import cv2
import numpy as np
from typing import Dict, Tuple


def analyze_defect(contour: np.ndarray, image_shape: Tuple[int, int, int]) -> Dict:
    """
    Analyze geometric properties of a defect contour.

    Args:
        contour: Contour of detected defect
        image_shape: Shape of the image (H, W, C)

    Returns:
        Dictionary containing geometric features
    """

    if contour is None or len(contour) == 0:
        return {
            "area_pixels": 0.0,
            "length_pixels": 0.0,
            "width_pixels": 0.0,
            "area_ratio": 0.0,
            "angle": 0.0
        }

    # Area
    area = float(cv2.contourArea(contour))

    # Rotated bounding box (better than axis-aligned)
    rect = cv2.minAreaRect(contour)
    (cx, cy), (w, h), angle = rect

    length = float(max(w, h))
    width = float(min(w, h))

    # Image area
    height, width_img = image_shape[:2]
    image_area = height * width_img

    area_ratio = (area / image_area) if image_area > 0 else 0.0

    return {
        "area_pixels": area,
        "length_pixels": length,
        "width_pixels": width,
        "area_ratio": area_ratio,
        "angle": float(angle)
    }