Honey Bee Detection Model Computer Vision Project
Updated 2 years ago
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Purpose of the Project
This project started as a way to add real-time counts of bees with/without pollen entering my backyard beehive to append some additional information to a livestream of the hive, and to correlate behavior at the hive entrance to weather, temperature, etc. Since then, I've added additional training data not specific to my hive which accounts for classification of drones and queens in addition to bees/pollen bees. Currently the model generalizes reasonably well, but more training data is required.
Assessed Classes & Labeling Guidelines
- bees (either workers or foragers)
- bees carrying pollen
- drones
- queens
Labeling should cover the entire body of the bee, excluding the wings as per the following example: 
For the class of bees carrying pollen, it is acceptable to extend the box to include the visible pollen packs to distinguish this from the bee class: 
Sample Results
Sample video of backyard hive entrance with low to moderate level of activity: https://www.youtube.com/watch?v=qZW5eYd0Yw8&t=2266s
Generic sample video of single bee: https://www.youtube.com/watch?v=A1x6VA8TWCg
Latest YOLOv5 Weights Files
Latest weights files for use by others are posted on my github here: https://github.com/mattnudi/bee-detection
These files will be updated as more images are added to the dataset
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
honey-bee-detection-model-zgjnb_dataset,
title = { Honey Bee Detection Model Dataset },
type = { Open Source Dataset },
author = { Matt Nudi },
howpublished = { \url{ https://universe.roboflow.com/matt-nudi/honey-bee-detection-model-zgjnb } },
url = { https://universe.roboflow.com/matt-nudi/honey-bee-detection-model-zgjnb },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { oct },
note = { visited on 2024-12-21 },
}