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from PyQt5 import QtGui
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from PyQt5.QtWidgets import *
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import cv2
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import numpy as np
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def init(self):
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self.unit4_img = np.ndarray(())
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self.unit4_robertsimg = np.ndarray(())
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self.unit4_prewittimg = np.ndarray(())
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self.unit4_logimg = np.ndarray(())
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self.unit4_sobelimg = np.ndarray(())
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self.unit4_laplacianimg = np.ndarray(())
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self.unit4_loughimg = np.ndarray(())
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self.unit4_cannyimg = np.ndarray(())
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self.unit4_img_channel = 1
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self.unit4_robertsimg_channel = 1
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self.unit4_prewittimg_channel = 1
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self.unit4_logimg_channel = 1
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self.unit4_sobelimg_channel = 1
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self.unit4_laplacianimg_channel = 1
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self.unit4_loughimg_channel = 1
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self.unit4_cannyimg_channel = 1
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def img_load(self):
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fileName, tmp = QFileDialog.getOpenFileName(self, '打开图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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init(self)
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self.unit4_img = cv2.imread(fileName, -1)
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if self.unit4_img.size <= 1:
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return
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if len(self.unit4_img.shape) == 3:
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self.unit4_img_channel = 3
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if self.unit4_img.shape[2] == 4:
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self.unit4_img = cv2.cvtColor(self.unit4_img, cv2.COLOR_BGRA2BGR)
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print(self.unit4_img.shape)
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unit4_img_refresh(self)
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def unit4_img_refresh(self):
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array = \
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[self.unit4_img,
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self.unit4_robertsimg,
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self.unit4_prewittimg,
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self.unit4_logimg,
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self.unit4_sobelimg,
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self.unit4_laplacianimg,
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self.unit4_loughimg,
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self.unit4_cannyimg]
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array2 = [self.ui.label_53,
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self.ui.label_43,
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self.ui.label_30,
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self.ui.label_49,
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self.ui.label_58,
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self.ui.label_32,
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self.ui.label_34,
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self.ui.label_50]
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channel = [self.unit4_img_channel,
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self.unit4_robertsimg_channel,
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self.unit4_prewittimg_channel,
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self.unit4_logimg_channel,
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self.unit4_sobelimg_channel,
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self.unit4_laplacianimg_channel,
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self.unit4_loughimg_channel,
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self.unit4_cannyimg_channel]
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height = 240
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weight = 240
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for index in range(len(array)):
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M = np.float32([[1, 0, 0], [0, 1, 0]])
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if array[index].size <= 1:
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array2[index].setPixmap(QtGui.QPixmap(''))
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continue
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print(array[index].shape)
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index_h = array[index].shape[0]
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index_w = array[index].shape[1]
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if index_h / index_w == height / weight:
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img = array[index].tobytes()
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if channel[index] == 1:
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image = QtGui.QImage(img, index_w, index_h, index_w * channel[index], QtGui.QImage.Format_Grayscale8)
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pix = QtGui.QPixmap.fromImage(image)
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scale_pix = pix.scaled(weight, height)
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array2[index].setPixmap(scale_pix)
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continue
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elif channel[index] == 3:
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image = QtGui.QImage(img, index_w, index_h, index_w * channel[index], QtGui.QImage.Format_BGR888)
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pix = QtGui.QPixmap.fromImage(image)
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scale_pix = pix.scaled(weight, height)
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array2[index].setPixmap(scale_pix)
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continue
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elif index_h / index_w > height / weight:
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h_ = index_h
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w_ = int(index_h * weight / height+ 0.5)
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M[0, 2] += (w_ - index_w) / 2
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M[1, 2] += (h_ - index_h) / 2
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else:
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h_ = int(index_w * height / weight + 0.5)
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w_ = index_w
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M[0, 2] += (w_ - index_w) / 2
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M[1, 2] += (h_ - index_h) / 2
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img = cv2.warpAffine(array[index], M, (w_, h_))
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data = img.tobytes()
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if channel[index] == 1:
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image = QtGui.QImage(data, w_, h_, w_ * channel[index], QtGui.QImage.Format_Grayscale8)
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pix = QtGui.QPixmap.fromImage(image)
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scale_pix = pix.scaled(weight, height)
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array2[index].setPixmap(scale_pix)
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continue
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else:
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image = QtGui.QImage(data, w_, h_, w_ * channel[index], QtGui.QImage.Format_BGR888)
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pix = QtGui.QPixmap.fromImage(image)
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scale_pix = pix.scaled(weight, height)
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array2[index].setPixmap(scale_pix)
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continue
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return
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def img_clear(self):
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if self.unit4_img.size > 1:
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init(self)
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unit4_img_refresh(self)
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '无需清空', '没有图片')
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msg_box.exec_()
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def action(self):
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if self.unit4_img.size>1:
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#try:
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Roberts(self)
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print("Roberts over!")
