Image Filter with OpenCV and PyQt

In this tutorial, you will learn how to use OpenCV module to filter image using kernels and to display the resulting image with PyQt. 

Follow these steps below:

1. Open Qt Designer. Put four Label widgets dan four Push Button widgets onto form.
2. Set objectName property of the four Label widgets by name labelImage, labelIdentity, labelKernel3x3, and labelKernel5x5.
3. Set objectName property of the four Push Button widgets by name pbOriginalImage, pbIdentityImage, pbKernel3x3, and pbKernel5x5.
4. Name form as image_filter.ui.
5. Form now looks as follows:





6. Write this script and name it as image_filter.py:



import sys
import cv2
import numpy as np
from PyQt5.QtWidgets import QApplication, QWidget, QLabel
from PyQt5.QtWidgets import QDialog, QFileDialog
from PyQt5.QtGui import QIcon, QPixmap, QImage
from PyQt5.uic import loadUi

fname = ""
    
class FormImageFilter(QDialog):

    def __init__(self):
        QDialog.__init__(self)
        loadUi("image_filter.ui",self)

        self.setWindowTitle("Image Filter")
        self.pbOriginalImage.clicked.connect(self.display_image)
        self.pbIdentityImage.clicked.connect(self.image_identity)
        self.pbKernel3x3.clicked.connect(self.kernel3x3)
        self.pbKernel5x5.clicked.connect(self.kernel5x5)

    def display_image(self):
        global fname
        fname = QFileDialog.getOpenFileName(self, 'Open file', 
           'd:\\',"Image Files (*.jpg *.gif *.bmp *.png *.tiff)")
        pixmap = QPixmap(fname[0])
        self.labelImage.setPixmap(pixmap)
        self.labelImage.setScaledContents(True);

    def image_identity(self, b=None):
        read_img = cv2.imread(fname[0], cv2.IMREAD_COLOR)
        kernel_identity = np.array([[0,0,0], [0,1,0], [0,0,0]])
        
        # To filter image using identity kernel
        output = cv2.filter2D(read_img, -1, kernel_identity)
        
        # To convert back from BGR to RGB space color
        cv2.cvtColor(output, cv2.COLOR_BGR2RGB, output)
        
        # To display image in label widget
        height, width, channel = output.shape
        bytesPerLine = 3 * width
        qImg = QImage(output.data, width, height, bytesPerLine, QImage.Format_RGB888)
        pixmap = QPixmap.fromImage(qImg)
        self.labelIdentity.setPixmap(pixmap)
        self.labelIdentity.setScaledContents(True);

    def kernel3x3(self):
        read_img = cv2.imread(fname[0], cv2.IMREAD_COLOR)
        
        # To filter image using kernel 3x3
        kernel_3x3 = np.ones((3,3), np.float32) / 9.0
        output = cv2.filter2D(read_img, -1, kernel_3x3)
        
        # To convert back from BGR to RGB space color
        cv2.cvtColor(output, cv2.COLOR_BGR2RGB, output)
        
        # To display image in label widget
        height, width, channel = output.shape
        bytesPerLine = 3 * width
        qImg = QImage(output.data, width, height, bytesPerLine, QImage.Format_RGB888)
        pixmap = QPixmap.fromImage(qImg)
        self.labelKernel3x3.setPixmap(pixmap)
        self.labelKernel3x3.setScaledContents(True);

    def kernel5x5(self):
        read_img = cv2.imread(fname[0], cv2.IMREAD_COLOR)
        
        # To filter image using kernel 5x5
        kernel_5x5 = np.ones((5,5), np.float32) / 25.0
        output = cv2.filter2D(read_img, -1, kernel_5x5)
        
        # To convert back from BGR to RGB space color
        cv2.cvtColor(output, cv2.COLOR_BGR2RGB, output)
        
        # To display image in label widget
        height, width, channel = output.shape
        bytesPerLine = 3 * width
        qImg = QImage(output.data, width, height, bytesPerLine, QImage.Format_RGB888)
        pixmap = QPixmap.fromImage(qImg)
        self.labelKernel5x5.setPixmap(pixmap)
        self.labelKernel5x5.setScaledContents(True);
        
if __name__=="__main__":
    app = QApplication(sys.argv)    
    w = FormImageFilter()
    w.show()
    sys.exit(app.exec_())



7. Run the program and you now can see the resulting images (identity image and two kernel images):