| import gradio as gr | |
| from ultralytics import YOLO | |
| import numpy as np | |
| from PIL import Image | |
| # Load YOLO model | |
| model = YOLO("yolo11n-pose.pt") # Replace with your YOLO model path | |
| # Function to process the input image | |
| def process_image(image): | |
| # YOLO inference | |
| results = model(image) | |
| # The result is a list, access the first item | |
| processed_image = results[0].plot() # .plot() returns the image with detections | |
| # Return the processed image for display | |
| return processed_image | |
| # Gradio Interface | |
| iface = gr.Interface( | |
| fn=process_image, # Function to call on image input | |
| inputs=gr.Image(type="pil"), # Image input (Upload an image file) | |
| outputs=gr.Image(type="pil"), # Output processed image | |
| live=True, # Enable live feedback (optional) | |
| title="Object Detection with YOLO", | |
| description="Upload an image for object detection using YOLO." | |
| ) | |
| # Launch the Gradio app | |
| iface.launch() | |