{"id":13689326,"url":"https://github.com/anibali/h36m-fetch","last_synced_at":"2025-04-06T02:12:34.906Z","repository":{"id":31685238,"uuid":"125937604","full_name":"anibali/h36m-fetch","owner":"anibali","description":"Human 3.6M 3D human pose dataset fetcher","archived":false,"fork":false,"pushed_at":"2023-03-19T23:20:27.000Z","size":63,"stargazers_count":375,"open_issues_count":2,"forks_count":49,"subscribers_count":10,"default_branch":"master","last_synced_at":"2025-03-30T01:13:13.710Z","etag":null,"topics":["dataset","human-pose-estimation"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/anibali.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":"2018-03-20T00:24:14.000Z","updated_at":"2025-03-24T21:24:19.000Z","dependencies_parsed_at":"2024-12-16T16:25:56.433Z","dependency_job_id":"f080f9ae-2461-45f0-8108-0e48e985651a","html_url":"https://github.com/anibali/h36m-fetch","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anibali%2Fh36m-fetch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anibali%2Fh36m-fetch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anibali%2Fh36m-fetch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anibali%2Fh36m-fetch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/anibali","download_url":"https://codeload.github.com/anibali/h36m-fetch/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247423516,"owners_count":20936626,"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":["dataset","human-pose-estimation"],"created_at":"2024-08-02T15:01:43.721Z","updated_at":"2025-04-06T02:12:34.882Z","avatar_url":"https://github.com/anibali.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"# Human3.6M dataset fetcher\n\n[Human3.6M](http://vision.imar.ro/human3.6m/description.php) is a 3D\nhuman pose dataset containing 3.6 million human poses and corresponding\nimages. The scripts in this repository make it easy to download,\nextract, and preprocess the images and annotations from Human3.6M.\n\n**Please do not ask me for a copy of the Human3.6M dataset. I do not own\nthe data, nor do I have permission to redistribute it. Please visit\nhttp://vision.imar.ro/human3.6m/ in order to request access and contact\nthe maintainers of the dataset.**\n\n## Requirements\n\n* Python 3\n* [`axel`](https://github.com/axel-download-accelerator/axel)\n* CDF\n* ffmpeg 3.2.4\n\nAlternatively, a Dockerfile is provided which has all of the\nrequirements set up. You can use it to run scripts like so:\n\n```bash\n$ docker-compose run --rm --user=\"$(id -u):$(id -g)\" main python3 \u003cscript\u003e\n```\n\n## Usage\n\n1. Firstly, you will need to create an account at\n   http://vision.imar.ro/human3.6m/ to gain access to the dataset.\n2. Once your account has been approved, log in and inspect your cookies\n   to find your PHPSESSID.\n3. Copy the configuration file `config.ini.example` to `config.ini`\n   and fill in your PHPSESSID.\n4. Use the `download_all.py` script to download the dataset,\n   `extract_all.py` to extract the downloaded archives, and\n   `process_all.py` to preprocess the dataset into an easier to use\n   format.\n\n## Frame sampling\n\nNot all frames are selected during the preprocessing step. We assume\nthat the data will be used in the Protocol #2 setup (see\n[\"Compositional Human Pose Regression\"](https://arxiv.org/abs/1704.00159)),\nso for subjects S9 and S11 every 64th frame is used. For the training\nsubjects (S1, S5, S6, S7, and S8), only \"interesting\" frames are used.\nThat is, near-duplicate frames during periods of low movement are\nskipped.\n\nYou can edit `select_frame_indices_to_include()` in `process_all.py` to\nchange this behaviour.\n\n## License\n\nThe code in this repository is licensed under the terms of the\n[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).\n\nPlease read the\n[license agreement](http://vision.imar.ro/human3.6m/eula.php) for the\nHuman3.6M dataset itself, which specifies citations you must make when\nusing the data in your own research. The file `metadata.xml` is directly\ncopied from the \"Visualisation and large scale prediction software\"\nbundle from the Human3.6M website, and is subject to the same license\nagreement.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanibali%2Fh36m-fetch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanibali%2Fh36m-fetch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanibali%2Fh36m-fetch/lists"}