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| pretty_name: AniTrack Core-4 | |
| language: | |
| - en | |
| license: other | |
| license_name: source-specific-terms | |
| license_link: LICENSE.md | |
| task_categories: | |
| - keypoint-detection | |
| - object-detection | |
| tags: | |
| - mouse | |
| - rodent | |
| - animal-pose | |
| - core4 | |
| - multi-animal | |
| - dataset-recipe | |
| annotations_creators: | |
| - expert-generated | |
| - crowdsourced | |
| # AniTrack | |
| The public data companion to | |
| [LuminBench-AniTrack](https://github.com/Lumin-Science/LuminBench-AniTrack): | |
| mouse detection and **Core-4 pose** (`nose`, `left_ear`, `right_ear`, `tail_base`). | |
| ## What is published here? | |
| This initial release contains **source-download manifests, semantic mappings, | |
| an acquisition script, and the training-data recipe**. It does **not** contain | |
| image shards, per-image labels, pretrained weights, or a ready-to-load | |
| `datasets.load_dataset()` training table. The counts below describe the original | |
| prepared training views, not payloads currently hosted on this Hub repository. | |
| Upstream images and labels must be acquired from their original publishers, | |
| under each source's terms. Public availability is not permission to relicense | |
| or mirror every source. See [LICENSE.md](LICENSE.md). | |
| ## Frozen recipe: Bridge-33K Rotating v2 | |
| | Partition / training view | Frames | Mouse annotations | Use | | |
| |---|---:|---:|---| | |
| | Pose training | 32,713 | 53,420 | Gradient updates | | |
| | Detector training | 32,754 | 53,502 | Gradient updates | | |
| | External validation | 2,662 | 4,801 | Checkpoint selection | | |
| | DLC historical test | 263 | 285 boxes / 283 Core-4-evaluable mice | Final comparison only | | |
| The union before cleaning contains 27,826 external training frames plus 5,114 | |
| TopViewMouse training frames. The latter includes 1,012 Openfield training | |
| images; the disjoint 54 Openfield test images remain inside the frozen | |
| 263-image historical test. Historical test images must not be used to train, | |
| generate training pseudo-labels, select checkpoints, or tune thresholds. | |
| ### Source families | |
| Counts are upstream human-supervised frames across their available splits, | |
| before the AniTrack split and cleaning operations. | |
| | Source | Frames | Supervision / view | Terms and evidence | | |
| |---|---:|---|---| | |
| | [TopViewMouse5K v2](https://zenodo.org/records/13757509) | 5,114 train + 263 test | Human 27-point union; partial Core-4; mostly top view | Constituent-source terms; no single annotator-count claim | | |
| | [MARS](https://data.caltech.edu/records/j1ww1-mdc55) | 15,000 | Two mice, seven points, top view | CC-BY-NC-4.0; five-worker median labels | | |
| | [Kumar OFA](https://zenodo.org/records/6380163) | 8,910 | One mouse, twelve points, top view | Custom non-commercial terms; human labels, rater count unreported | | |
| | [Lightning Pose CRIM13](https://figshare.com/articles/dataset/Lightning_Pose_dataset_CRIM13/24993384) | 5,260 labeled centers | Two mice, seven points, top view | CC-BY-4.0; five-annotator median; 21,040 neighboring frames are not human-labeled centers | | |
| | [SLEAP mice_hc](https://docs.sleap.ai/v1.6.2/reference/datasets/#mice_hc) | 1,474 | Two mice, five points, overhead | Human labels; preserve dataset credits and verify redistribution terms | | |
| | [SLEAP mice_of](https://docs.sleap.ai/v1.6.2/reference/datasets/) | 1,000 | One to five mice, partial Core-4, **below-floor** | Human labels; not a strict-overhead source; verify redistribution terms | | |
| | [Mouse Lockbox](https://depositonce.tu-berlin.de/items/0d508909-ac27-46bd-9e52-17409196daeb) | 544 usable top-camera rows | One mouse, apparatus occlusions | CC-BY-4.0; human pose labels; only verified top camera used | | |
| ### Sampling, cleaning, and limitations | |
| MARS, Kumar and CRIM13 are capped at **1,242 frames per epoch each**, using | |
| seeded rotating windows. Smaller sources retain their eligible frames. Pose | |
| training rotates the selected target in multi-mouse images; detector training | |
| retains all valid boxes in a selected frame. The original pose virtual epoch | |
| contains 11,070 crops, with 600 epochs and global batch 64 (103,800 updates). | |
| Human partial keypoints are masked, never filled with teacher predictions. | |
| Near-complete overlap is excluded from the isolated pose-crop view but retained | |
| for detector supervision when boxes remain useful. Empty records and exact | |
| duplicate annotations are removed. The original detector loader additionally | |
| skipped seven invalid normalized-label records; do not silently repair the | |
| published recipe and still call it an exact reproduction. | |
| Published video/group splits are preserved where available. MARS lacks released | |
| session identifiers; its deterministic frame-hash split is **not proof of | |
| session-independent generalization**. TopViewMouse does not expose reliable | |
| session IDs either. SLEAP mice_of is a below-floor domain and should be reported | |
| separately in source-level evaluations. | |
| ## Acquire the original archives | |
| Clone this small metadata repository **on the machine where you intend to store | |
| the data**: | |
| ```bash | |
| git clone https://huggingface.co/datasets/LuminScience/AniTrack | |
| cd AniTrack | |
| python3 download_sources.py --list | |
| # Only after reviewing the upstream terms; downloads are explicit: | |
| python3 download_sources.py --download --accept-source-terms \ | |
| --output-root /your/data/raw | |
| ``` | |
| The script uses only Python's standard library, validates pinned publisher MD5 | |
| checksums (and sizes where available), and does not extract or alter the source | |
| archives. Existing valid files are reused; invalid existing files cause a hard | |
| failure. Use `--sources mars_topview_pose` to acquire a selected source. No | |
| training split is created by this acquisition step. | |
| The `manifests/` files preserve native layouts and Core-4 mappings. The external | |
| preparation configuration records the split and missing-label policies; | |
| `recipe.json` records the combined training contract. Conversion, split audits, | |
| and pose/detector training live in the companion code repository. Pin revisions | |
| of both repositories for any experiment. The historical external staging | |
| manifest filename containing `gated` refers to two now-directly-downloadable | |
| sources, not a Hub access gate. | |
| ## Scope | |
| This is a frame-level detection/pose resource, not newly annotated ground truth | |
| for persistent tracking identities. No new animal experiments were conducted | |
| to produce this collection. Cite the original datasets and respect their animal | |
| research, attribution, and usage requirements. Candidate datasets awaiting | |
| access or semantic review are not counted in this recipe. | |