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Runtime error
| import cv2 | |
| import numpy as np | |
| from ultralytics import YOLO | |
| import os | |
| import logging | |
| logging.basicConfig( | |
| filename="app.log", | |
| level=logging.INFO, | |
| format="%(asctime)s - %(levelname)s - %(message)s" | |
| ) | |
| BASE_DIR = os.path.dirname(os.path.abspath(__file__)) | |
| MODEL_PATH = os.path.abspath(os.path.join(BASE_DIR, "../../models/yolov8m.pt")) | |
| try: | |
| model = YOLO(MODEL_PATH) | |
| logging.info("Loaded YOLOv8m model for lighting check.") | |
| except Exception as e: | |
| logging.error(f"Failed to load YOLOv8m model: {str(e)}") | |
| model = None | |
| def process_lighting(frame): | |
| if model is None: | |
| logging.error("YOLO model not loaded. Skipping lighting check.") | |
| return [], frame | |
| try: | |
| results = model(frame) | |
| except Exception as e: | |
| logging.error(f"Error during YOLO inference: {str(e)}") | |
| return [], frame | |
| detections = [] | |
| line_counter = 1 | |
| for r in results: | |
| for box in r.boxes: | |
| conf = float(box.conf[0]) | |
| if conf < 0.5: | |
| continue | |
| cls = int(box.cls[0]) | |
| label = model.names[cls] | |
| if label != "lighting": | |
| continue | |
| xyxy = box.xyxy[0].cpu().numpy().astype(int) | |
| x_min, y_min, x_max, y_max = xyxy | |
| detection_label = f"Line {line_counter} - {label.capitalize()} (Conf: {conf:.2f})" | |
| detections.append({ | |
| "type": label, | |
| "label": detection_label, | |
| "confidence": conf, | |
| "coordinates": [x_min, y_min, x_max, y_max] | |
| }) | |
| color = (0, 0, 255) # Blue as requested | |
| cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2) | |
| cv2.putText(frame, detection_label, (x_min, y_min - 10), | |
| cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2) | |
| line_counter += 1 | |
| logging.info(f"Detected {len(detections)} lighting fixtures in road_safety.") | |
| return detections, frame |