add tracking eval

README.md

@@ -0,0 +1,168 @@
+---
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: video
+    dtype: string
+  - name: video_dataset
+    dtype: string
+  - name: exp
+    dtype: string
+  - name: obj_id
+    list: string
+  - name: mask_id
+    list: string
+  - name: points
+    list:
+    - name: object_id
+      dtype: string
+    - name: points
+      list:
+        list: float64
+  - name: segments
+    list:
+    - name: object_id
+      dtype: string
+    - name: segments
+      list:
+        list: int64
+  - name: masks
+    list:
+    - name: object_id
+      dtype: string
+    - name: masks
+      list:
+        list: string
+  - name: start_frame
+    dtype: int64
+  - name: end_frame
+    dtype: int64
+  - name: w
+    dtype: int64
+  - name: h
+    dtype: int64
+  - name: n_frames
+    dtype: int64
+  - name: fps
+    dtype: float64
+  - name: video_source
+    dtype: string
+configs:
+- config_name: default
+  data_files:
+    - path: "data/**/*.json"
+- config_name: person
+  data_files:
+    - path: "data/personpath22/*.json"
+- config_name: sports
+  data_files:
+    - path: "data/sportsmot/*.json"
+- config_name: animal
+  data_files:
+    - path: "data/APTv2/*.json"
+- config_name: misc
+  data_files:
+    - path: "data/sav/*.json"
+- config_name: dance
+  data_files:
+    - path: "data/dancetrack/*.json"
+---
+
+# Molmo2-VideoTrackEval
+
+Molmo2-VideoTrackEval is an evaluation benchmark for video point tracking, containing human-annotated ground truth across 5 diverse video datasets. It includes segmentation masks for evaluating whether predicted points fall within the correct object regions.
+
+This benchmark is part of the [Molmo2 dataset collection](https://huggingface.co/collections/allenai/molmo2) and is used to evaluate the Molmo2 family of models on video object tracking via point trajectories.
+
+Quick links:
+- 📃 [Paper]()
+- 🎥 [Blog with Videos]()
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load entire evaluation dataset
+ds = load_dataset("allenai/Molmo2-VideoTrackEval")
+
+# Load a specific benchmark subset by config name
+dance = load_dataset("allenai/Molmo2-VideoTrackEval", "dance")
+sports = load_dataset("allenai/Molmo2-VideoTrackEval", "sports")
+person = load_dataset("allenai/Molmo2-VideoTrackEval", "person")
+misc = load_dataset("allenai/Molmo2-VideoTrackEval", "misc")
+animal = load_dataset("allenai/Molmo2-VideoTrackEval", "animal")
+```
+
+## Available Configs
+
+| Config | Description |
+|--------|-------------|
+| `default` | All evaluation data combined |
+| `personpath22` | Pedestrian tracking benchmark |
+| `sportsmot` | Sports multi-object tracking benchmark |
+| `APTv2` | Animal pose tracking benchmark |
+| `sav` | Segment Anything Video benchmark |
+| `dancetrack` | Dance tracking benchmark |
+
+## Data Format
+
+Each row contains tracking annotations for one or more objects in a video clip:
+
+| Field | Description |
+|-------|-------------|
+| `id` | Unique identifier for this annotation |
+| `video` | Video filename |
+| `video_dataset` | Source dataset name (e.g., 'dancetrack', 'sportsmot') |
+| `video_source` | Video directory path (can be ignored) |
+| `exp` | Text expression describing the tracked object(s) |
+| `obj_id` | List of object IDs per video |
+| `mask_id` | List of mask IDs corresponding to tracked objects starting from '0' |
+| `points` | List of point trajectories per object. Each entry contains `object_id` and `points` (list of [x, y] coordinates per frame) |
+| `segments` | List of segment annotations per object. Each entry contains `object_id` and `segments` |
+| `masks` | List of segmentation masks per object for evaluation. Each entry contains `object_id` and `masks` (used to verify if predicted points fall within the ground truth object region) |
+| `start_frame` | Starting frame index for this clip |
+| `end_frame` | Ending frame index for this clip |
+| `w` | Video width |
+| `h` | Video height |
+| `n_frames` | Number of frames in the clip |
+| `fps` | Frames per second |
+
+**Important:** `start_frame` and `end_frame` indicate which portion of the source video to use. You need to trim the video to this range — the annotations correspond to frames within `[start_frame, end_frame]`, not the entire video.
+
+### Evaluation with Masks
+
+The `masks` field contains ground truth segmentation masks that can be used to evaluate tracking predictions. A predicted point is considered correct if it falls within the segmentation mask of the target object for that frame.
+
+## Folder Structure
+
+```
+Molmo2-VideoTrackEval/
+├── README.md
+└── data/
+    ├── APTv2/
+    │   └── APTv2_point_tracks_with_masks.json
+    ├── dancetrack/
+    │   └── dancetrack_point_tracks_with_masks.json
+    ├── personpath22/
+    │   └── personpath22_point_tracks_with_masks.json
+    ├── sav/
+    │   └── sav_point_tracks_with_masks.json
+    └── sportsmot/
+        └── sportsmot_point_tracks_with_masks.json
+```
+
+## Video Sources
+
+| Dataset | Category | Download |
+|---------|----------|----------|
+| personpath22 | People | [PersonPath22](https://amazon-science.github.io/tracking-dataset/personpath22.html) |
+| sportsmot | Sports | [SportsMOT](https://codalab.lisn.upsaclay.fr/competitions/12424#participate) |
+| APTv2 | Animals | [APTv2](https://github.com/ViTAE-Transformer/APTv2) |
+| sav | Misc | [SA-V](https://ai.meta.com/datasets/segment-anything-video/) (Videos at 6 fps) |
+| dancetrack | Dancers | [DanceTrack](https://github.com/DanceTrack/DanceTrack?tab=readme-ov-file#dataset) |
+
+## License
+
+This dataset is licensed under ODC-BY-1.0. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).

data/APTv2/APTv2_point_tracks_with_masks.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e260e619eadb62ab5ee0aa62fb14f7dfc5cc084aebdf724c054d466d469cff53
+size 13820262

data/dancetrack/dancetrack_point_tracks_with_masks.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b50697cf511ec1b473fbd335c6a4bf1cd849d3cc802912e0965273271dc4d3c
+size 350921009

data/personpath22/personpath22_point_tracks_with_masks.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e93f56a825427c42067b318c8aee5d932feba20ada7194e2c97e53a1266f51d8
+size 109480453

data/sav/sav_point_tracks_with_masks.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3a59dfd418eeb9e287d027bea93a0fba1741577d95a86bb3a171a2d9cf87cbce
+size 2960756

data/sportsmot/sportsmot_point_tracks_with_masks.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e9211ea22aca0c3659548cfc7be75e4e4aa27eb5be996ba2542386ed3e613ed6
+size 170165351