nrl-ai/anylearning-rfdetr-locust-keypoints
Keypoint Detection • Updated
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AnyLearning datasets
This repository contains reproducible sample datasets used to develop and test AnyLearning OSS.
Dataset licenses are recorded in LICENSES.md. The repository's scripts and original documentation are Apache-2.0, but that license does not override the terms of any dataset. Check the dataset license before use.
Licence-cleared
| Task | Dataset | Licence |
|---|---|---|
| Image classification | ZhangLabData: Chest X-Ray | CC BY 4.0 |
| Object detection | Safety Helmet and Reflective Jacket Detection | Apache 2.0 |
| Semantic segmentation | Electron Microscopy Particle Segmentation | CC BY 4.0 |
| Handpose classification | American Sign Language Letters | Public Domain |
| Keypoint detection | Generated Keypoint Stick Figures | CC0 1.0 |
| Keypoint detection | Desert Locust | Apache 2.0 |
| Tabular classification | UCI Bank Marketing | CC BY 4.0 |
| Tabular regression | UCI Concrete Compressive Strength | CC BY 4.0 |
| Text classification | Banking77 | CC BY 4.0 |
| Response evaluation | TruthfulQA | Apache 2.0 |
The first four are the real datasets AnyLearning's test suite loads via REAL_DATASETS in
tests/fixtures/datasets.py.
The keypoint set is a deterministic, generated starter project: 24 training images, 8 validation images, two instances per image and five named landmarks. It is intentionally simple and is suitable for tutorials and mechanical tests, not model-quality claims.
Small, ready-to-upload keypoint archives are also mirrored on the AnyLearning CDN:
- CC0 stick figures: train.zip and valid.zip
- CC BY 4.0 vertebral X-ray subset: 64-image train.zip and 16-image valid.zip
- Apache-2.0 Desert Locust: 630-image train.zip and 70-image valid.zip
Every vertebral archive embeds its attribution and conversion notes. See the dataset README before using medical images; this is an engineering example, not a clinically validated dataset.
The structured-data catalog is available at
/datasets/structured/catalog-v1.json.
AnyLearning can install its real examples directly from the Dataset workspace;
each entry carries its source, citation, license, size and SHA-256 checksum.
Fetch on demand for engineering validation
| Task | Dataset | Why it is not committed |
|---|---|---|
| Keypoint detection | Spondylolisthesis Vertebral Landmark v1 | The complete source is fetched from its fixed DOI; a small attributed subset is mirrored on the CDN. |
Datasets without verified redistribution terms are intentionally excluded from this public repository. See LICENSES.md for the acceptance policy.
Using these with AnyLearning
Each dataset ships as per-subset zips. Download this repository next to the
anylearning-oss checkout, or point ANYLEARNING_DATA_DIR at it, and the test suite
will find it automatically:
hf download nrl-ai/anylearning-data --repo-type dataset --local-dir ../anylearning-data
pytest tests/e2e/test_real_datasets_e2e.py
Archives are extracted into ~/.cache/anylearning-test-data/, never back into a
repository. See docs/testing.md in the main repository.
Community
Please read CONTRIBUTING.md before submitting a dataset and report vulnerabilities according to SECURITY.md. General support questions belong in the AnyLearning OSS discussions. Participation is governed by CODE_OF_CONDUCT.md.
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