To convert PIL Image to Grayscale in Python, use the ImageOps.grayscale() method. PIL module provides ImageOps class, which provides various methods that can help us to modify the image.
To open the image in Python, PIL provides an Image class that has an open() image. So, we can open the image.
Pillow supports the variety of image file formats such as PNG, JPEG, PPM, GIF, TIFF, and BMP.
Pillow supports image editing operations like cropping, resizing, adding text to images, rotating, greyscaling.
The ImageOps.grayscale() function converts RGB image to Grayscale image. The complete pixel turns to grey, and no other color will be seen.
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
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Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.
In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.
Heres a solution
Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.
But How do we do it?
If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?
The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.
There’s a variety of hashing algorithms out there such as
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The work of a Data Analyst is not limited to work only on readily available data, rather sometimes the data need to be mined from the images also.
This story is all about different types of image feature extraction using Python. Additionally, here you will find a classic comparison of the speed of two image processing libraries — OpenCV and PIL
____ OpenCV is 1.4 Times faster than PIL ____
📌 Want to follow along? here is my Jupyter-Notebook.
📌 More resources are always mentioned with 💡
In my recent project, I need to process 10000+ images per day and extract the data from them. And only Python can help me with this batch processing. I usually do the below processes on image:
1. Extract the aspect ratio of the image.
2. Crop the image.
3. Change the image to grayscaled one.
4. Image Rotation.
However, my work doesn’t stop here. I do much more ad-hoc analysis.
In my project, a lot of information is also hidden in the image name. And the string manipulation methods discussed here are quite handy in such tasks.
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