Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
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
Using the savefig method of the pyplot package, we can save the figure remotely by specifying the location of the figure.StepsTo use a different backend, set it using matplotlib.use('Agg') method.Plot the lines using plot() method.Using savefig() method, we can save the image remotely, just putting the directory.To show the figure, use plt.show().Exampleimport matplotlib matplotlib.use('Agg') from matplotlib import pyplot as plt plt.plot([1, 2, 3]) plt.savefig("remotely_fig.png")Output
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]
To plot multiple lines in a diagram, we can use the cycler that could help to set a new color from the given list of colors. (Here, ‘r’ => ‘red’, ‘g’ => ‘green’, ‘y’ => ‘yellow’, ‘b’ => ‘blue’).StepsUse a cycler to set the color for the group of lines. The color list consists of ‘r’ for red, ‘g’ for green, ‘b’ for blue, and ‘y’ for yellow.The cycler class helps to create a new Cycler object from a single positional argument, a pair of positional arguments, or the combination of keyword arguments.Plot the number of lines with different colors.Use ... Read More
In this program, we will up sample an image. Up sampling is increasing the spatial resolution while keeping the 2D representation of an image. It is typically used for zooming in on a small region of an image. We will use the pyrup() function in the openCV library to complete this task.Original ImageAlgorithmStep 1: Read the image. Step 2: Pass the image as a parameter to the pyrup() function. Step 3: Display the output.Example Codeimport cv2 image = cv2.imread('testimage.jpg') print("Size of image before pyrUp: ", image.shape) image = cv2.pyrUp(image) print("Size of image after pyrUp: ", image.shape) cv2.imshow('UpSample', image)OutputSize ... Read More
In this program, we will perform the Blackhat operation on an image using OpenCV. BlackHat transform is used to enhance dark objects of interest in a bright background. We will use the morphologyEx(image, cv2.MORPH_BLACKHAT, kernel) function.Original ImageAlgorithmStep 1: Import cv2. Step 2: Read the image. Step 3: Define the kernel size. Step 4: Pass the image and kernel to the cv2.morphologyex() function. Step 5: Display the output.Example Codeimport cv2 image = cv2.imread('image_test.jpg') filter_size = (5,5) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, filter_size) image = cv2.morphologyEx(image, cv2.MORPH_BLACKHAT, kernel) cv2.imshow('BlackHat', image)Output
In this program, we will perform the TopHat operation on images. TopHat operation is a morphological operation that is used to extract small elements and details from given images. TopHat is used to enhance bright objects in a dark background. We will use the morphologyEx(image, cv2.MORPH_TOPHAT, kernel) functionOriginal ImageAlgorithmStep 1: Import cv2. Step 2: Read the image. Step 3: Define the kernel size. Step 4: Pass the image and kernel to the cv2.morphologyex() function. Step 5: Display the output.Example Codeimport cv2 image = cv2.imread('tophat.jpg') filter_size = (5, 5) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, filter_size) image = cv2.morphologyEx(image, cv2.MORPH_TOPHAT, kernel) cv2.imshow('TopHat', image)OutputExplanationAs ... Read More
The following program code shows how you can plot a newline in matplotlib label with Tex.StepsSetup X-axis and Y-axis labels for the diagram with to plot a newline in the labels.Set the current .rcParams for axes facecolor; the group is axed.Use a cycler to set the color for the group of lines. The color list consists of ‘r’ for red, ‘g’ for green, ‘b’ for blue, and ‘y’ for yellow.The cycler class helps to create a new Cycler object from a single positional argument, a pair of positional arguments, or the combination of keyword arguments.Plot the number of lines ... Read More
In this program, we will dilate an image using the dilate function in the OpenCV library. Dilation adds pixels to the boundaries of objects in an image, i.e., it expands the image on all sides.Original ImageAlgorithmStep 1: Import cv2 and numpy. Step 2: Read the image using opencv.imread(). Step 3: Define the kernel using np.ones() function. Step 4: Pass the image and kernel to the dilate() function. Step 5: Display the imageExample Codeimport cv2 import numpy as np image = cv2.imread('testimage.jpg') kernel = np.ones((3, 3), np.uint8) image = cv2.dilate(image, kernel) cv2.imshow('Dilated Image', image)OutputExplanationAs you can see, the image ... Read More
In this program, we will perform the opening operation on image. Opening removes small objects from the foreground of an image, placing them in the background. This technique can also be used to find specific shapes in an image. Opening can be called erosion followed by dilation. The function we will use for this task is cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel).Original ImageAlgorithmStep 1: Import cv2 and numpy. Step 2: Read the image. Step 3: Define the kernel. Step 4: Pass the image and kernel to the cv2.morphologyex() function. Step 4: Display the output.Example Codeimport cv2 import numpy as np image = ... Read More