from PIL import Image, ImageOps
import cv2
import numpy as np

def add_yellow_border(image_path, output_path, border_size=2):
    """
    给指定的图像添加黄色外边框并保存。

    参数:
    image_path (str): 原始图像的路径。
    output_path (str): 带边框的图像保存路径。
    border_size (int): 边框的像素宽度，默认为2。
    """
    # 打开图像
    img = Image.open(image_path)

    # 计算边框颜色和大小
    # 灰色
    # border_color = (192, 192, 192)
    border_color = (255, 255, 0)
    border = (border_size, border_size, border_size, border_size)  # (左, 上, 右, 下)

    # 添加边框
    img_with_border = ImageOps.expand(img, border=border, fill=border_color)

    # 保存新图像
    img_with_border.save(output_path)
    print(f"Image saved with a yellow border to {output_path}")

def find_qr_code_border_and_save(image_path):
    # 读取图像
    img = cv2.imread(image_path)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 边缘检测
    edges = cv2.Canny(gray, 50, 150, apertureSize=3)

    # 霍夫变换检测直线
    lines = cv2.HoughLinesP(edges, 1, np.pi / 180, threshold=100, minLineLength=100, maxLineGap=10)
    print(lines)
    # 初始化最小和最大的x和y值
    min_x, max_x = img.shape[1], 0
    min_y, max_y = img.shape[0], 0

    if lines is not None:
        # 更新x和y的最小和最大值来找到边界框
        for line in lines:
            x1, y1, x2, y2 = line[0]
            min_x = min(min_x, x1, x2)
            max_x = max(max_x, x1, x2)
            min_y = min(min_y, y1, y2)
            max_y = max(max_y, y1, y2)

        # 截取二维码区域
        qr_code_region = img[min_y:max_y, min_x:max_x]

        # 保存截取的图片
        cv2.imwrite('qr_code_detected.png', qr_code_region)
        print("二维码区域已保存为 'qr_code_detected.png'")

    else:
        print("未检测到任何直线")

# 示例用法
# image_path = '20240506202950.png'  # 替换为你的图像路径 jkkkkkkkkkk
# output_path = '20240506202950_border.png'  # 替换为保存新图像的路径
# add_yellow_border(image_path, output_path,5)

find_qr_code_border_and_save('IMG_3565.png')