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allenai/Molmo2-VideoTrack

Molmo2-VideoTrack Molmo2-VideoTrack is a dataset of video point tracking annotations collected from human annotators across 16 video datasets. It can be used to fine-tune vision-language models for video object tracking via point trajectories. Molmo2-VideoTrack is part of the Molmo2 dataset collection and was used to train the Molmo2 family of models. Quick links: ๐Ÿ“ƒ Paper ๐ŸŽฅ Blog with Videos Usage from datasets import load_dataset # Load entire dataset ds =โ€ฆ See the full description on the dataset page: https://huggingface.co/datasets/allenai/Molmo2-VideoTrack.

sourceHugging Faceodc-byupdated 9mo agoView on Hugging Face
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Molmo2-VideoTrack

Molmo2-VideoTrack is a dataset of video point tracking annotations collected from human annotators across 16 video datasets. It can be used to fine-tune vision-language models for video object tracking via point trajectories.

Molmo2-VideoTrack is part of the Molmo2 dataset collection and was used to train the Molmo2 family of models.

Quick links:

Usage

python
from datasets import load_dataset

# Load entire dataset
ds = load_dataset("allenai/Molmo2-VideoTrack", split="train")

# Filter by video dataset
dancetrack = ds.filter(lambda x: x == 'dancetrack', input_columns='video_dataset')

Data Format

Each row contains tracking annotations for one or more objects in a video clip:

FieldDescription
idUnique identifier for this annotation
videoVideo filename
cliptrimmed clip id
video_datasetSource dataset name (e.g., 'dancetrack', 'mose')
video_sourceVideo directory used in training (can be ignored)
expText expression describing the tracked object(s)
obj_idList of object IDs per video
mask_idList of mask IDs corresponding to tracked objects starting from '0'
pointsList of point trajectories per object. Each entry contains object_id (corresponding to an ID in mask_id) and points (list of [x, y] coordinates per frame). Example: [{'object_id': '0', 'points': [[x1, y1], [x2, y2], ...]}, ...]
segmentsList of segment annotations per object. Each entry contains object_id (corresponding to an ID in mask_id) and segments. Example: [{'object_id': '0', 'segments': [...]}, ...]
start_frameStarting frame index for this clip (use to trim the source video)
end_frameEnding frame index for this clip (use to trim the source video)
wVideo width
hVideo height
n_framesNumber of frames in the clip
fpsUsed in training

Important: start_frame and end_frame indicate which portion of the source video to use. You need to trim the video to this range โ€” the annotations correspond to frames within [start_frame, end_frame], not the entire video.

Folder Structure

Molmo2-VideoTrack/
โ”œโ”€โ”€ README.md
โ””โ”€โ”€ data/
    โ”œโ”€โ”€ animaltrack/
    โ”‚   โ””โ”€โ”€ point_tracks.parquet
    โ”œโ”€โ”€ APTv2/
    โ”‚   โ””โ”€โ”€ point_tracks.parquet
    โ”œโ”€โ”€ ...
    โ””โ”€โ”€ {video_dataset}/
        โ””โ”€โ”€ point_tracks.parquet

Video Sources

The table below contains information on the sources of the third party datasets used or referenced in curating the data for Molmo2-VideoTrack. We do not provide video files or share the original raw data from datasets with restrictions on use and distribution according to the source license. We instead provide the links, license information, and notes for downloading videos from the original datasets for transparency and reproducibility. Please verify the licenses and use requirements that apply to each dataset before downloading as they may change or be updated by the dataset providers.

DatasetCategoryAnnotation SourceDownloadDataset LicenseNote
moseGeneralSegmentation<a href="https://huggingface.co/datasets/FudanCVL/MOSE" target="_blank">MOSE</a>CC BY-NC-SA 4.0
mosev2GeneralSegmentation<a href="https://huggingface.co/datasets/FudanCVL/MOSEv2" target="_blank">MOSEv2</a>CC BY-NC-SA 4.0
savGeneralSegmentation<a href="https://ai.meta.com/datasets/segment-anything-video/" target="_blank">SA-V</a>CC BY 4.0Sampled at 6 fps from the original 24 fps video to match the segmentation annotation
vipsegGeneralSegmentation<a href="https://github.com/VIPSeg-Dataset/VIPSeg-Dataset/" target="_blank">VIPSeg</a>Non-commercial research use onlyChange to 720p format
animaltrackAnimalsBounding Box<a href="https://hengfan2010.github.io/projects/AnimalTrack/" target="_blank">AnimalTrack</a>Non-commercial research use onlyTrain and val videos are used due to data scarcity
APTv2AnimalsBounding Box<a href="https://github.com/ViTAE-Transformer/APTv2" target="_blank">APTv2</a>Apache 2.0
bftBird FlocksBounding Box<a href="https://george-zhuang.github.io/nettrack/" target="_blank">BFT</a>Apache 2.0
soccernetSportsBounding Box<a href="https://www.soccer-net.org/data" target="_blank">SoccerNet</a>Non-commercial research use onlyFill in the NDA form to access the videos
sportsmotSportsBounding Box<a href="https://codalab.lisn.upsaclay.fr/competitions/12424#participate" target="_blank">SportsMOT</a>CC BY-NC 4.0
teamtrackSportsBounding Box<a href="https://github.com/AtomScott/TeamTrack" target="_blank">TeamTrack</a>MIT
mot2020PedestriansBounding Box<a href="https://motchallenge.net/data/MOT20/" target="_blank">MOT20</a>CC BY-NC-SA 3.0
personpath22PedestriansBounding Box<a href="https://amazon-science.github.io/tracking-dataset/personpath22.html" target="_blank">PersonPath22</a>CC BY-NC 4.0
dancetrackDancersBounding Box<a href="https://github.com/DanceTrack/DanceTrack?tab=readme-ov-file#dataset" target="_blank">DanceTrack</a>Non-commercial research use only
bdd100kAutonomous DrivingBounding Box<a href="http://128.32.162.150/bdd100k/videoparts/" target="blank">BDD100K</a>BSD-3Download only bdd100kvideostrain_00.zip
uavdtUAVBounding Box<a href="https://sites.google.com/view/grli-uavdt/%E9%A6%96%E9%A1%B5" target="_blank">UAVDT</a>Research use only
seadronesUAVBounding Box<a href="https://seadronessee.cs.uni-tuebingen.de/dataset" target="_blank">SeaDronesSee</a>CC0 / UnknownUse 'Multi-Object Tracking'

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. Please refer to the Video Sources section for the original datasets that provide the videos used to generate the segmentations and point tracks for this dataset. All use of the videos and original data from these datasets are subject to the licenses and terms of use provided by the sources. Please check the sources to determine if they are appropriate for your use case.