services/crack_detection_service.py

import cv2
import numpy as np

def detect_cracks_and_holes(frame):
    try:
        # Convert frame to grayscale
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        blurred = cv2.GaussianBlur(gray, (5, 5), 0)

        # Edge detection using Canny
        edges = cv2.Canny(blurred, 30, 100)  # Lower thresholds to detect more cracks

        # Morphological operations to enhance cracks and holes
        kernel = np.ones((3, 3), np.uint8)
        dilated = cv2.dilate(edges, kernel, iterations=2)
        eroded = cv2.erode(dilated, kernel, iterations=1)

        # Find contours
        contours, _ = cv2.findContours(eroded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        items = []
        for contour in contours:
            # Filter small contours (noise)
            area = cv2.contourArea(contour)
            if area < 30:  # Reduced threshold to catch smaller cracks
                continue

            # Get bounding box
            x, y, w, h = cv2.boundingRect(contour)
            area = w * h

            # Calculate aspect ratio and circularity
            aspect_ratio = float(w) / h if h > 0 else 0
            perimeter = cv2.arcLength(contour, True)
            circularity = 4 * np.pi * area / (perimeter * perimeter) if perimeter > 0 else 0

            # Classify as crack or hole
            if 0.05 < aspect_ratio < 20 and circularity < 0.4:  # Adjusted for more crack detection
                item_type = 'crack'
                # Check if it's an underlying crack (longer and thinner)
                if aspect_ratio > 8:
                    severity = 'Underlying'
                elif area > 4000:
                    severity = 'Severe'
                elif area > 800:
                    severity = 'Moderate'
                else:
                    severity = 'Minor'
            elif circularity > 0.6:  # Circular shapes are holes
                item_type = 'hole'
                if area > 4000:
                    severity = 'Severe'
                elif area > 800:
                    severity = 'Moderate'
                else:
                    severity = 'Minor'
            else:
                continue  # Skip objects that don't match crack or hole criteria

            items.append({
                'type': item_type,
                'box': [x, y, x + w, y + h],
                'severity': severity,
                'confidence': 0.95  # Simulated confidence
            })

        return items
    except Exception as e:
        print(f"Error in detection: {str(e)}")
        return []