example for Shirley

README.md

@@ -1,6 +1,6 @@
 ---
 title: DeepForest
-emoji: 🔥
+emoji: 🌴
 colorFrom: pink
 colorTo: purple
 sdk: gradio

app.py

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+import gradio as gr
+from deepforest import main
+import matplotlib.pyplot as plt
+
+# Initialize the deepforest model and use the released version
+model = main.deepforest()
+model.use_release()
+
+def predict_and_visualize(image):
+    """
+    Function to predict and visualize the image using deepforest model.
+    
+    Args:
+    - image: An image array.
+    
+    Returns:
+    - An image with predictions visualized.
+    """
+    # Predict image and return plot. Since Gradio passes image as array, save it temporarily.
+    temp_path = "/tmp/uploaded_image.png"
+    plt.imsave(temp_path, image)
+    img = model.predict_image(path=temp_path, return_plot=True)
+    
+    # Since the output is BGR and matplotlib (and hence Gradio) needs RGB, we convert the color scheme
+    img_rgb = img[:, :, ::-1]
+    
+    # Return the RGB image
+    return img_rgb
+
+# Define the Gradio interface
+iface = gr.Interface(fn=predict_and_visualize,
+                     inputs=gr.Image(type="numpy", label="Upload Image"),
+                     outputs=gr.Image(label="Predicted Image"),
+                     title="DeepForest Tree Detection",
+                     examples=["./example.jpg"]
+                     description="Upload an image to detect trees using the DeepForest model.")
+
+# Launch the Gradio app
+iface.launch()

requirements.txt

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+gradio
+deepforest
+matplotlib