Create app.py

app.py

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+# Install required libraries
+!pip install ultralytics opencv-python matplotlib gradio
+
+import gradio as gr
+import cv2
+import numpy as np
+from ultralytics import YOLO
+
+# Load YOLOv8 model
+model = YOLO("yolov8s.pt")
+
+def detect_objects(image):
+    """
+    Function to perform object detection using YOLOv8.
+    """
+    # Convert image to RGB (Gradio provides images in numpy array format)
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+    # Run YOLOv8 inference
+    results = model(image_rgb)
+
+    # Convert the annotated image back to OpenCV format
+    annotated_image = results[0].plot()  # Get annotated image
+
+    return annotated_image  # Return the image with bounding boxes
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=detect_objects,  # Function to call
+    inputs=gr.Image(type="numpy"),  # Input: Image
+    outputs=gr.Image(type="numpy"),  # Output: Processed Image
+    title="YOLOv8 Object Detection",
+    description="Upload an image, and YOLOv8 will detect objects in it."
+)
+
+# Launch the Gradio app
+interface.launch()