"""接口3 马克笔检测测试：辅助函数(纯numpy) + 真实样本检测/拒识。"""
import cv2
import numpy as np
from conftest import fixture

from hairline.marker_detect import (
    detect_marker_hairline, path_to_curve_mask, _snap_anchor,
)
from hairline.service import get_landmarker, get_parser


def test_path_to_curve_mask():
    path = np.array([[10, 5], [10, 50], [10, 90]])     # 水平线 row=10
    m = path_to_curve_mask(path, 100, 100, thickness=3)
    assert m[10, 50] == 255
    assert m[90, 50] == 0


def test_snap_anchor_moves_to_peak():
    bh = np.zeros((100, 100), np.float32)
    bh[40, 30] = 99.0                                  # 峰值在 (40,30)
    r, c = _snap_anchor(bh, x=33, y=42, w=1000)        # 起点附近 → 应吸到峰值
    assert (r, c) == (40, 30)


def _ctx(path_img):
    img = cv2.imread(path_img)
    rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    lm = get_landmarker().detect(rgb)
    pm = get_parser().parse(rgb)
    return img, lm, pm


def test_detect_real_marked():
    img, lm, pm = _ctx(fixture("marked_hairline.jpg"))
    path = detect_marker_hairline(img, lm, pm)
    assert path is not None and len(path) > 50          # 检测到画线


def test_reject_clean_photo():
    img, lm, pm = _ctx(fixture("frontal.jpg"))
    assert detect_marker_hairline(img, lm, pm) is None  # 无画线 → 拒识