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import gradio as gr | |
from ultralytics import YOLO | |
from PIL import Image | |
# Load the trained YOLOv8 model | |
model = YOLO("best.pt") | |
# Define the prediction function | |
def predict(image): | |
results = model(image) # Run YOLOv8 model on the uploaded image | |
results_img = results[0].plot() # Get image with bounding boxes | |
return Image.fromarray(results_img) | |
# Create Gradio interface | |
interface = gr.Interface( | |
fn=predict, | |
inputs=gr.Image(type="pil"), | |
outputs=gr.Image(type="pil"), | |
title="Helmet Detection with YOLOv8", | |
description="Upload an image to detect helmets." | |
) | |
# Launch Gradio app | |
interface.launch(share=True) | |