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Create bridge_pier_check.py
Browse files
services/under_construction/bridge_pier_check.py
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# services/under_construction/bridge_pier_check.py
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import cv2
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import numpy as np
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from ultralytics import YOLO
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import os
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# Load YOLOv8m model
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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MODEL_PATH = os.path.join(BASE_DIR, "../../models/yolov8m.pt")
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model = YOLO(MODEL_PATH)
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def detect_bridge_piers(frame):
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"""
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Detect bridge piers in a frame using YOLOv8m.
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Args:
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frame: Input frame (numpy array)
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Returns:
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dict: Detection results with numbered labels
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numpy array: Annotated frame
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"""
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# Run YOLOv8 inference
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results = model(frame)
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detections = []
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line_counter = 1 # Initialize counter for numbered labels
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# Process detections
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for r in results:
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for box in r.boxes:
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conf = float(box.conf[0])
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if conf < 0.5:
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continue
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cls = int(box.cls[0])
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label = model.names[cls]
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if label != "bridge_pier": # Assuming "bridge_pier" class exists
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continue
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xyxy = box.xyxy[0].cpu().numpy()
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x_min, y_min, x_max, y_max = map(int, xyxy)
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# Add numbered label
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detection_label = f"Line {line_counter} - Bridge Pier (Conf: {conf:.2f})"
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detections.append({
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"label": detection_label,
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"confidence": conf,
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"coordinates": [x_min, y_min, x_max, y_max]
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})
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# Draw bounding box and label
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color = (0, 0, 255) # Red for bridge piers
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cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2)
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cv2.putText(frame, detection_label, (x_min, y_min - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
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line_counter += 1
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return {"detections": detections, "frame": frame}
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def process_bridge_piers(frame):
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"""
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Wrapper function for integration with app.py.
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"""
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result = detect_bridge_piers(frame)
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return result["detections"], result["frame"]
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