In this article, let’s talk about histogram equalization and image thresholding. Histogram equalization is one of the tools we have for image pre-processing and it makes image thresholding or segmentation tasks easier.
The reason we need histogram equalization is that when we collect images that are washed out or images with low contrast, we can stretch the histogram to span the entire range.
Let’s look at an example, Image is collected using an electron microscope.
In the above image, we can see the separation but it is not clear as it could be. So let’s look at the histogram and use the equalization to stretch the histogram to threshold it.
import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2.imread("test.jpg", 0) equ = cv2.equalizeHist(img)
First I’ve read my image as grayscale and assigned it to the variable
img. To perform histogram equalization we can run
Let’s look at our test image’s histogram. And you can see it is skewed to the right side.
plt.hist(img.flat, bins=100, range=(0, 255))
Let’s look at the equalized image’s histogram. And you can see the histogram is stretched all the way to 255.
plt.hist(equ.flat, bins=100, range=(0, 255))
Below is the result of the histogram equalized image,
As you can see there is a lot of noise in the above image, because it considers the global contrast of the image, not just the local contrast. Therefore performing the global equalization might not work very well on your image, In those cases, we can use Adaptive Histogram Equalization or also know as CLAHE (Contrast Limiting Adaptive Histogram Equalization).
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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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Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…
You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.
class AnyClass: def __init__(): print("Init called on its own") obj = AnyClass()
The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.
The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.
Init called on its own
Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,
class AnyClass: def __init__(self, var): self.some_var = var def __add__(self, other_obj): print("Calling the add method") return self.some_var + other_obj.some_var obj1 = AnyClass(5) obj2 = AnyClass(6) obj1 + obj2
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