59 lines
1.5 KiB
Python
59 lines
1.5 KiB
Python
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# -*- coding: utf-8 -*-
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# @Time : 2024/3/12 21:03
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# @Author : len
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# @File : QR矫正.py
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# @Software: PyCharm
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# @Comment :
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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# 读取原图
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srcImagePath = r"./android_img/test/img_1.png"
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srcImage = cv2.imread(srcImagePath)
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srcImage = cv2.resize(srcImage, (500, 500)) # 调整图像大小
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# 调整亮度和对比度
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alpha = 1.8 # 对比度因子
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beta = -30 # 亮度因子
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contrastImage = cv2.convertScaleAbs(srcImage, alpha=alpha, beta=beta)
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# 转换为灰度图
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grayImage = cv2.cvtColor(contrastImage, cv2.COLOR_BGR2GRAY)
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# 双边滤波
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filterImage = cv2.bilateralFilter(grayImage, 13, 26, 6)
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# 二值化
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_, binaryImage = cv2.threshold(filterImage, 210, 255, cv2.THRESH_BINARY_INV)
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# 腐蚀
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erodeImage = cv2.erode(binaryImage, None, iterations=2)
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# 膨胀
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dilateImage = cv2.dilate(erodeImage, None, iterations=19)
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# Canny边缘检测
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cannyImage = cv2.Canny(dilateImage, 10, 100)
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# Hough变换检测直线
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lines = cv2.HoughLines(cannyImage, 5, np.pi/180, 100)
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# 直线简化逻辑（这里简化为展示所有检测到的直线）
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if lines is not None:
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for line in lines:
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rho, theta = line[0]
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a = np.cos(theta)
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b = np.sin(theta)
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x0 = a * rho
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y0 = b * rho
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x1 = int(x0 + 1000 * (-b))
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y1 = int(y0 + 1000 * (a))
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x2 = int(x0 - 1000 * (-b))
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y2 = int(y0 - 1000 * (a))
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cv2.line(srcImage, (x1, y1), (x2, y2), (0, 0, 255), 2)
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plt.imshow(cv2.cvtColor(srcImage, cv2.COLOR_BGR2RGB))
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plt.title('Detected Lines')
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plt.show()
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