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import cv2
import numpy as np
import os
from django.conf import settings
from ultralytics import YOLO
# Global model variable
_model = None
def get_model():
global _model
if _model is None:
MODEL_PATH = os.path.join(settings.BASE_DIR, 'best.pt')
try:
_model = YOLO(MODEL_PATH)
except Exception as e:
print(f"Error loading model: {e}")
return _model
def run_detection(image_path):
"""
Runs YOLO detection on an image file path and returns a list of detections.
"""
model = get_model()
if model is None:
return []
img = cv2.imread(image_path)
if img is None:
return []
results = model(img)
detections = []
for r in results:
boxes = r.boxes
for box in boxes:
# Get coordinates in percentage for the frontend
x_center, y_center, w, h = box.xywhn[0].tolist()
x = (x_center - w/2) * 100
y = (y_center - h/2) * 100
width = w * 100
height = h * 100
conf = float(box.conf[0])
cls = int(box.cls[0])
label = model.names[cls]
detections.append({
"id": len(detections),
"x": x,
"y": y,
"width": width,
"height": height,
"label": label,
"confidence": conf * 100
})
return detections
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