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app.py

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+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+
+# Load YOLO model
+model = YOLO("best.pt")
+
+# Define the prediction function
+def detect_species(files):
+    """
+    Detect species in uploaded images using the YOLO model.
+    
+    Args:
+        files (list): List of uploaded image files.
+    
+    Returns:
+        list: Annotated images or error messages for each file.
+    """
+    annotated_images = []
+    for file in files:  # Loop through the list of uploaded files
+        try:
+            # Open and process the image
+            image = Image.open(file)
+            image = np.array(image)  # Convert to numpy array
+            results = model(image)  # Run the YOLO model
+            annotated_image = results[0].plot()  # Generate annotated image
+            annotated_images.append(annotated_image)  # Add to results
+        except Exception as e:
+            # Handle errors (e.g., unsupported or corrupt files)
+            error_message = f"Error processing file {file.name}: {str(e)}"
+            print(error_message)  # Log the error
+            annotated_images.append(np.zeros((100, 100, 3)))  # Placeholder image
+    return annotated_images
+
+# Create the Gradio app
+app = gr.Interface(
+    fn=detect_species,
+    inputs=gr.Files(file_types=["image"], label="Upload Images"),  # Allow multiple image uploads
+    outputs=gr.Gallery(label="Detection Results"),  # Display results in a gallery
+    title="Plant Species Detector",
+    description="Upload one or more leaf images, and the model will detect the species.",
+    examples=["example1.jpg", "example2.jpg"],  # Optional: Add example images
+)
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch(share=True)  # Set share=True to get a public URL

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:40cf469a5957a0bee78266cde69c7a63dcedb12ec9cb75d3b174a2dec526981e
+size 19196051

requirements.txt

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+gradio==4.44.1
+ultralytics==8.3.40
+numpy<2.0,>=1.26.0
+pillow<11.0,>=10.0.0