import cv2
import numpy as np
from PIL import Image
import os
import sys


def detect_captcha_left_edge(image_path_or_array, output_path=None):
    """
    识别滑块验证码中橙色缺口覆盖层的最左边X坐标，并生成绿线标记图。
    支持传入图片路径(str)或numpy.ndarray(BGR/RGB)。
    """
    if isinstance(image_path_or_array, str):
        img = Image.open(image_path_or_array)
        img_np = np.array(img)
    else:
        img_np = image_path_or_array.copy()
        # OpenCV 截图通常是 BGR，转成 RGB
        if img_np.shape[2] == 3:
            img_np = cv2.cvtColor(img_np, cv2.COLOR_BGR2RGB)

    h, w = img_np.shape[:2]

    # 转换为HSV颜色空间
    hsv = cv2.cvtColor(img_np, cv2.COLOR_RGB2HSV)

    # 检测 peach/orange 覆盖层
    # 色调: 10-35 (橙色/桃色), 饱和度: 40-255, 亮度: 140-255
    lower = np.array([10, 40, 140])
    upper = np.array([35, 255, 255])
    mask = cv2.inRange(hsv, lower, upper)

    # 形态学操作去噪
    kernel = np.ones((5, 5), np.uint8)
    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)

    # 查找轮廓
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    if not contours:
        raise ValueError("未检测到橙色区域")

    # 筛选候选区域：
    # 1. 轮廓中心位于验证码图片区域内（y + bh/2 在 0.4h ~ 0.65h 之间）
    # 2. 面积足够大
    # 3. y 范围足够长（bh > 0.2h），排除滑块按钮等短区域
    candidates = []
    for cnt in contours:
        x, y, bw, bh = cv2.boundingRect(cnt)
        area = bw * bh
        if area < 5000:
            continue
        center_y = y + bh / 2
        if center_y < h * 0.4 or center_y > h * 0.65:
            continue
        if bh < h * 0.2:
            continue
        candidates.append((cnt, x, y, bw, bh, area, bh))

    if not candidates:
        raise ValueError("未检测到拼图覆盖层")

    # 选择 y 范围最长的候选
    best = max(candidates, key=lambda c: c[6])
    _, x, y, bw, bh, area, bh_max = best

    # 左边缘 x 坐标
    left_x = x

    # 在原图上画绿线
    canvas = img_np.copy()
    cv2.line(canvas, (left_x, 0), (left_x, h), (0, 255, 0), 2)

    # 保存绿线标记图
    if output_path is None:
        base, ext = os.path.splitext(image_path_or_array if isinstance(image_path_or_array, str) else "")
        output_path = f"{base}_green.png"

    cv2.imwrite(output_path, cv2.cvtColor(canvas, cv2.COLOR_RGB2BGR))

    return left_x, output_path


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("用法: python detect_captcha_edge.py <图片路径> [输出路径]")
        sys.exit(1)

    image_path = sys.argv[1]
    output_path = sys.argv[2] if len(sys.argv) > 2 else None

    left_x, out = detect_captcha_left_edge(image_path, output_path)
    print(f"拼图最左边X坐标: {left_x}")
    print(f"绿线标记图: {out}")