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Articles by Prasad Naik
35 articles
Write a Python program to remove a certain length substring from a given string
We need to write a Python program which will remove a certain substring from a given stringAlgorithmStep 1: Define a string. Step 2: Use the replace function to remove the substring from the given string.Example Codeoriginal_string = "C++ is a object oriented programming language"modified_string = original_string.replace("object oriented", "")print(modified_string)OutputC++ is a programming languageExplanationThe in-build Python replace() function takes the following parameters:Oldstring: The string which you want to removeNewstring: The new string you want to replace in place of the oldstringCount: Optional. Number of times you want to replace the oldstring with the newstring
Read MorePython program to display various datetime formats
The datetime module supplies classes for manipulating dates and time. We will display different formats like day of the week, week number, day of the year, etc.AlgorithmStep 1: Import datetime. Step 2: Print day of the week. Step 3: Print week number. Step 4: Print day of the year.Example Codeimport datetime print("Day of the week: ", datetime.date.today().strftime("%A")) print("Week number: ", datetime.date.today().strftime("%W")) print("Day of the year: ", datetime.date.today().strftime("%j"))OutputDay of the week: Sunday Week number: 06 Day of the year: 045ExplanationThe arguments of the strftime() function are explained below:%A: Weekday's full name (Example: 'Monday')%W: Week number of the year with sunday ...
Read MoreApplying Gaussian Blur to an image using the Pillow library
In this program, we will blur an image using a Gaussian filter. The ImageFilter class in the pillow library contains a function called GaussianBlur() which helps to apply the gaussian blur filter. It takes only one parameter that is blur radius.Original ImageAlgorithmStep 1: Import Image and ImageFilter from Pillow. Step 2: Open the image. Step 3: Call the gaussianblur() method and specify the radius Step 4: Display the output.Example Codefrom PIL import Image, ImageFilter im = Image.open('image_test.jpg') im1 = im.filter(ImageFilter.GaussianBlur(radius = 9)) im1.show()Output
Read MoreApplying MaxFilter on an image using Pillow library
In this program, we will apply a minimum filter on an image using the pillow library. In maximum filtering, the value of each pixel in a selected window of the image is replaced by the maximum pixel of that window. The filter function is used to apply different filters using the pillow library.Original ImageAlgorithmStep 1: Import Image from Pillow. Step 2: Open the image. Step 3: Call the filter function and specify maxfilter. Step 4: Display the output.Example Codefrom PIL import Image, ImageFilter im = Image.open('testimage.jpg') im1 = im.filter(ImageFilter.MaxFilter(size = 7)) im1.show()Output
Read MoreLoading and displaying an image using the Pillow library
In this program, we will read or load an image using the pillow library. The pillow library consists of a method called Image.open(). This function takes the file path or the name of the file as a string. To display the image, we use another function show(). It does not require any parameter.Example Codefrom PIL import Image im = Image.open('testimage.jpg') im.show()Output
Read MoreDownsampling an image using OpenCV
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 MoreCalculating the mean of all pixels for each band in an image using the Pillow library
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]
Read MorePerforming white TopHat operation on images using OpenCV
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 MoreDilating images using the OpenCV function dilate()
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 MorePerforming an opening operation on an image using OpenCV
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 = ...
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