Python Tutorial

Introduction Python Features Python Applications Python System requirements Python Installation Python Examples Python Basics Python Indentation Python Variables Python Data Types Python IDE Python Keywords Python Operators Python Comments Python Pass Statement

Python Conditional Statements

Python if Statement Python elif Statement Python If-else statement Python Switch Case

Python Loops

Python for loop Python while loop Python Break Statement Python Continue Statement Python Goto Statement

Python Arrays

Python Array Python Matrix

Python Strings

Python Strings Python Regex

Python Built-in Data Structure

Python Lists Python Tuples Python Lists vs Tuples Python Dictionary Python Sets

Python Functions

Python Function Python min() function Python max() function Python User-define Functions Python Built-in Functions Python Recursion Anonymous/Lambda Function in Python apply() function in python Python lambda() Function

Python File Handling

Python File Handling Python Read CSV Python Write CSV Python Read Excel Python Write Excel Python Read Text File Python Write Text File Read JSON File in Python

Python Exception Handling

Python Exception Handling Python Errors and exceptions Python Assert

Python OOPs Concept

OOPs Concepts in Python Classes & Objects in Python Inheritance in Python Polymorphism in Python Python Encapsulation Python Constructor Python Super function Python Static Method Static Variables in Python Abstraction in Python

Python Iterators

Iterators in Python Yield Statement In Python Python Yield vs Return

Python Generators

Python Generator

Python Decorators

Python Decorator

Python Functions and Methods

Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods

Python Modules

Python Modules Python Datetime Module Python Math Module Python Import Module Python Time ModulePython Random Module Python Calendar Module CSV Module in Python Python Subprocess Module

Python MySQL

Python MySQL Python MySQL Client Update Operation Delete Operation Database Connection Creating new Database using Python MySQL Creating Tables Performing Transactions

Python MongoDB

Python MongoDB

Python SQLite

Python SQLite

Python Data Structure Implementation

Python Stack Python Queue Python Linked List Python Hash Table Python Graph

Python Advance Topics

Speech Recognition in Python Face Recognition in Python Python Linear regression Python Rest API Python Command Line Arguments Python JSON Python Subprocess Python Virtual Environment Type Casting in Python Python Collections Python Attributes Python Commands Python Data Visualization Python Debugger Python DefaultDict Python Enumerate

Python 2

What is Python 2

Python 3

Anaconda in Python 3 Anaconda python 3 installation for windows 10 List Comprehension in Python3

How to

How to Parse JSON in Python How to Pass a list as an Argument in Python How to Install Numpy in PyCharm How to set up a proxy using selenium in python How to create a login page in python How to make API calls in Python How to run Python code from the command prompt How to read data from com port in python How to Read html page in python How to Substring a String in Python How to Iterate through a Dictionary in Python How to convert integer to float in Python How to reverse a string in Python How to take input in Python How to install Python in Windows How to install Python in Ubuntu How to install PIP in Python How to call a function in Python How to download Python How to comment multiple lines in Python How to create a file in Python How to create a list in Python How to declare array in Python How to clear screen in Python How to convert string to list in Python How to take multiple inputs in Python How to write a program in Python How to compare two strings in Python How to create a dictionary in Python How to create an array in Python How to update Python How to compare two lists in Python How to concatenate two strings in Python How to print pattern in Python How to check data type in python How to slice a list in python How to implement classifiers in Python How To Print Colored Text in Python How to open a file in python How to Open a file in python with Path How to run a Python file in CMD How to change the names of Columns in Python How to Concat two Dataframes in Python How to Iterate a List in Python How to learn python Online How to Make an App with Python How to develop a game in python How to print in same line in python How to create a class in python How to find square root in python How to import numy in python How to import pandas in python How to uninstall python How to upgrade PIP in python How to append a string in python How to comment out a block of code in Python How to change a value of a tuple in Python How to append an Array in Python How to Configure Python Interpreter in Eclipse How to plot a Histogram in Python How to Import Files in Python How to Download all Modules in Python How to get Time in seconds in Python How to Practice Python Programming How to plot multiple linear regression in Python How to set font for Text in Python How to Convert WhatsApp Chat Data into a Word Cloud using Python How to Install Tweepy in Python How to Write a Configuration file in Python How to Install Scikit-Learn How to add 2 lists in Python How to assign values to variables in Python and other languages How to build an Auto Clicker using Python How to check if the dictionary is empty in Python How to check the version of the Python Interpreter How to convert Float to Int in Python How to Convert Int to String in Python How to Define a Function in Python How to Install Pandas in Python How to Plot Graphs Using Python How to Program in Python on Raspberry pi How to Reverse a number in Python How to Sort a String in Python How to build a Virtual Assistant Using Python How to Fix an EOF Error in Python How to make a firewall in Python How to clear screen in Python How to Create User Defined Exceptions in Python How to determine if a binary tree is height-balanced How to Import Kaggle Datasets Directly into Google Colab How to Install Python in Kali Linux

