Create app.py

app.py

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+import gradio as gr
+import torch
+from PIL import Image
+import requests
+
+# Load the trained YOLOv8 model
+model = torch.hub.load('ultralytics/yolov8', 'custom', path='best.pt')
+
+def detect_objects(image):
+    # Run the YOLOv8 model on the input image
+    results = model(image)
+
+    # Extract the bounding boxes and labels from the results
+    boxes = results.xyxy[0].numpy()  # Bounding boxes
+    labels = results.names  # Labels
+
+    # Convert the image to a PIL Image for display
+    img = Image.fromarray(results.render()[0])
+
+    return img
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs="image",
+    title="YOLOv8 Object Detection",
+    description="Upload an image to detect objects using the YOLOv8 model."
+)
+
+# Launch the interface
+iface.launch()