"""尺度校准：像素 → 厘米（虹膜直径法，眼宽降级）。

人类虹膜直径高度稳定（成人平均 11.7mm），作为天然标尺把像素距离换算成厘米。
虹膜点（索引 469/471、474/476）需 refine_landmarks=True 才输出；缺失时降级用
眼宽（外→内眼角，均值约 2.85cm）。详见技术方案 §3。
"""
from face_analysis.face_mesh_landmarks import (
    IRIS_LEFT_LEFT, IRIS_LEFT_RIGHT, IRIS_RIGHT_LEFT, IRIS_RIGHT_RIGHT,
    LEFT_EYE_OUTER, LEFT_EYE_INNER, RIGHT_EYE_INNER, RIGHT_EYE_OUTER,
)

AVG_IRIS_DIAMETER_CM = 1.17   # 虹膜平均直径 11.7mm
AVG_EYE_WIDTH_CM = 2.85       # 眼裂平均宽度约 28.5mm（降级标尺）


def _lm_list(landmarks):
    """兼容 NormalizedLandmarkList（有 .landmark）与裸 list 两种入参。"""
    return landmarks.landmark if hasattr(landmarks, "landmark") else landmarks


def normalized_to_pixel(landmark, image_width, image_height):
    """归一化坐标 → 像素坐标。"""
    return landmark.x * image_width, landmark.y * image_height


def pixel_distance(p1, p2):
    """两点像素欧氏距离。"""
    return ((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2) ** 0.5


def _iris_diameter_px(lm, w, h):
    """左右虹膜直径像素均值；任一边缘点缺失/为 0 返回 None。"""
    try:
        ll = normalized_to_pixel(lm[IRIS_LEFT_LEFT], w, h)
        lr = normalized_to_pixel(lm[IRIS_LEFT_RIGHT], w, h)
        rl = normalized_to_pixel(lm[IRIS_RIGHT_LEFT], w, h)
        rr = normalized_to_pixel(lm[IRIS_RIGHT_RIGHT], w, h)
    except (IndexError, KeyError):
        return None
    left_d = pixel_distance(ll, lr)
    right_d = pixel_distance(rl, rr)
    if left_d <= 0 or right_d <= 0:
        return None
    return (left_d + right_d) / 2


def _eye_width_px(lm, w, h):
    """左右眼宽（外→内眼角）像素均值，作为虹膜降级标尺。"""
    l = pixel_distance(normalized_to_pixel(lm[LEFT_EYE_OUTER], w, h),
                       normalized_to_pixel(lm[LEFT_EYE_INNER], w, h))
    r = pixel_distance(normalized_to_pixel(lm[RIGHT_EYE_OUTER], w, h),
                       normalized_to_pixel(lm[RIGHT_EYE_INNER], w, h))
    return (l + r) / 2


def estimate_scale_factor(landmarks, image_width, image_height):
    """估算 px_per_cm（每厘米对应像素数）。

    优先用虹膜直径法；虹膜点不可用时降级用眼宽。返回正浮点数。
    """
    lm = _lm_list(landmarks)
    iris_px = _iris_diameter_px(lm, image_width, image_height)
    if iris_px is not None:
        return iris_px / AVG_IRIS_DIAMETER_CM
    # 降级：眼宽法
    eye_px = _eye_width_px(lm, image_width, image_height)
    return eye_px / AVG_EYE_WIDTH_CM


if __name__ == "__main__":
    import sys
    import cv2
    from face_analysis.detector import detector

    path = sys.argv[1] if len(sys.argv) > 1 else "tests/fixtures/frontal.jpg"
    img = cv2.imread(path)
    if img is None:
        print(f"无法读取图片: {path}")
        sys.exit(1)
    h, w = img.shape[:2]
    lms = detector.detect(img)
    if lms is None:
        print("未检出人脸")
        sys.exit(1)
    print(f"px_per_cm: {estimate_scale_factor(lms, w, h):.4f}")