{"id":28653885,"url":"https://github.com/tiger-ai-lab/quickcodec","last_synced_at":"2025-06-13T07:08:01.570Z","repository":{"id":294783408,"uuid":"988052658","full_name":"TIGER-AI-Lab/QuickCodec","owner":"TIGER-AI-Lab","description":null,"archived":false,"fork":false,"pushed_at":"2025-05-22T03:24:58.000Z","size":301422,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-05-22T03:29:17.539Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Cython","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TIGER-AI-Lab.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.rst","contributing":null,"funding":null,"license":"LICENSE.txt","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,"zenodo":null}},"created_at":"2025-05-22T01:40:56.000Z","updated_at":"2025-05-22T03:25:01.000Z","dependencies_parsed_at":"2025-05-22T03:39:52.706Z","dependency_job_id":null,"html_url":"https://github.com/TIGER-AI-Lab/QuickCodec","commit_stats":null,"previous_names":["tiger-ai-lab/quickcodec"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TIGER-AI-Lab/QuickCodec","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TIGER-AI-Lab%2FQuickCodec","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TIGER-AI-Lab%2FQuickCodec/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TIGER-AI-Lab%2FQuickCodec/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TIGER-AI-Lab%2FQuickCodec/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TIGER-AI-Lab","download_url":"https://codeload.github.com/TIGER-AI-Lab/QuickCodec/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TIGER-AI-Lab%2FQuickCodec/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259599331,"owners_count":22882357,"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":[],"created_at":"2025-06-13T07:08:00.486Z","updated_at":"2025-06-13T07:08:01.542Z","avatar_url":"https://github.com/TIGER-AI-Lab.png","language":"Cython","funding_links":[],"categories":[],"sub_categories":[],"readme":"QuickCodec\n====\n\nQuickCodec is designed for fast loading videos for VLLMs, especially long videos with relatively high frame sampling rates.\n\n---\n\n![version]\n\n\nInstallation\n------------\n\nThe easiest way to use QuickCodec is via the binary wheels are provided on [PyPI][pypi] for Linux, MacOS and Windows linked against the latest stable version of ffmpeg. You can install these wheels by running:\n\n```bash\npip install quickcodec\n```\n\n\nInstalling From Source\n----------------------\n\nFor the more adventurous fold  Here's how to build PyAV from source. You must use [MSYS2](https://www.msys2.org/) when using Windows.\n\n```bash\ngit clone https://github.com/PyAV-Org/PyAV.git\ncd PyAV\nsource scripts/activate.sh\n\n# Build ffmpeg from source. You can skip this step\n# if ffmpeg is already installed.\n./scripts/build-deps\n\n# Build PyAV\n./scripts/build\n\n# if you want to install it globally instead of in the env, deactivate\ndeactivate\n\npip install .\n```\n\n---\n\nRoadmap\n----------------------\n\nQuickCodec is ojnly just getting started!\nAs our lab is always working on (long) video, we will continue to add new features and remove sharp edges.\n\n- Pull in qwen_procesing to this library, as it is the last bottleneck after accelerating prefill and loading.\n- Support more sparse access patterns, I.e. a seek-if-needed design.\n- Add more elegant handling of shared memory.\n- Add long lived workers.\n- Add better error handling if a subprocess blows up.\n\n\nSupported Platforms\n----------------------\n- **Linux:** this is our main platform and what we test against. If you have problems with any linux distro please open an issue and we will try to resolve it.\n- **MacOS:** as it is unix-like, everything should work for MacOS, however *we do not actively test against it*.\n- **Windows:** we build for it, however it is quite different and you may encounter weird problems.\n\nNotice\n----------------------\nQuickVideo is build on top of [FFmpeg][ffmpeg] and [PyAv][pyav] libraries.  \nHuge thanks to the contributors and maintainers of those libraries, they have done a huge amount of work create a clean interface that handles a lot of the messy nature of multimedia processing.\nThis project is **not endorsed** any maintainer of PyAv or FFmpeg, if you have any problems with QuickCodec please open as issue on **this repository**.\nWe inherit all the features of PyAv (including processing for other modalities like audio) which you can read about [here][docs], have fun!\n\n\n[conda-badge]: https://img.shields.io/conda/vn/conda-forge/av.svg?colorB=CCB39A\n[conda]: https://anaconda.org/conda-forge/av\n[docs-badge]: https://img.shields.io/badge/docs-on%20pyav.basswood--io.com-blue.svg\n[docs]: https://pyav.basswood-io.com\n[pypi-badge]: https://img.shields.io/pypi/v/av.svg?colorB=CCB39A\n[pypi]: https://pypi.org/project/quickvideo\n[discuss]: https://github.com/PyAV-Org/PyAV/discussions\n[version]: https://img.shields.io/badge/Version-0.0.1-blue\n[github-tests-badge]: https://github.com/PyAV-Org/PyAV/workflows/tests/badge.svg\n[github-tests]: https://github.com/PyAV-Org/PyAV/actions?workflow=tests\n[github]: https://github.com/TigerLab/PyAV\n\n[ffmpeg]: https://ffmpeg.org/\n[pyav]: https://github.com/PyAV-Org/PyAV\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftiger-ai-lab%2Fquickcodec","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftiger-ai-lab%2Fquickcodec","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftiger-ai-lab%2Fquickcodec/lists"}