BBoxEE is a open-source tool for annotating bounding boxes and exporting data to training object detectors. BBoxEE was specifically developed for the Animal Detection Network (Andenet) initiative, however, it is not limited to annotating camera trap data and can be used for any bounding box annotation task.
BBoxEE is actively under development by Peter Ersts of the Center for Biodiversity and Conservation at the American Museum of Natural History. Additional documentation will be forthcoming.
We have put together a quick start guide. This quick start guide is intended to introduce the basic functionality of BBoxEE. It is not intended to be a comprehensive user guide. Additional documentation will follow.
BBoxEE is being developed with Python 3.8.10 on Ubuntu 20.04 with the following libraries:
- PyQt6 (6.5.3)
- Pillow (10.1.0)
- Numpy (1.24.3)
- Tabulate (0.9.0)
- TensorFlow (2.13.1)
- Torch (2.1.0)
- yolov5 (7.0.13)
Build a virtual environment and install the dependencies:
cd [Your BBoxEE Workspace]
[Apple M1 Note]
If you follow the Linux steps PyQt6 may not install due to clang not finding Python.h
You can resolve this by adding and additional environmental variable with the following:
export C_INCLUDE_PATH=/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Headers
[Linux & OSX]
python3 -m venv bboxee-env
source bboxee-env/bin/activate
git clone https://github.com/persts/BBoxEE
python -m pip install --upgrade pip
python -m pip install -r BBoxEE/requirements.txt
[Windows]
python -m venv bboxee-env
bboxee-env\Scripts\activate.bat
git clone https://github.com/persts/BBoxEE
python -m pip install --upgrade pip
python -m pip install -r BBoxEE\requirements.txtcd BBoxEE
python main.py