use-libreyolo
use-libreyolo is a Computer vision skill for AI agents, published by LibreYOLO in the libreyolo repository on GitHub. Skillspace rates use-libreyolo D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Use LibreYOLO as a computer vision library: run inference, train, validate, export, and track with object-detection / segmentation (and pose, classify, gaze, OBB, semantic, depth, point, restore) models on your own images and video. This is the guide for *using* the `libreyolo` pip package — not for contributing to or developing it. Use whenever someone wants to detect, segment, or track with a YOLO9 or RF-DETR model, train on a YOLO-format dataset, measure mAP, run inference on an exported model, or export to ONNX / TensorRT / OpenVINO / CoreML / NCNN / TFLite. Covers both the `libreyolo` CLI and the `from libreyolo import LibreYOLO` Python API.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 493
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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