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--- |
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license: mit |
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language: |
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- en |
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--- |
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## Tree Crown Detection in RGB Airborne Imagery |
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The model was initially described in [Remote Sensing](https://www.mdpi.com/2072-4292/11/11/1309) on a single site. The prebuilt model uses a semi-supervised approach in which millions of moderate quality annotations are generated using a LiDAR unsupervised tree detection algorithm, followed by hand-annotations of RGB imagery from select sites. Comparisons among geographic sites were added to [Ecological Informatics](https://www.sciencedirect.com/science/article/pii/S157495412030011X). The model was further improved, and the Python package was released in [Methods in Ecology and Evolution](https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.13472). |
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- **Repository:** https://github.com/weecology/DeepForest |
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- **Paper :** https://www.sciencedirect.com/science/article/pii/S157495412030011X |
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- **Demo :** https://huggingface.co/spaces/weecology/deepforest-demo |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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``` |
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from deepforest import main |
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from deepforest import get_data |
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from deepforest.visualize import plot_results |
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# Initialize the model class |
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model = main.deepforest() |
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# Load a pretrained tree detection model from Hugging Face |
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model.load_model(model_name="weecology/deepforest-tree", revision="main") |
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sample_image_path = get_data("OSBS_029.png") |
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img = model.predict_image(path=sample_image_path) |
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plot_results(img) |
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``` |
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## Citation |
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``` |
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@article{WEINSTEIN2020101061, |
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title = {Cross-site learning in deep learning RGB tree crown detection}, |
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journal = {Ecological Informatics}, |
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volume = {56}, |
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pages = {101061}, |
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year = {2020}, |
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issn = {1574-9541}, |
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doi = {https://doi.org/10.1016/j.ecoinf.2020.101061}, |
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url = {https://www.sciencedirect.com/science/article/pii/S157495412030011X}, |
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author = {Ben G. Weinstein and Sergio Marconi and Stephanie A. Bohlman and Alina Zare and Ethan P. White}, |
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``` |
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## Model Card Authors |
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Ben G. Weinstein, Sergio Marconi, Stephanie A. Bohlman, Alina Zare and Ethan P. White |
