{"id":15132128,"url":"https://github.com/vishwast333/traffixvision","last_synced_at":"2026-01-20T15:07:14.343Z","repository":{"id":255481427,"uuid":"852243128","full_name":"VishwasT333/TraffixVision","owner":"VishwasT333","description":"TraffixVision is an advanced video analysis tool for real-time traffic monitoring. It detects lanes, tracks vehicles using YOLOv8, and analyzes their direction and travel time. Ideal for smart cities, it provides real-time metrics, counts vehicles, and outputs annotated videos, aiding in traffic management and road safety.","archived":false,"fork":false,"pushed_at":"2024-09-04T14:25:29.000Z","size":29501,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-12T02:09:16.628Z","etag":null,"topics":["opencv","python","yolov8"],"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/VishwasT333.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-04T13:28:22.000Z","updated_at":"2024-09-04T14:33:36.000Z","dependencies_parsed_at":null,"dependency_job_id":"a0783bad-982c-4c42-8d2f-027b20ef2d69","html_url":"https://github.com/VishwasT333/TraffixVision","commit_stats":null,"previous_names":["vishwast333/traffixvision"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VishwasT333%2FTraffixVision","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VishwasT333%2FTraffixVision/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VishwasT333%2FTraffixVision/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VishwasT333%2FTraffixVision/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/VishwasT333","download_url":"https://codeload.github.com/VishwasT333/TraffixVision/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247406078,"owners_count":20933803,"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":["opencv","python","yolov8"],"created_at":"2024-09-26T04:03:57.081Z","updated_at":"2026-01-20T15:07:14.313Z","avatar_url":"https://github.com/VishwasT333.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TraffixVision\nTraffixVision is an advanced video analysis tool for real-time traffic monitoring. It detects lanes, tracks vehicles using YOLOv8, and analyzes their direction and travel time. Ideal for smart cities, it provides real-time metrics, counts vehicles, and outputs annotated videos, aiding in traffic management and road safety.\n\n## Future Prospects\nThe primary aim of TraffixVision's vehicle counting and direction prediction features is to optimize traffic signal management. In future iterations, the system could be integrated with traffic signals to dynamically adjust the timing based on real-time vehicle counts. For example, once a fixed number of vehicles are detected in a lane, the signal could turn green, allowing those vehicles to pass, thus reducing congestion.\n\nGiven that TraffixVision is tailored for Bangalore, India, the system could be fine-tuned to allow vehicles in the left lane to move freely without waiting for a signal, reflecting local traffic rules where left turns are often allowed on red. Additionally, by analyzing the average time vehicles take to travel from one signal to another, TraffixVision could optimize signal timings even further. For instance, if it takes vehicles 10 seconds to reach a signal, the system could adjust the opposite signal(say) to turn green at the 7th second, minimizing wait times and improving traffic flow efficiency.\n\nThese future developments would make TraffixVision a powerful tool for adaptive traffic management, helping reduce congestion and improving the overall efficiency of urban traffic systems.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvishwast333%2Ftraffixvision","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvishwast333%2Ftraffixvision","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvishwast333%2Ftraffixvision/lists"}