# -*- coding: utf-8 -*-
# @Time    : 2024/2/19 9:54
# @Author  : len
# @File    : correct_qr.py
# @Software: PyCharm 
# @Comment :

import cv2
import numpy as np
import scipy.spatial.distance as dist

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

    # 使用goodFeaturesToTrack来检测角点
    corners = cv2.goodFeaturesToTrack(gray, maxCorners=4, qualityLevel=0.01, minDistance=10)

    # 如果检测到角点
    if corners is not None and len(corners) >= 4:
        # 对角点数组进行整形
        corners = np.intp(corners)

        # 对角点进行排序
        rect = order_points(corners.reshape(4, 2))

        # 计算变换后图像的宽和高
        width = max(int(dist.euclidean(rect[2], rect[3])), int(dist.euclidean(rect[1], rect[0])))
        height = max(int(dist.euclidean(rect[1], rect[2])), int(dist.euclidean(rect[0], rect[3])))

        # 构造目标点，用于将图像映射到鸟瞰图
        dst = np.array([[0, 0], [width - 1, 0], [width - 1, height - 1], [0, height - 1]], dtype="float32")

        # 计算透视变换矩阵并应用
        M = cv2.getPerspectiveTransform(rect, dst)
        warp = cv2.warpPerspective(image_source, M, (width, height))

        # 使用QRCodeDetector来检测和解码二维码
        detector = cv2.QRCodeDetector()
        data, vertices_array, binary_qr_code = detector.detectAndDecode(warp)

        # 如果检测到二维码，则返回解码数据
        if vertices_array is not None:
            return data, warp
        else:
            print("未检测到二维码。")
            return None
    else:
        # 如果未检测到足够的角点，则打印错误信息
        print("未检测到足够的角点。")
        return None

# 用于排序角点的函数
def order_points(pts):
    # 初始化排序后的点
    rect = np.zeros((4, 2), dtype="float32")

    # 根据点的坐标总和来进行排序
    s = pts.sum(axis=1)
    rect[0] = pts[np.argmin(s)]
    rect[2] = pts[np.argmax(s)]

    # 计算点的差值，用于找到其余两个点
    diff = np.diff(pts, axis=1)
    rect[1] = pts[np.argmin(diff)]
    rect[3] = pts[np.argmax(diff)]

    # 返回排序后的点
    return rect

# 运行校正函数
# 请确保传入正确的图像路径
result = correct_qr_code_skew("./data/img.png")
if result:
    decoded_data, corrected_image = result
    print("解码的数据:", decoded_data)