Honeybee Segmentation and Tracking Datasets

Here you can find data resulting from our publications on markerless honeybee detection and tracking.

Honeybee detection

This dataset was created as a part of the study Towards dense object tracking in a 2D honeybee hive. It comprises frames and annotations of 2 video recordings of an observation bee hive. The recordings were done at 30 fps and 70 fps, in each of them 360 frames were annotated in a consecutive sequence at 2 fps.

The annotation includes positions and orientation angles of all bees in an image within a selected region with high bee density. Annotating was split into tasks on 1024x1024 px windows as shown below:

30 fps recording
70 fps recording

2 object classes were introduced: (1) fully visible bees, (2) abdomens of bees partially hidden inside cells of a honey comb. The orientation angle of objects of class 2 is always 0. The format of annotation files is:
offset_x offset_y class position_x position_y angle

Files for download:

Due to the size of the images we did not post the full recordings here. If you are interested in other parts of this recording please contact us.


Tutorial with a simplified segmentation-based detection can be found here: https://github.com/oist/DenseObjectDetection. We also provide a checkpoint pretrained on the 30fps dataset.

A parametrizable version of our annotation tool can be found here: https://github.com/oist/DenseObjectAnnotation.


Honeybee tracking

This dataset is the result of our study Pixel personality for dense object tracking in a 2D honeybee hive and it comprises detection and trajectory information from two beehive recordings. The videos were originally recorded at 30 fps, we downsampled them to 10 fps 5 min segments. Object detections were done as described in the work above. Detection files are numbered according to the video frames and have format: position_x,position_y,object_class,orientation_angle. Trajectory files comprise ~50% of individuals that were correctly tracked for > 80% of time. The file format is frame_nb,position_x,position_y,object_class,orientation_angle. 

Files for download:

Recording 1:

Recording 2: