Honey Bee Detection Model Computer Vision Project

Matt Nudi

Updated 2 years ago

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Classes (4)
bee drone
pollenbee
queen

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Description

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

Use This Trained Model

Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.

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Cite This Project

LICENSE
CC BY 4.0

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 2024-11-21 },
                            }
                        
                    

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