Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from ultralytics import YOLO
+
+# Load the YOLOv8 model
+model = YOLO("best.pt")  # Ensure this file is in the same directory as app.py on Hugging Face
+
+# Define the inference function
+def predict(image):
+    # Convert the input image from RGB to BGR (OpenCV format)
+    image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    
+    # Run the model on the input image
+    results = model(image_bgr)
+    
+    # Extract the result image with detections
+    annotated_image = results[0].plot()  # Returns a BGR image with annotations
+    
+    # Convert the image back to RGB for displaying in Gradio
+    annotated_image_rgb = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
+    
+    return annotated_image_rgb
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="numpy", label="Upload an Image"),
+    outputs=gr.Image(type="numpy", label="Detected Objects"),
+    title="YOLOv8 Object Detection",
+    description="Upload an image to detect objects with YOLOv8 model."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch(share=True)