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Prewitt(self)
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print("Prewitt over!")
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Log(self)
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print("Log over!")
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Sobel(self)
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print("Sobel over!")
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Laplacian(self)
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print("Laplacian over!")
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Lough(self)
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print("Lough over!")
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Canny(self)
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print("Canny over!")
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unit4_img_refresh(self)
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#except:
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#msg_box = QMessageBox(QMessageBox.Warning, '算子执行异常', '请更换图片')
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#msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '请选择图片')
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msg_box.exec_()
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def Roberts(self):
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img = self.unit4_img
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if(self.unit4_img_channel == 3):
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# Roberts算子
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kernelx = np.array([[-1,0],[0,1]],dtype=int)
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kernely = np.array([[0,-1],[1,0]],dtype=int)
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# 卷积操作
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x = cv2.filter2D(img,cv2.CV_16S,kernelx)
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y = cv2.filter2D(img,cv2.CV_16S,kernely)
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# 数据格式转换
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absX=cv2.convertScaleAbs(x)
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absY=cv2.convertScaleAbs(y)
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self.unit4_robertsimg = cv2.addWeighted(absX,0.5,absY,0.5,0)
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def Prewitt(self):
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grayImage = self.unit4_img
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if (self.unit4_img_channel == 3):
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grayImage = cv2.cvtColor(grayImage, cv2.COLOR_BGR2GRAY)
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kernelx = np.array([[1, 1, 1], [0, 0, 0], [-1, -1, -1]], dtype=int)
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kernely = np.array([[-1, 0, 1], [-1, 0, 1], [-1, 0, 1]], dtype=int)
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x = cv2.filter2D(grayImage, cv2.CV_16S, kernelx)
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y = cv2.filter2D(grayImage, cv2.CV_16S, kernely)
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absX = cv2.convertScaleAbs(x)
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absY = cv2.convertScaleAbs(y)
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self.unit4_prewittimg = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
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def Log(self):
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img = self.unit4_img
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if (self.unit4_img_channel == 3):
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 2边缘扩充处理图像并使用高斯滤波处理该图像
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image = cv2.copyMakeBorder(img, 2, 2, 2, 2, borderType=cv2.BORDER_REPLICATE)
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image = cv2.GaussianBlur(image, (3, 3), 0, 0)
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# 使用Numpy定义LoG算子
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m1 = np.array(
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[[0, 0, -1, 0, 0], [0, -1, -2, -1, 0], [-1, -2, 16, -2, -1], [0, -1, -2, -1, 0], [0, 0, -1, 0, 0]])
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# 卷积运算
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rows = image.shape[0]
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cols = image.shape[1]
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image1 = np.zeros(image.shape)
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for i in range(2, rows - 2):
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for j in range(2, cols - 2):
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image1[i, j] = np.sum((m1 * image[i - 2:i + 3, j - 2:j + 3]))
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self.unit4_logimg = cv2.convertScaleAbs(image1)
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def Sobel(self):
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grayImage = self.unit4_img
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if (self.unit4_img_channel == 3):
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grayImage = cv2.cvtColor(grayImage, cv2.COLOR_BGR2GRAY)
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# 求Sobel 算子
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x = cv2.Sobel(grayImage, cv2.CV_16S, 1, 0)
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y = cv2.Sobel(grayImage, cv2.CV_16S, 0, 1)
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# 数据格式转换
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absX = cv2.convertScaleAbs(x)
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absY = cv2.convertScaleAbs(y)
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self.unit4_sobelimg = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
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def Laplacian(self):
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grayImage = self.unit4_img
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if (self.unit4_img_channel == 3):
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grayImage = cv2.cvtColor(grayImage, cv2.COLOR_BGR2GRAY)
