{"id":16606150,"url":"https://github.com/nickorzha/video_objcount","last_synced_at":"2025-08-23T03:33:24.661Z","repository":{"id":167166017,"uuid":"642741410","full_name":"nickorzha/video_objcount","owner":"nickorzha","description":"video-based object counting software for tallying pretty much anything ","archived":false,"fork":false,"pushed_at":"2023-05-19T08:58:08.000Z","size":49954,"stargazers_count":19,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-06T12:45:38.168Z","etag":null,"topics":["computer-vision","object-counter","object-counting","video-analysis","video-processing"],"latest_commit_sha":null,"homepage":"","language":"Python","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/nickorzha.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":"2023-05-19T08:41:50.000Z","updated_at":"2025-04-11T14:19:29.000Z","dependencies_parsed_at":null,"dependency_job_id":"608682e1-4de9-4e7a-9ad2-29ff6e917bb6","html_url":"https://github.com/nickorzha/video_objcount","commit_stats":null,"previous_names":["adrian-krol/video_objcount","nickorzha/video_objcount"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/nickorzha/video_objcount","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickorzha%2Fvideo_objcount","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickorzha%2Fvideo_objcount/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickorzha%2Fvideo_objcount/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickorzha%2Fvideo_objcount/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nickorzha","download_url":"https://codeload.github.com/nickorzha/video_objcount/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickorzha%2Fvideo_objcount/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271737475,"owners_count":24812129,"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","status":"online","status_checked_at":"2025-08-23T02:00:09.327Z","response_time":69,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["computer-vision","object-counter","object-counting","video-analysis","video-processing"],"created_at":"2024-10-12T01:05:26.754Z","updated_at":"2025-08-23T03:33:24.645Z","avatar_url":"https://github.com/nickorzha.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# object counting from video\nThis is an open-source video-based object counting software for tallying pretty much anything (vehicles, people, animals — you name it).\n\n![](object_counting.jpg)\n\n## Requirements\n- Python 3 (tested with version 3.7)\n\n## Setup\n- Clone this repo.\n- Install the dependencies in _requirements.txt_ `pip install -r requirements.txt`.\n- Choose a detector and install its dependencies where necessary (if you're not sure what to pick, we recommend you start with `yolo`).\n\n| Detector | Description | Dependencies |\n|---|---|---|\n| `yolo` | Perform detection using models created with the YOLO (You Only Look Once) neural net. https://pjreddie.com/darknet/yolo/ | |\n| `tfoda` | Perform detection using models created with the Tensorflow Object Detection API. https://github.com/tensorflow/models/tree/master/research/object_detection | CPU: `pip install tensorflow-cpu` \u003cbr\u003e GPU: `pip install tensorflow-gpu` |\n| `detectron2` | Perform detection using models created with FAIR's Detectron2 framework. https://github.com/facebookresearch/detectron2 | `python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'` (https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md) |\n| `haarcascade` | Perform detection using Haar feature-based cascade classifiers. https://docs.opencv.org/3.4/db/d28/tutorial_cascade_classifier.html | |\n\n## Run\n- Create a _.env_ file (based on _.env.example_) in the project's root directory and edit as appropriate.\n- Run `python -m  main`.\n- Run using Docker `docker build -t adrian-krol/ivy .`.\n\n## Debug\nBy default, runs in \"debug mode\" which provides you a window to monitor the object counting process. You can:\n- press the `p` key to pause/play the counting process\n- press the `s` key to capture a screenshot\n- press the `q` key to quit the program\n- click any point on the window to log the coordinates of the pixel in that position\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnickorzha%2Fvideo_objcount","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnickorzha%2Fvideo_objcount","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnickorzha%2Fvideo_objcount/lists"}