Add Get Started code and Paper citation

README.md

@@ -2,10 +2,52 @@
 license: mit
 language:
 - en
-tags:
-- deepforest
 ---
 
+
 ## Tree Crown Detection in RGB Airborne Imagery
 
-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).
+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).
+
+- **Repository:** https://github.com/weecology/DeepForest
+- **Paper :** https://www.sciencedirect.com/science/article/pii/S157495412030011X
+- **Demo :** https://huggingface.co/spaces/weecology/deepforest-demo 
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```
+from deepforest import main
+from deepforest import get_data
+from deepforest.visualize import plot_results
+# Initialize the model class
+model = main.deepforest()
+
+# Load a pretrained tree detection model from Hugging Face
+model.load_model(model_name="weecology/deepforest-tree", revision="main")
+
+sample_image_path = get_data("OSBS_029.png")
+img = model.predict_image(path=sample_image_path)
+plot_results(img)
+```
+
+
+## Citation
+```
+@article{WEINSTEIN2020101061,
+title = {Cross-site learning in deep learning RGB tree crown detection},
+journal = {Ecological Informatics},
+volume = {56},
+pages = {101061},
+year = {2020},
+issn = {1574-9541},
+doi = {https://doi.org/10.1016/j.ecoinf.2020.101061},
+url = {https://www.sciencedirect.com/science/article/pii/S157495412030011X},
+author = {Ben G. Weinstein and Sergio Marconi and Stephanie A. Bohlman and Alina Zare and Ethan P. White},
+```
+
+## Model Card Authors
+
+Ben G. Weinstein, Sergio Marconi, Stephanie A. Bohlman, Alina Zare and Ethan P. White