{"id":19308863,"url":"https://github.com/balavenkatesh3322/docker_video_analysis","last_synced_at":"2026-05-04T18:38:30.865Z","repository":{"id":118937886,"uuid":"248701226","full_name":"balavenkatesh3322/Docker_video_analysis","owner":"balavenkatesh3322","description":"Video analysis using YoloV3 and openCV library","archived":false,"fork":false,"pushed_at":"2020-04-11T10:45:31.000Z","size":6149,"stargazers_count":1,"open_issues_count":0,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-01-06T01:30:55.980Z","etag":null,"topics":["computer-vision","docker","object-detection","opencv","videoanalysis","yolov3"],"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/balavenkatesh3322.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}},"created_at":"2020-03-20T08:11:21.000Z","updated_at":"2021-12-08T11:27:53.000Z","dependencies_parsed_at":null,"dependency_job_id":"d4316a5c-2ba3-4a0d-a4b0-0f1eb6de7ebb","html_url":"https://github.com/balavenkatesh3322/Docker_video_analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2FDocker_video_analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2FDocker_video_analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2FDocker_video_analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2FDocker_video_analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/balavenkatesh3322","download_url":"https://codeload.github.com/balavenkatesh3322/Docker_video_analysis/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240409849,"owners_count":19796797,"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","docker","object-detection","opencv","videoanalysis","yolov3"],"created_at":"2024-11-10T00:16:45.887Z","updated_at":"2026-05-04T18:38:30.861Z","avatar_url":"https://github.com/balavenkatesh3322.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# docker_video_analysis\n\n## Introduction\nI have setup docker file to do Video analysis using Yolo and openCV library which will read video as frames and detect objects in that frames. I saved all videos files and output json file in local videos folder.\n\n## Dependencies\nDocker image with python 3.7 and opencv 4.1.0\n\nBuild and tag the image \"sudo docker build -t opencvcalculai .\"\n\nRun docker file \"sudo docker run -d opencvcalculai:latest\"\n\nRun this command \"xhost local:root\" when erro occures as \"Gtk-WARNING **: 06:49:47.946: cannot open display: unix:0\"\n\ndocker-compose build\n\ndocker-compose up \n\nor\n\nInstall below required library in your local machine.\n\n1) python 3.7\n2) opencv 4.1.0\n3) numpy \n\n\n## Download Pre-Trained Yolov3 Model file\nDownload the pre-trained YOLO v3 weights file from this [link](https://drive.google.com/file/d/1AECks3mc2Xwe2BjvNdC_QKiiKZF8wt35/view?usp=sharing) and place it in the current directory\n\n## Quick Start\n\n\n\nThis analyse python file using Yolov3 to detect objects from videos and save object names as JSON file in videos folder.\n\n\n## Sample Output\nI have uploaded sample json file results in videos folder.\n\n{'remote', 'cup', 'cell phone', 'person'}\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbalavenkatesh3322%2Fdocker_video_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbalavenkatesh3322%2Fdocker_video_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbalavenkatesh3322%2Fdocker_video_analysis/lists"}