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(`@parva101/video2dataset`)\n\n[![CI](https://github.com/Parva101/video2dataset/actions/workflows/ci.yml/badge.svg)](https://github.com/Parva101/video2dataset/actions/workflows/ci.yml)\n[![License: Apache-2.0](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](./LICENSE)\n[![FiftyOne Plugin](https://img.shields.io/badge/FiftyOne-plugin-orange.svg)](https://docs.voxel51.com/plugins/index.html)\n\n## Demo\n\n### YouTube -\u003e Dataset\n\n![video2dataset YouTube flow (FiftyOne App)](./assets/video2dataset_youtube_demo.gif)\n\n### Local Video -\u003e Dataset\n\n![video2dataset local video flow (FiftyOne App)](./assets/video2dataset_local_demo.gif)\n\nA production-ready FiftyOne Python plugin that converts YouTube URLs or local\nvideo files into image datasets by extracting representative keyframes.\n\n## Features\n\n- YouTube ingest via `yt-dlp`\n- Local video ingest\n- Three frame selection strategies:\n- `uniform` (every N seconds)\n- `scene_change` (histogram-based scene detection)\n- `hybrid` (uniform + scene change)\n- Optional perceptual hash deduplication (`pHash`)\n- Automatic dataset creation + open in FiftyOne App\n- Source metadata attached to samples and dataset info\n\n## Operators\n\n- `sample_from_youtube`\n- `sample_from_video`\n\n## Requirements\n\n- Python 3.10+\n- FiftyOne (latest stable recommended)\n- Python packages in [`requirements.txt`](./requirements.txt)\n- `ffmpeg` on `PATH` (recommended)\n\nInstall dependencies:\n\n```bash\npip install -r requirements.txt\n```\n\n## Installation\n\nInstall from GitHub:\n\n```bash\nfiftyone plugins download https://github.com/Parva101/video2dataset\n```\n\nInstall only this plugin:\n\n```bash\nfiftyone plugins download https://github.com/Parva101/video2dataset --plugin-names @parva101/video2dataset\n```\n\nVerify install:\n\n```bash\nfiftyone plugins list\nfiftyone operators list\n```\n\n## Usage\n\n1. Launch FiftyOne App\n2. Open Operator Browser\n3. Run:\n- `Video Sampler: YouTube to dataset`, or\n- `Video Sampler: local video to dataset`\n4. Configure:\n- `dataset_name` (required)\n- `strategy`: `uniform | scene_change | hybrid`\n- `max_frames`\n- `interval_seconds`\n- `scene_threshold` (`0` to `1`)\n- `dedup` and `dedup_threshold`\n- `overwrite_dataset`\n- `output_dir` (optional)\n\n## Output schema\n\nSample fields:\n\n- `filepath`\n- `source_type`\n- `sampling_strategy`\n- `timestamp_sec`\n- `frame_number`\n\nAdditional YouTube fields:\n\n- `source_url`\n- `video_id`\n- `title`\n- `duration_sec`\n- `uploader`\n\nDataset `info` fields:\n\n- `source_type`\n- `source_metadata`\n- `extraction_info`\n\n## Development\n\n```bash\npip install -r requirements.txt\npip install -r requirements-dev.txt\npytest\nruff check .\n```\n\n## Troubleshooting\n\n- If YouTube download fails, verify the URL is public and update `yt-dlp`\n- If no frames are selected, lower `scene_threshold` or `interval_seconds`\n- If dedup removes everything, lower `dedup_threshold` or disable `dedup`\n- If dataset exists, enable `overwrite_dataset` or use a different name\n\n## Contributing\n\nSee [CONTRIBUTING.md](./CONTRIBUTING.md).\n\n## Security\n\nReport vulnerabilities via [SECURITY.md](./SECURITY.md).\n\n## Changelog\n\nSee [CHANGELOG.md](./CHANGELOG.md).\n\n## License\n\nLicensed under Apache-2.0. See [LICENSE](./LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparva101%2Fvideo2dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fparva101%2Fvideo2dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparva101%2Fvideo2dataset/lists"}