{"id":20290037,"url":"https://github.com/UFTHaq/Motion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","last_synced_at":"2025-05-07T19:31:43.101Z","repository":{"id":206674440,"uuid":"717435434","full_name":"UFTHaq/Motion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","owner":"UFTHaq","description":"Limp Detection in Leg using OpenCV and MediaPipe with Motion Capture","archived":false,"fork":false,"pushed_at":"2023-11-25T03:13:44.000Z","size":946,"stargazers_count":2,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-22T12:16:19.582Z","etag":null,"topics":["mediapipe-pose","motion-capture","opencv","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/UFTHaq.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-11-11T13:36:29.000Z","updated_at":"2024-02-25T14:05:43.000Z","dependencies_parsed_at":"2023-11-25T04:21:54.384Z","dependency_job_id":"df407147-88b2-4b71-b53e-21a033332dae","html_url":"https://github.com/UFTHaq/Motion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","commit_stats":null,"previous_names":["ufthaq/motion-capture-leg-limp"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/UFTHaq","download_url":"https://codeload.github.com/UFTHaq/Motion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252943780,"owners_count":21829308,"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":["mediapipe-pose","motion-capture","opencv","python"],"created_at":"2024-11-14T15:06:01.806Z","updated_at":"2025-05-07T19:31:38.088Z","avatar_url":"https://github.com/UFTHaq.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"![GitHub last commit](https://img.shields.io/github/last-commit/UFTHaq/Motion-Capture-Leg-Limp?style=for-the-badge)\n![GitHub top language](https://img.shields.io/github/languages/top/UFTHaq/Motion-Capture-Leg-Limp?label=Python\u0026logo=python\u0026logoColor=white\u0026style=for-the-badge)\n![GitHub top language](https://img.shields.io/github/languages/top/UFTHaq/Motion-Capture-Leg-Limp?logo=Jupyter\u0026style=for-the-badge)\n![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/UFTHaq/Motion-Capture-Leg-Limp?style=for-the-badge)\n![GitHub Repo stars](https://img.shields.io/github/stars/UFTHaq/Motion-Capture-Leg-Limp?color=red\u0026style=for-the-badge)\n\n# Motion Capture - Leg Limp\nLimp Detection in Leg using OpenCV and MediaPipe with Motion Capture\n\n\u003cp align=\"justify\"\u003e This project combines the power of OpenCV and MediaPipe with advanced motion capture techniques to create a robust system for real-time limp detection in the\n  leg. By integrating motion capture capabilities, the application achieves enhanced precision in identifying and analyzing irregularities in leg movement.\n\u003c/p\u003e\n\n\nIf you consider this page is useful, please leave a star\n\n## MediaPipe - Pose Landmark\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://mediapipe.dev/images/mobile/pose_tracking_full_body_landmarks.png\" height=\"350\" /\u003e\n\u003c/p\u003e\n\n## I. You need the videos\n\nhttps://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/84dbb9bd-0af4-40f3-8cc3-2725bbdb9dd0\n\nhttps://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/bca10186-cbb4-4c3b-89bd-026db75f3112\n\n## II. Then, you capture the motion\nHere is the visualize graphic about the leg range of motion data captured from the video\n|Normal (right-left) leg|Limp (right-left) leg|\n|:-:|:-:|\n|\u003cimg src=\"https://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/395454cc-2f82-4143-bcc0-85e555e5a060\" width=\"500\" /\u003e|\u003cimg src=\"https://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/9c1095c9-33d8-4b1a-8277-15fec37e1f05\" width=\"500\" /\u003e |\n\n|Normal (right) leg \u0026 Limp (right) leg|Normal (left) leg \u0026 Limp (left) leg|\n|:-:|:-:|\n|\u003cimg src=\"https://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/1e92fe98-5970-4a84-91b9-1f6e1deb3e30\" width=\"500\" /\u003e|\u003cimg src=\"https://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/5f368834-bf8c-4103-9c81-a8fad3124fd6\" width=\"500\" /\u003e |\n\n## III. Take Conclusion\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/UFTHaq/Motion-Capture-Leg-Limp/assets/104829519/9c1095c9-33d8-4b1a-8277-15fec37e1f05\" width=\"800\" /\u003e\n\u003c/p\u003e\n\n\u003cp align=\"justify\"\u003e In image Limp (right-left) leg, it can be observed that there is a significant difference in the range of motion between the left and right legs. From this, it can be assumed that there is a limp in the left leg. The range of motion angle in the left leg (red line) tends to be smaller than the range of motion angle in the right leg because, in the limping left leg, the joint tends to lock the angle to alleviate pain caused by excessive leg movement. The larger the range of motion angle, the more pronounced the perceived pain.\n\u003c/p\u003e\n\n\u003chr\u003e\n\u003c/hr\u003e\n\u003cp align=\"center\"\u003e\n  \u003cb\u003eIf you consider this page is useful, please leave a star\u003c/b\u003e\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FUFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FUFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FUFTHaq%2FMotion-Capture-Leg-Limp-with-Python-OpenCV-MediaPipe/lists"}