Video to ML dataset
AI Training Datasets: Generate a frame-level ML training dataset from a video.
Different from every other App: the OUTPUT is the data, not a summary. Upload a video and we'll sample 50 evenly-spaced frames, label each one with object classes + scene attributes + event tags, and produce a JSON or CSV dataset machine-consumable by your ML pipeline. Designed for ML engineers and AI startups who need labeled data without paying a labeling vendor.
Built for ML engineers, AI startups, data teams, and computer vision teams.
Sample output
Frame-level JSON dataset
Frame 12: person, forklift, pallet
Attribute: indoor warehouse lighting
Export: JSON or CSV
What to upload
A video to extract a labeled training dataset from.
- Driving footage (urban / highway)
- Warehouse / industrial cameras
- Retail / aisle footage
- Wildlife / agriculture footage
What you get
A machine-consumable dataset (NOT a human-readable summary).
- Per-frame labels (class names + bounding boxes + confidence)
- Scene attributes (weather, lighting, density, etc.)
- Event tags (e.g. 'person_crossing', 'vehicle_approaching')
- Auto-detected domain tag (urban_driving / warehouse / retail / …)
- Aggregate label histogram
Exports
- JSON (full dataset — drop-in for most ML pipelines)
- CSV (flat per-label rows — for spreadsheet / pandas analysis)
Tips for better results
Up to 30 minutes per video (default cap)
Higher resolution = better label accuracy (Gemini multimodal benefits)
Mixed scene content produces a more balanced dataset than one continuous shot
If you need more frames, run multiple videos and concatenate the JSON exports