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