Create app.py

app.py

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+import gradio as gr
+import cv2
+import torch
+import numpy as np
+
+# Load the YOLOv5 model
+model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
+
+# Function to run inference on an image
+def run_inference(image):
+    # Convert the image from PIL format to a format compatible with OpenCV
+    image = np.array(image)
+
+    # Run YOLOv5 inference
+    results = model(image)
+
+    # Convert the annotated image from BGR to RGB for display
+    annotated_image = results.render()[0]
+    annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
+
+    return annotated_image
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=run_inference,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="YOLOv5 Object Detection",
+    description="Upload an image to run YOLOv5 object detection and see the results."
+)
+
+# Launch the app
+interface.launch()