yolo-datasets skillA
yolo-datasets is agent-read markdown (skill) from ultralytics/skills: Use when uploading, annotating, building, converting, analyzing, or debugging datasets in Ultralytics Platform or local YOLO — Platform dataset management and Smart Annotation, data.yaml, YOLO label .txt formats, COCO/DOTA/mask conversion, auto-labeling, splits, validation, and errors like "no labels found" or mAP near 0. Covers detect, segment, semantic, depth, classify, pose, and OBB data..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# 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](https://platform.ultralytics.com), 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. For detect, segment, semantic, and OBB, switch to **Smart** mode to label with SAM or predictions from a compatible official/custom YOLO model. 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](https://docs.ultralytics.com/platform/data) and the [Annotation Editor](https://docs.ultralytics.com/platform/data/annotation). …
Read the whole file at its exact version.
How to install
mdr add ultralytics/skills/yolo-datasets@git:20260904.9c3b8ecmdr add ultralytics/skills/yolo-datasets@sha256:6f2cb591af58a454Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_cbxkyabqsaoggysd)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260904.9c3b8ec latest | 2026-09-04 | 9c3b8ec | 7,091 B | A | view · diff |
| git:20260820.dcee0db | 2026-08-20 | dcee0db | 7,027 B | A | view · diff |
| git:20260814.05a799c | 2026-08-14 | 05a799c | 7,029 B | A | view · diff |
| git:20260811.e35dbcc | 2026-08-11 | e35dbcc | 6,647 B | A | view · diff |
| git:20260811.47343d9 | 2026-08-11 | 47343d9 | 5,290 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (7091 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ultralytics/skills · 25 stars · license AGPL-3.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_cbxkyabqsaoggysd GET https://markdownregistry.com/api/v1/resolve?ref=ultralytics/skills/yolo-datasets GET https://markdownregistry.com/api/v1/blob/6f2cb591af58a454cba74e8cd84736e711d99e0c703864aadf8542d50bf64fba
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