vidlabel
An open, directory-based format and Python library for video annotation data: time markers and spans, bounding boxes, masks, tracks and labels in one annotation table (JSON + Parquet). Video pixels are not stored; datasets point at your videos.
Status: alpha (0.6.1). The format and API can still change between minor versions; see the changelog.
pip install vidlabel # library and command line
pip install "vidlabel[video]" # + OpenCV: read frames, preview, check-video
pip install "vidlabel[ui]" # + local web interface: vidlabel ui my_dataset
pip install "vidlabel[mcp]" # + MCP server for AI agents: vidlabel mcp my_dataset
pip install "vidlabel[torch]" # + PyTorch datasets
Python 3.10 or newer. vidlabel-spec (the format's models and JSON Schema) is installed with it.
from vidlabel import Dataset, VideoMetadata
ds = Dataset.create("my_dataset")
ds.add_video(VideoMetadata(video_id="clip", frame_count=100, fps={"num": 25, "den": 1}, width=640, height=360))
ds.add_labels(["cat"])
ds.add_annotations([{"kind": "box", "label": "cat", "start_frame": 0, "box": (10, 10, 200, 150), "origin": "human"}], "clip")
print(ds.validate())
Documentation, format specification and guides: https://github.com/HIManish-G/pyvidlabel (wiki). MIT licensed.
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Release files for vidlabel 0.6.1
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| File | Size | Uploaded | Provenance | Actions |
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| vidlabel-0.6.1-py3-none-any.whl | Python 3 | none | any | Details for vidlabel-0.6.1-py3-none-any.whl |
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