Create app.py

app.py

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+# Import required libraries
+import torch
+import gradio as gr
+from PIL import Image
+
+# Load the pretrained YOLOv5 model
+model = torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True)
+
+# Function to process the image and return detections
+def detect_objects(image):
+    # Perform inference on the uploaded image
+    results = model(image)
+    
+    # Plot results on the image (YOLOv5 provides results with bounding boxes, class names, and confidence scores)
+    results_img = results.render()[0]  # Render the detections on the image
+    
+    # Convert to a PIL Image for compatibility with Gradio
+    return Image.fromarray(results_img)
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="Object Detection App",
+    description="Upload an image to detect objects using the YOLOv5 model."
+)
+
+# Launch the Gradio app
+interface.launch()