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# 高斯滤波
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grayImage = cv2.GaussianBlur(grayImage,ksize=(5,5),sigmaX=0,sigmaY=0)
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# 拉普拉斯算法
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dst = cv2.Laplacian(grayImage, cv2.CV_16S, ksize=3)
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# 数据格式转换
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self.unit4_laplacianimg = cv2.convertScaleAbs(dst)
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def Lough(self):
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img = self.unit4_img
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if (self.unit4_img_channel == 3):
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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img = cv2.GaussianBlur(img, (3, 3), 0)
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edges = cv2.Canny(img, 50, 150, apertureSize=3)
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lines = cv2.HoughLines(edges, 1, np.pi / 2, 118)
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result = img.copy()
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for i_line in lines:
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for line in i_line:
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rho = line[0]
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theta = line[1]
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if (theta < (np.pi / 4.)) or (theta > (3. * np.pi / 4.0)): # 垂直直线
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pt1 = (int(rho / np.cos(theta)), 0)
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pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
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cv2.line(result, pt1, pt2, (0, 0, 255))
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else:
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pt1 = (0, int(rho / np.sin(theta)))
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pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
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cv2.line(result, pt1, pt2, (0, 0, 255), 1)
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linesP = cv2.HoughLinesP(edges, 1, np.pi / 180, 80, 200, 15)
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result_P = img.copy()
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for i_P in linesP:
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for x1, y1, x2, y2 in i_P:
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cv2.line(result_P, (x1, y1), (x2, y2), (0, 255, 0), 3)
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self.unit4_loughimg = result_P
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def Canny(self):
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image = self.unit4_img
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if (self.unit4_img_channel == 3):
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image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# 高斯滤波
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image= cv2.GaussianBlur(image, (3, 3), 0)
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# 求x，y方向的Sobel算子
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gradx = cv2.Sobel(image, cv2.CV_16SC1, 1, 0)
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grady = cv2.Sobel(image, cv2.CV_16SC1, 0, 1)
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print("Yes")
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# 使用Canny函数处理图像，x,y分别是3求出来的梯度，低阈值50，高阈值150
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self.unit4_cannyimg = cv2.Canny(gradx, grady, 50, 150)
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def canny_save(self):
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if self.unit4_cannyimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_cannyimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def log_save(self):
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if self.unit4_logimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_logimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def lough_save(self):
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if self.unit4_loughimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_loughimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def laplacian_save(self):
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if self.unit4_laplacianimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_laplacianimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def sobel_save(self):
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if self.unit4_sobelimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_laplacianimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def prewitt_save(self):
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if self.unit4_prewittimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_prewittimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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else:
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msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
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msg_box.exec_()
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def roberts_save(self):
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if self.unit4_robertsimg.size > 1:
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fileName, tmp = QFileDialog.getSaveFileName(self, '保存图像', 'Image', '*.png *.jpg *.bmp *.jpeg')
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if fileName == '':
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return
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cv2.imwrite(fileName, self.unit4_robertsimg)
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msg_box = QMessageBox(QMessageBox.Information, '成功', '图像保存成功,保存路径为：' + fileName)
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msg_box.exec_()
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|
|
else:
|
|
|
msg_box = QMessageBox(QMessageBox.Warning, '提示', '没有生成图像')
|
|
|
msg_box.exec_()
|
