Python OpenCV實現任意角度二維條碼矯正

"""
author: puhaiyang
blog: https://blog.csdn.net/puhaiyang
github: https://github.com/puhaiyang
"""
import math
import cv2
from pyzbar import pyzbar
import imutils


def azimuthangle(x1, y1, x2, y2):
    """ 已知兩點座標計算角度 -
    :param x1: 原點橫座標值
    :param y1: 原點縱座標值
    :param x2: 目標點橫座標值
    :param y2: 目標縱座標值
    """
    dx = x2 - x1
    dy = y2 - y1
    # 求斜率
    k = dy / dx
    # 結果是弧度值
    angle = math.atan(k)
    # 弧度值轉為角度
    return angle * 180 / math.pi


def get_angle(qr_item):
    """
    獲取出進行矯正所需要的角度
    """
    # 將座標從下到上，從左到右進行排序
    locs = {qr_item.polygon[0], qr_item.polygon[1], qr_item.polygon[2], qr_item.polygon[3]}
    locs = sorted(locs, key=lambda x: x.y * 100000 + x.x * 1000)
    return azimuthangle(locs[2].x, locs[2].y, locs[3].x, locs[3].y)


def to_up_angle(qr_item):
    """
    獲取出使二維條碼朝上的角度
    """
    if qr_item.orientation == 'UP':
        angle_ext = 0
    elif qr_item.orientation == 'RIGHT':
        angle_ext = 270
    elif qr_item.orientation == 'DOWN':
        angle_ext = 180
    else:
        angle_ext = 90
    return angle_ext


def resize_img(ori_img):
    """
    圖片壓縮
    """
    height = ori_img.shape[0]
    width = ori_img.shape[1]
    # 執行壓縮,按照500的寬度為標準
    if width > 500:
        scale_percent = int(500 / width * 100)
        s_width = int(width * scale_percent / 100)
        s_height = int(height * scale_percent / 100)
        # 新的寬度和高度
        dim = (s_width, s_height)
        return cv2.resize(ori_img, dim, interpolation=cv2.INTER_AREA)
    else:
        return ori_img


def adjust_rotae_angle(img):
    angle = 0
    # 對圖片進行壓縮
    img = resize_img(img)
    # symbol為64代表二維條碼
    qr_result = pyzbar.decode(img, symbols=[64])
    if len(qr_result) == 1:
        # 識別到了一個二維條碼,將二維條碼朝上旋轉
        first_adjust_angle = to_up_angle(qr_result[0])
        # 進行旋轉
        img_rotae_to_up = imutils.rotate_bound(img, first_adjust_angle)
        # 再次識別
        qr_result2 = pyzbar.decode(img_rotae_to_up, symbols=[64])
        if len(qr_result2) == 1:
            last_adjust_angle = -get_angle(qr_result2[0])
            angle = first_adjust_angle + last_adjust_angle
            print("first angle:%d last angle:%d angle:%d" % (first_adjust_angle, last_adjust_angle, angle))
        else:
            print('last 未識別到二維條碼')
    else:
        print('first 未識別到二維條碼')
    return angle


if __name__ == '__main__':
    # 載入圖片
    img = cv2.imread('123.jpg')
    adjust_angle = adjust_rotae_angle(img.copy())
    if adjust_angle != 0:
        img_rotae = imutils.rotate_bound(img, adjust_angle)
        cv2.imwrite('img_rotae.jpg', img_rotae)