Update app.py

app.py

@@ -77,7 +77,7 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio app
-iface.launch()"""
+iface.launch()
 
 import gradio as gr
 import torch
@@ -127,5 +127,31 @@ iface = gr.Interface(
     examples=example_images  # Link the example images
 )
 
+# Launch the Gradio app
+iface.launch()"""
+
+import gradio as gr
+import torch
+from PIL import Image
+
+# Load the YOLO model
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='model.pt')  # Replace with your uploaded model's path
+
+# Define the prediction function
+def predict(image):
+    results = model(image)  # Perform object detection using YOLO
+    results.render()  # Render bounding boxes on the image
+    output_image = Image.fromarray(results.imgs[0])  # Convert to PIL image
+    return output_image
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(type="pil", label="Upload an Image"),  # Upload input as PIL Image
+    outputs=gr.outputs.Image(type="pil", label="Predicted Image with Bounding Boxes"),  # Output image
+    title="Object Detection App",
+    description="Upload an image, and the YOLO model will detect objects in it."
+)
+
 # Launch the Gradio app
 iface.launch()