatar_url":"https://github.com/kr1shnasomani.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eSportiq\u003c/h1\u003e\n\u003cp align=\"center\" style=\"margin-top:30px;\"\u003e\n  \u003cimg src=\"https://github.com/user-attachments/assets/34e9b4e7-a768-4143-b819-fc726dbf96d3\" height=\"150cm\"/\u003e\n\u003c/p\u003e\nThe project is designed for player and ball tracking in tennis. It processes video input to detect court boundaries, track player movements, and map ball trajectories, utilizing computer vision techniques, Mediapipe, and a custom ball detection model for accurate analysis and visualization.\n\n## Repository Structure:\nThe following is the structure of the repository:\n```\nSportiq\n├── code/\n│   ├── BallDetection.py\n│   ├── BallMapping.py\n│   ├── BallTrackNet.py\n│   ├── BodyTracking.py\n│   ├── CourtDetection.py\n│   ├── CourtMapping.py\n│   └── TraceHeader.py\n├── dataset/\n│   └── input.mp4\n├── model/\n│   └── TrackNet-Model.md\n├── output/\n│   └── output.mp4\n├── README.md\n└── requirements.txt\n```\n\n## Execution Guide:\n1. Clone the repository:\n   ```\n   git clone https://github.com/kr1shnasomani/Sportiq.git\n   cd Sportiq\n   ```\n   \n2. Install the dependencies:\n   ```\n   pip install -r requirements.txt\n   ```\n\n3. In the following files, replace the path with yours:\n   - `CourtDetection.py` - line 13, enter root directory\n   - `TraceHeader.py` - line 4, enter the input video path\n  \n4. Download the TrackNet model from **https://raw.githubusercontent.com/hgupt3/TRACE/main/TrackNet/Weights.pth** and rename the model to `TrackNet.pth`\n\n5. Run the project:\n   \n   You will need to run the `CourtDetection.py` script to run thei entire project:\n   ```\n   /usr/bin/python3 /Users/krishnasomani/Documents/Projects/Sportiq/code/CourtDetection.py\n   ```\n\n## Output:\n\nhttps://github.com/user-attachments/assets/31d239fb-44a8-4906-a2e6-43886348ba5b\n\n## Workflow:\n\n![image](https://github.com/user-attachments/assets/3a72bb94-7b6e-46e7-baf8-770a92bd4780)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkr1shnasomani%2Fsportiq","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkr1shnasomani%2Fsportiq","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkr1shnasomani%2Fsportiq/lists"}