Datasets
Data collected by us is available via Google Drive, mostly due to the size of the data. This includes:
Photosā
Manually taken photos from inspections of the beehive frames (no annotations, JPG, ~15MP) in years: 2019, 2020, 2021, 2024.
Example foto (webp re-compressed for the web):
Videosā
šļøāšØļø Entrance Observer videos š„ of the hive entrance
2025ā
Videos were encoded on the edge as follows:
Input #0
Metadata:
major_brand : isom
minor_version : 512
compatible_brands: isomiso2mp41
encoder : Lavf59.27.100
Duration: 00:00:30.03, start: 0.000000, bitrate: 14927 kb/s
Stream #0:0[0x1](und): Video: mpeg4 (Simple Profile) (mp4v / 0x7634706D), yuv420p, 1280x720 [SAR 1:1 DAR 16:9], 14926 kb/s, 15.02 fps, 15.02 tbr, 12016 tbn (default)
Dataset type 1ā
- September 04.
- some chunks have pairs with
_detect.mp4
suffixes, showing yolov8 model detections. - 5-25mb per chunk. mp4
- some chunks have pairs with
- September 05
- Dataset duration ~8h (11:30 - 20:00 EEST)
- Sunny weather.
- Zoom at landing board ~ 40cm wide
- ~ 25GB in total
- 1280x720px. 30 min chunks. 15FPS. 5-25mb per chunk. mp4
- file names are in UTC timestamps.
- metrics in jsonl format
- bee tracks in jsonl format
- September 6th. Sunny weather.
- Dataset duration ~8h (8:00-15:36, 19:35-20:35 EEST)
- ~13:20 a flight pattern is seen
- metrics in jsonl
- bee tracks in jsonl
Example video (ffmpeg re-compressed for the web):
Dataset type 2ā
- September 7th
- September 8th
- September 9th
- Dataset duration ~3h (12:00-15:00 EEST)
Dataset type 3ā
Camera placed on second hive section (closer), changed zoom, removed glass and aluminium boundaries, added stones instead
- September 10th
- 11:30 - 17:00
- September 11th
- rainy day, very little activity
- September 13th
- rainy day
- September 14th
- cloudy day
2024ā
- 640x480 resolution, 10sec chunks
- white background, lots of shadows.
- ~ 1h of videos in total, 1.1GB
2023ā
18-20 july 2023 - small set of videos for testing neural network detection results
- 3840Ā xĀ 2160, varying positions and length
External resources that could be usedā
- Current bee detection model uses yolo v5 weights from https://universe.roboflow.com/matt-nudi/honey-bee-detection-model-zgjnb
- Datasets from the Brno team: https://www.kaggle.com/datasets/imonbilk/bee-dataset-but-1 https://www.kaggle.com/datasets/imonbilk/bee-dataset-but-2 https://www.kaggle.com/datasets/imonbilk/bee-dataset-but-hs
- roboflow datasets (with annotations) https://universe.roboflow.com/search?q=varroa
- inaturalist datasets https://www.inaturalist.org/observations?place_id=any&taxon_id=54328 https://www.inaturalist.org/observations?place_id=any&taxon_id=47219