| --- |
| task_categories: |
| - keypoint-detection |
| license: cc-by-4.0 |
| tags: |
| - biology |
| - pose-estimation |
| - multiview |
| - fly |
| - lightning-pose |
| pretty_name: Fly Anipose (Lightning Pose subset) |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: ind |
| path: data/ind-train-*.parquet |
| - split: ood |
| path: data/ood-test-*.parquet |
| --- |
| |
| # Fly Anipose — Lightning Pose Multiview Dataset |
|
|
| 6-camera pose estimation dataset for *Drosophila* leg keypoints, packaged for use with [Lightning Pose](https://github.com/danbider/lightning-pose). |
|
|
| ## Dataset Description |
|
|
| Head-fixed flies run on a spherical treadmill while 6 synchronized cameras capture locomotion at **300 Hz**. Each frame is labeled with **30 keypoints** — 5 joint segments (A–E) on each of 6 legs (left legs L1–L3, right legs R1–R3). |
|
|
| Labels are **filtered Anipose predictions**, not hand-labeled frames. They were constructed by: |
| 1. Removing instances with mean 3D reprojection error > 10 px |
| 2. Running k-means on 3D poses and keeping 25 instances per session |
| 3. Using filtered 2D predictions; setting keypoints with 2D reprojection error > 10 px to NaN |
|
|
| Source data: Karashchuk et al., *Cell Reports* 2021 — original archive at https://doi.org/10.5061/dryad.nzs7h44s4 |
|
|
| ## Data Splits |
|
|
| | Split | Labeled instances | Sessions | |
| |-------|----------------:|--------:| |
| | In-distribution (InD) | 377 | 16 | |
| | Out-of-distribution (OOD) | 300 | 12 | |
|
|
| InD and OOD sets contain **different animals/sessions** (no overlap). |
|
|
| - `CollectedData_Cam-{A-F}.csv` — InD labels; `videos/` — InD videos |
| - `CollectedData_Cam-{A-F}_new.csv` — OOD labels; `videos_new/` — OOD videos |
|
|
| ## Keypoints |
|
|
| 30 keypoints total: side (`L`/`R`) + leg number (`1`–`3`) + segment (`A`–`E`, proximal→distal). |
|
|
| | Left legs | Right legs | |
| |-----------|------------| |
| | L1A, L1B, L1C, L1D, L1E | R1A, R1B, R1C, R1D, R1E | |
| | L2A, L2B, L2C, L2D, L2E | R2A, R2B, R2C, R2D, R2E | |
| | L3A, L3B, L3C, L3D, L3E | R3A, R3B, R3C, R3D, R3E | |
|
|
| ## Directory Structure |
|
|
| ``` |
| fly_anipose_subset/ |
| ├── labeled-data/ # Extracted frames per session×view; includes ±2 context frames |
| ├── videos/ # Full InD session videos (<SessionKey>_<View>.mp4) |
| ├── calibrations/ # Per-session camera calibration (.toml) for 3D features |
| ├── calibrations.csv # InD calibration index |
| ├── calibrations_new.csv # OOD calibration index |
| ├── CollectedData_Cam-{A-F}.csv # InD 2D keypoint labels (x,y per keypoint) |
| ├── CollectedData_Cam-{A-F}_new.csv # OOD 2D keypoint labels |
| ├── config_fly-anipose.yaml # Sample Lightning Pose training config |
| ├── project.yaml # View and keypoint definitions (required by LP App) |
| └── models/ # Pre-trained model checkpoints |
| ├── baseline/ |
| ├── seed1/ |
| ├── seed2/ |
| └── pleasant_ensemble/ |
| ``` |
|
|
| See the Lightning Pose documentation for full details on the [multiview data directory structure](https://lightning-pose.readthedocs.io/en/latest/source/directory_structure_reference/multiview_structure.html) and [model directory structure](https://lightning-pose.readthedocs.io/en/latest/source/directory_structure_reference/model_dir_structure.html). |
|
|
| ## Usage with Lightning Pose |
|
|
| The included `config_fly-anipose.yaml` is a ready-to-use training config. Key settings: |
|
|
| - **Image resize:** 256 × 256 |
| - **Backbone:** `resnet50_animal_ap10k` |
| - **Views:** Cam-A through Cam-F |
| - **Keypoints:** 30 |
|
|
| Update `data.data_dir` and `data.video_dir` to absolute paths on your machine before training. |
|
|
| ```bash |
| litpose train config_fly-anipose.yaml |
| ``` |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the original Anipose paper: |
|
|
| ```bibtex |
| @article{karashchuk2021anipose, |
| title = {Anipose: A toolkit for robust markerless 3D pose estimation}, |
| author = {Karashchuk, Pierre and Rupp, Katie L and Dickinson, Evyn S and |
| Walling-Bell, Sarah and Sanders, Elisha and Azim, Eiman and |
| Brunton, Bingni W and Tuthill, John C}, |
| journal = {Cell Reports}, |
| volume = {36}, |
| number = {13}, |
| year = {2021}, |
| doi = {10.1016/j.celrep.2021.109730} |
| } |
| ``` |
|
|
| Original data archive: https://doi.org/10.5061/dryad.nzs7h44s4 |
|
|
