In this program, we will perform inverse zero thresholding on an image using openCV. Thresholding is a process in which the value of each pixel is changed in relation to a threshold value. The pixel is given a certain value if it is less than the threshold and some other value if it is greater than the threshold. In inverse zero thresholding, pixels having intensity value greater than the threshold value are set to 0.Original ImageAlgorithmStep 1: Import cv2. Step 2: Define the threshold and max_val. Step 3: Pass these parameters in the cv2.threshold value and specify the type of ... Read More

In this program, we will perform zero thresholding on an image using openCV. Thresholding is a process in which the value of each pixel is changed in relation to a threshold value. The pixel is given a certain value if it is less than the threshold and some other value if it is greater than the threshold. In zero thresholding, pixels having intensity value less than the threshold value are set to 0.Original ImageAlgorithmStep 1: Import cv2. Step 2: Define the threshold and max_val. Step 3: Pass these parameters in the cv2.threshold value and specify the type of thresholding you ... Read More

Just by using plt.ylabel(rotation='horizontal'), we can align a label according to our requirement.StepsPlot the lines using [0, 5] and [0, 5] lists.Set the y-label for Y-axis, using ylabel method by passing rotation='horizontal'.Set the x-label for X-axis, using xlabel method.To show the plot, use plt.show() method.Examplefrom matplotlib import pyplot as plt plt.plot([0, 5], [0, 5]) plt.ylabel("Y-axis ", rotation='horizontal') plt.xlabel("X-axis ") plt.show()Output

In this program, we will perform truncate thresholding on an image using openCV. Thresholding is a process in which the value of each pixel is changed in relation to a threshold value.The pixel is given a certain value if it is less than the threshold and some other value if it is greater than the threshold. In truncate thresholding, values greater than the threshold are reduced to the threshold value. Every other pixel remains the same.Original ImageAlgorithmStep 1: Import cv2. Step 2: Define threshold and max_val. Step 3: Pass these parameters in the cv2.threshold value and specify the type of ... Read More

In this program, we will perform inverse binary thresholding on an image using openCV. Thresholding is a process in which the value of each pixel is changed in relation to a threshold value.The pixel is given a certain value if it is less than the threshold and some other value if it is greater than the threshold. In inverse binary thresholding, if the value of the pixel is less than the threshold, it will be given a maximum value i.e. white. If it is greater than the threshold, it will be assigned 0, i.e., black.Original ImageAlgorithmStep 1: Import cv2. Step ... Read More

Using the figsize attribute of figure(), we can change the figure size. To change the format of a figure, we can use the savefig method.StepsStore the figure size in the variable.Create a new figure, or activate an existing figure, with given figure size.Plot the line using x.Set the image title with its size.Save the figure using savefig() method.Examplefrom matplotlib import pyplot as plt figure_size = (10, 10) plt.figure(figsize=figure_size) x = [1, 2, 3] plt.plot(x, x) plt.title("Figure dimension is: {}".format(figure_size)) plt.savefig("imgae.png", format="png")Output

Just using the savefig method of the pyplot package and mentioning the file format, we can save the output as a SVG format.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Create xpoints and ypoints using np.array(0, 5).Plot lines using xpoints and ypoints.Set the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.To save the file in SVG format, use savefig() method where image name is myImagePDF.svg, format="svg".To show the image, use plt.show() method.Exampleimport matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() xpoints = np.array([0, 5]) ypoints = np.array([0, ... Read More

In this program, we will perform binary thresholding on an image using openCV.Thresholding is a process in which the value of each pixel is changed in relation to a threshold value. The pixel is given a certain value if it is less than the threshold and some other value if it is greater than the threshold. In binary thresholding, if the value of the pixel is less than the threshold, it will be given a 0 value, i.e., black. If it is greater than the threshold, it will be assigned 255, i.e., white.Original ImageAlgorithmStep 1: Import cv2. Step 2: Define ... Read More

In this program, we will down sample an image. Downsampling is decreasing the spatial resolution while keeping the 2D representation of an image. It is typically used for zooming out of an image. We will use the pyrdown() function in the openCV library to complete this task.Original ImageAlgorithmStep 1: Fead the image. Step 2: Pass the image as a parameter to the pyrdown() function. Step 3: Display the output.Example Codeimport cv2 image = cv2.imread('testimage.jpg') print("Size of image before pyrDown: ", image.shape) image = cv2.pyrDown(image) print("Size of image after pyrDown: ", image.shape) cv2.imshow('DownSample', image)OutputSize of image before pyrDown:  (350, ... Read More

In this program, we will calculate the mean of all the pixels in each channel using the Pillow library. There are a total three channels in an image and therefore, we will get a list of three values.Original ImageAlgorithmStep 1: Import the Image and ImageStat libraries. Step 2: Open the image. Step 3: Pass the image to the stat function of the imagestat class. Step 4: Print the mean of the pixels.Example Codefrom PIL import Image, ImageStat im = Image.open('image_test.jpg') stat = ImageStat.Stat(im) print(stat.mean)Output[76.00257724463832, 69.6674300254453, 64.38017448200654]