data: add Desert Locust keypoints

.gitattributes

@@ -15,3 +15,5 @@ american_sign_language/test.zip filter=lfs diff=lfs merge=lfs -text
 american_sign_language/valid.zip filter=lfs diff=lfs merge=lfs -text
 vertebral_keypoints/v1/vertebral-keypoints-train-64.zip filter=lfs diff=lfs merge=lfs -text
 vertebral_keypoints/v1/vertebral-keypoints-valid-16.zip filter=lfs diff=lfs merge=lfs -text
+desert_locust_keypoints/train.zip filter=lfs diff=lfs merge=lfs -text
+desert_locust_keypoints/valid.zip filter=lfs diff=lfs merge=lfs -text

LICENSES.md

@@ -16,6 +16,7 @@ is not a licence.
 | `electron_microscopy_particle_segmentation` | Semantic segmentation | **CC BY 4.0** | [Dataset Ninja](https://datasetninja.com) |
 | `american_sign_language` | Handpose classification | **Public Domain** | [Roboflow Public](https://public.roboflow.com/object-detection/american-sign-language-letters/1) |
 | `keypoint_stick_figures` | Keypoint detection | **CC0 1.0** | Generated by the AnyLearning project; no third-party pixels |
+| `desert_locust_keypoints` | Keypoint detection | **Apache 2.0** | Graving et al. (2019), [official DeepPoseKit-Data repository](https://github.com/jgraving/DeepPoseKit-Data) |
 | `vertebral_keypoints` CDN subset | Keypoint detection | **CC BY 4.0** | Reyes (2025), [Mendeley Data V1](https://doi.org/10.17632/5jdfdgp762.1) |
 | `structured/v1/bank-marketing.csv` | Tabular classification | **CC BY 4.0** | Moro, Rita & Cortez (2014), [UCI DOI 10.24432/C5K306](https://doi.org/10.24432/C5K306) |
 | `structured/v1/concrete-strength.csv` | Tabular regression | **CC BY 4.0** | Yeh (1998), [UCI DOI 10.24432/C5PK67](https://doi.org/10.24432/C5PK67) |

README.md

@@ -34,6 +34,7 @@ override the terms of any dataset. **Check the dataset license before use.**
 | Semantic segmentation | [Electron Microscopy Particle Segmentation](electron_microscopy_particle_segmentation/) | CC BY 4.0 |
 | Handpose classification | [American Sign Language Letters](american_sign_language/) | Public Domain |
 | Keypoint detection | [Generated Keypoint Stick Figures](keypoint_stick_figures/) | CC0 1.0 |
+| Keypoint detection | [Desert Locust](desert_locust_keypoints/) | Apache 2.0 |
 | Tabular classification | [UCI Bank Marketing](structured/) | CC BY 4.0 |
 | Tabular regression | [UCI Concrete Compressive Strength](structured/) | CC BY 4.0 |
 | Text classification | [Banking77](structured/) | CC BY 4.0 |
@@ -54,6 +55,8 @@ CDN:
   and [valid.zip](https://cdn.anylearning.nrl.ai/datasets/keypoint_stick_figures/valid.zip)
 - [CC BY 4.0 vertebral X-ray subset: 64-image train.zip](https://cdn.anylearning.nrl.ai/datasets/vertebral_keypoints/v1/vertebral-keypoints-train-64.zip)
   and [16-image valid.zip](https://cdn.anylearning.nrl.ai/datasets/vertebral_keypoints/v1/vertebral-keypoints-valid-16.zip)
+- [Apache-2.0 Desert Locust: 630-image train.zip](https://huggingface.co/datasets/nrl-ai/anylearning-data/resolve/main/desert_locust_keypoints/train.zip)
+  and [70-image valid.zip](https://huggingface.co/datasets/nrl-ai/anylearning-data/resolve/main/desert_locust_keypoints/valid.zip)
 
 Every vertebral archive embeds its attribution and conversion notes. See the
 dataset README before using medical images; this is an engineering example,

desert_locust_keypoints/ATTRIBUTION.md

@@ -0,0 +1,17 @@
+# Desert Locust dataset attribution
+
+Source: https://github.com/jgraving/DeepPoseKit-Data
+
+Licence: Apache License 2.0
+
+Citation:
+
+Graving, Jacob M.; Chae, Daniel; Naik, Hemal; Li, Liang; Koger, Benjamin;
+Costelloe, Blair R.; and Couzin, Iain D. (2019). "DeepPoseKit, a software
+toolkit for fast and robust animal pose estimation using deep learning."
+*eLife* 8:e47994. https://doi.org/10.7554/eLife.47994
+
+Conversion notes: AnyLearning normalized the public Desert Locust data into
+standard COCO keypoint archives and used the reproducible 630-image training /
+70-image validation split documented by MMPose. Pixel values and landmark
+coordinates were not intentionally modified.

desert_locust_keypoints/README.md

@@ -0,0 +1,37 @@
+# Desert Locust Keypoints
+
+- **Task:** Keypoint Detection
+- **Licence:** Apache License 2.0
+- **Splits:** 630 training images, 70 validation images
+- **Instances:** one locust per image
+- **Landmarks:** 35 anatomical keypoints
+- **Source:** [DeepPoseKit-Data](https://github.com/jgraving/DeepPoseKit-Data)
+
+The archives are import-ready COCO keypoint datasets for AnyLearning. They use
+the reproducible 90/10 split published by MMPose and retain the source images
+and landmark coordinates; AnyLearning only normalized filenames and COCO
+metadata for its importer.
+
+Download and upload each archive into the matching subset of a
+**Keypoint Detection** project:
+
+- [train.zip](https://huggingface.co/datasets/nrl-ai/anylearning-data/resolve/main/desert_locust_keypoints/train.zip)
+  — SHA-256 `57da95c4f7927b9e57680e07fe662f40fc11e32e48f70ee433edab8437ddfa14`
+- [valid.zip](https://huggingface.co/datasets/nrl-ai/anylearning-data/resolve/main/desert_locust_keypoints/valid.zip)
+  — SHA-256 `b1e6bc5547dafc0c02e3ec26e9b8b4ddec03d9ca7ac749055cb92c9579344249`
+
+The 35 ordered landmarks are `head`, `neck`, `thorax`, `abdomen1`, `abdomen2`,
+15 left-side antenna/eye/leg landmarks, and their 15 right-side counterparts.
+Every archive embeds `ATTRIBUTION.md` with the licence, citation and conversion
+notes.
+
+Please cite the source paper when using the data:
+
+> Graving, J. M. et al. (2019). DeepPoseKit, a software toolkit for fast and
+> robust animal pose estimation using deep learning. *eLife*, 8, e47994.
+> https://doi.org/10.7554/eLife.47994
+
+The upstream dataset repository is distributed under Apache License 2.0. The
+copy of that licence at the root of this repository applies to the Desert
+Locust dataset; repository documentation and scripts do not override the terms
+of other datasets stored alongside it.

desert_locust_keypoints/train.zip

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desert_locust_keypoints/valid.zip

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