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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()
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