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Update services/operations_maintenance/pothole_detection.py
Browse files
services/operations_maintenance/pothole_detection.py
CHANGED
@@ -3,15 +3,20 @@ import numpy as np
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from ultralytics import YOLO
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import os
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import logging
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logging.basicConfig(
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filename="app.log",
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level=logging.INFO,
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format="%(asctime)s - %(levelname)s - %(message)s"
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)
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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MODEL_PATH = os.path.abspath(os.path.join(BASE_DIR, "../../models/yolov8m.pt"))
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try:
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model = YOLO(MODEL_PATH)
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logging.info("Loaded YOLOv8m model for pothole detection.")
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@@ -19,18 +24,37 @@ except Exception as e:
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logging.error(f"Failed to load YOLOv8m model: {str(e)}")
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model = None
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def process_potholes(frame):
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if model is None:
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logging.error("YOLO model not loaded. Skipping pothole detection.")
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return [], frame
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try:
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-
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except Exception as e:
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logging.error(f"Error during YOLO inference: {str(e)}")
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return [], frame
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detections = []
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line_counter = 1
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for r in results:
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@@ -55,8 +79,15 @@ def process_potholes(frame):
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color = (255, 127, 80) # Coral (red + orange mix)
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cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2)
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cv2.putText(
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line_counter += 1
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from ultralytics import YOLO
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import os
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import logging
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from typing import Tuple, List, Dict, Any
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# Configure logging
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logging.basicConfig(
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filename="app.log",
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level=logging.INFO,
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format="%(asctime)s - %(levelname)s - %(message)s"
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)
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# Define base directory and model path
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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MODEL_PATH = os.path.abspath(os.path.join(BASE_DIR, "../../models/yolov8m.pt"))
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# Initialize YOLO model
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try:
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model = YOLO(MODEL_PATH)
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logging.info("Loaded YOLOv8m model for pothole detection.")
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logging.error(f"Failed to load YOLOv8m model: {str(e)}")
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model = None
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def process_potholes(frame: np.ndarray) -> Tuple[List[Dict[str, Any]], np.ndarray]:
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"""
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Detect potholes in a video frame using YOLOv8m.
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Args:
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frame (np.ndarray): Input frame in BGR format.
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Returns:
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Tuple[List[Dict[str, Any]], np.ndarray]: A tuple containing:
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- List of detected potholes.
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- Annotated frame with bounding boxes and labels.
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"""
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# Validate input frame
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if not isinstance(frame, np.ndarray) or frame.size == 0:
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logging.error("Invalid input frame provided to pothole_detection.")
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return [], frame
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# Check if model is loaded
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if model is None:
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logging.error("YOLO model not loaded. Skipping pothole detection.")
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return [], frame
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try:
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# Perform YOLO inference
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results = model(frame, verbose=False)
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logging.debug("Completed YOLO inference for pothole detection.")
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except Exception as e:
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logging.error(f"Error during YOLO inference: {str(e)}")
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return [], frame
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detections: List[Dict[str, Any]] = []
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line_counter = 1
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for r in results:
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color = (255, 127, 80) # Coral (red + orange mix)
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cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2)
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cv2.putText(
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frame,
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detection_label,
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(x_min, y_min - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.6,
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color,
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2
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)
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line_counter += 1
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