---
task_categories:
  - keypoint-detection
license: cc-by-nc-4.0
tags:
  - biology
  - pose-estimation
  - mouse
  - lightning-pose
pretty_name: Facemap
size_categories:
  - 1K<n<10K
---

# Facemap — Lightning Pose Single-View Dataset

Single-camera orofacial pose estimation dataset for mice, packaged for use with [Lightning Pose](https://github.com/paninski-lab/lightning-pose).

## Dataset Description

Mice were head-fixed and recorded with a close-up camera of the face during neural activity experiments. **15 keypoints** are labeled around the eyes, nose, mouth, whiskers, and lower lip; a paw keypoint is also included for frames in which the paw enters the camera field of view. Several keypoints (e.g., paw) are frequently occluded or absent.

Sessions were recorded from two camera angles (cam0 and cam1), both treated as a single view.

Source data: original archive at https://doi.org/10.25378/janelia.23712957.

## Data Splits

| Split | Labeled frames | Sessions |
|-------|---------------:|---------:|
| In-distribution (InD) | 2,400 | 57 |
| Out-of-distribution (OOD) | 100 | 6 |

- `CollectedData.csv` — InD labels; `videos/` — InD videos
- `CollectedData_test.csv` — OOD labels; `videos_test/` — OOD videos

## Keypoints

15 keypoints total.

| Region | Keypoints |
|--------|-----------|
| Eye | eye_back, eye_bottom, eye_front, eye_top |
| Nose | nose_bottom, nose_r, nose_tip, nose_top, nosebridge |
| Mouth | lowerlip, mouth |
| Whiskers | whisker_c1, whisker_c2, whisker_d1 |
| Paw | paw |

## Directory Structure

```
facemap/
├── labeled-data/          # Extracted frames per session; includes ±2 context frames
├── videos/                # InD session video clips
├── videos_test/           # OOD session video clips
├── CollectedData.csv      # InD 2D keypoint labels (x,y per keypoint)
├── CollectedData_test.csv # OOD 2D keypoint labels
├── config_facemap.yaml    # Sample Lightning Pose training config
└── project.yaml           # View and keypoint definitions (required by LP App)
```

See the Lightning Pose documentation for full details on the [single-view data directory structure](https://lightning-pose.readthedocs.io/en/latest/source/directory_structure_reference/singleview_structure.html).

## Usage with Lightning Pose

The included `config_facemap.yaml` is a ready-to-use training config. Key settings:

- **Image resize:** 256 × 256
- **Backbone:** `resnet50_animal_ap10k`
- **Keypoints:** 15

Update `data.data_dir` to an absolute path on your machine before training.

```bash
litpose train config_facemap.yaml
```

## Citation

If you use this dataset, please cite:

```bibtex
@article{syeda2024facemap,
  title     = {Facemap: a framework for modeling neural activity based on orofacial tracking},
  author    = {Syeda, Atika and Zhong, Lin and Tung, Renee and Long, Will and
               Pachitariu, Marius and Stringer, Carsen},
  journal   = {Nature Neuroscience},
  volume    = {27},
  number    = {1},
  pages     = {187--195},
  year      = {2024},
  publisher = {Nature Publishing Group US New York}
}
```

Original data archive: https://doi.org/10.25378/janelia.23712957.