Ultralytics YOLO datasets

The #1 cause of silent training failure is a malformed dataset — validate before training.

Fastest route: prepare data in Platform

1. Open Platform, create a dataset under Annotate, and choose its task.
2. Upload images, videos, ZIP/TAR archives, or NDJSON. Existing YOLO labels and COCO JSON can be imported; cloud-storage integrations can keep supported data in place.
3. Open an image in the fullscreen editor. Use manual tools for detect, segment, semantic, classify, pose, or OBB. Switch to Smart mode to label with SAM (detect, segment, semantic, OBB) or a compatible official/custom YOLO model (those tasks plus pose).
4. Review the Classes, Charts, and Errors tabs, fix the split, and create a numbered dataset version before important runs.

Platform datasets cover all seven YOLO tasks. Depth targets are imported rather than drawn in the editor. See Platform Data and the Annotation Editor.

To train on the same dataset from local code, create an API key under Settings > API Keys, set ULTRALYTICS_API_KEY, and pass the dataset's ul:// URI as data:

yolo train model=yolo26n.pt data=ul://username/datasets/dataset-slug epochs=100