app .py

from ultralytics import YOLO
import cv2
import gradio as gr

# Load the YOLO model
model = YOLO('yolov8n.pt')

def detect_objects(image):
    # Convert PIL image (from Gradio webcam) → OpenCV format (BGR)
    frame = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

    # Perform object detection
    results = model(frame)

    # Plot detections (draw bounding boxes)
    annotated_frame = results[0].plot()

    # Convert back to RGB for displaying in Gradio
    annotated_frame = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)

    return annotated_frame

# Create Gradio interface (this works in Hugging Face Spaces)
demo = gr.Interface(
    fn=detect_objects,
    inputs=gr.Image(source="webcam", streaming=True),  # Enable live camera
    outputs="image",
    title="🎥 Real-time Object Detection (YOLOv8)",
    description="Detects and labels objects in live camera feed using YOLOv8."
)

demo.launch()