The MillionTrees benchmark is designed to provie open, reproducible and rigorous evaluation of tree detection algorithms. ]This repo is the python package for rapid data sharing and evaluation.
We are in the process of release public data, these are datasets that have previously been published and have a DOI. We will followup this release, likely with a 1.0 tag, of the previously unpublished parts of the dataset along with a scientific manuscript.
TreeBoxes: 4411 images, 2 splits, 197343 rows TreePolygons: 18437 images, 2 splits, 760347 rows TreePoints: 3929 images, 2 splits, 256184 rows
There has been a tremendous number of tree crown detection benchmarks, but a lack of progress towards a single algorithm that can be used globally across aquisition sensors, forest type and annotation geometry. Our view is that the hundreds of tree detection algorithms for RGB data published in the last 10 years are all data starved. There are many good models, but they can only be so useful with the small datasets any research team can collect. The result is years of effort in model development, but ultimately a lacking solution for a large audience. The MillionTrees dataset seeks to collect a million annotations across point, polygon and box geometries at a global scale.
pip install MillionTrees
To build from the GitHub source and install the required dependencies, follow these instructions:
-
Clone the GitHub repository:
git clone https://github.com/username/repo.git -
Change to the repository directory:
cd repo -
Install the required dependencies using pip:
pip install -r requirements.txt -
(Optional) Build and install the package:
python setup.py install
Once the installation is complete, you can use the MillionTrees package in your Python projects.
Datasets are documented on ReadTheDocs with sample images overlayed with annotations. https://milliontrees.idtrees.org/en/latest/datasets.html
The design of the MillionTrees benchmark was inspired by the WILDS benchmark, and we are grateful to their work, as well as Sara Beery for suggesting the use of this template.