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import gradio as gr
import torch
import cv2
import numpy as np
from PIL import Image
from ultralytics import YOLO
# Load YOLOv11 Model
model_path = "best.pt"
model = YOLO(model_path)
def predict(image):
image = np.array(image)
results = model(image)
# Draw bounding boxes
for result in results:
for box in result.boxes:
x1, y1, x2, y2 = map(int, box.xyxy[0])
conf = box.conf[0]
cls = int(box.cls[0])
label = f"{model.names[cls]} {conf:.2f}"
cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
cv2.putText(image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
return Image.fromarray(image)
# Gradio Interface
iface = gr.Interface(fn=predict, inputs="image", outputs="image", title="YOLOv11 Object Detection")
iface.launch()
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