Sorting

Python Sort List Sort Dictionary in Python Python sort() function Python Bubble Sort

Programs

Factorial Program in Python Prime Number Program in Python Fibonacci Series Program in Python Leap Year Program in Python Palindrome Program in Python Check Palindrome In Python Calculator Program in Python Armstrong Number Program in Python Python Program to add two numbers Anagram Program in Python Number Pattern Programs in Python Even Odd Program in Python GCD Program in Python Python Exit Program Python Program to check Leap Year Operator Overloading in Python Pointers in Python Python Not Equal Operator Raise Exception in Python Salary of Python Developers in India

Questions

What is a Script in Python What is the re.sub() function in Python After Python What Should I Learn What Does the Percent Sign (%) Mean in Python What is online python free IDE What is Python online compiler What are the Purposes of Python What is Python compiler GDB What is Ipython shell What does base case mean in recursion What does the if __name__ == "__main__" do in Python What is Sleeping Time in Python What is Collaborative Filtering in ML, Python What is the Python Global Interpreter Lock What is None Literal in Python What is the Output of the bool in Python Is Python Case-sensitive when Dealing with Identifiers Is Python Case Sensitive Is Python Object Oriented Programming language

Differences

Difference between Perl and Python Difference between python list and tuple Difference between Input() and raw_input() functions in Python Difference between Python 2 and Python 3 Difference Between Yield And Return In Python Important Difference between Python 2.x and Python 3.x with Example Difference between Package and Module in Python Difference between Expression and Statement in Python Difference between For Loop and While Loop in Python Difference between Module and Package in Python Difference between Sort and Sorted in Python Difference between Overloading and Overriding in Python Python vs HTML Python vs R Python vs Java Python vs PHP While vs For Loop in Python Python Iterator vs Iterable Set Vs List Python

Python Kivy

Kivy Architecture Kivy Buttons Kivy Layouts Kivy Widgets What is Kivy in Python

Python Tkinter

Application to get live USD/INR rate Using Tkinter in Python Application to Search Installed Application using Tkinter in Python Compound Interest GUI Calculator using Tkinter in Python Create a Table Using Tkinter in Python Create First GUI Application using Tkinter in Python File Explorer using Tkinter in Python GUI Calendar using Tkinter in Python GUI to extract lyrics from a song Using Tkinter in Python GUI to Shut down, Restart and Logout from the PC using Tkinter in Python Loan calculator using Tkinter in Python Make Notepad using Tkinter in Python Rank Based Percentile GUI Calculator using Tkinter in Python Screen Rotation app Using Tkinter in Python Spell Corrector GUI using Tkinter in Python Standard GUI Unit Converter using Tkinter in Python Text detection using Tkinter in Python To Do GUI Application using Tkinter in Python Weight Conversion GUI using Tkinter in Python Age calculator using Tkinter Create a Digital Clock Using Tkinter Create a GUI Marksheet using Tkinter Simple GUI Calculator Using Tkinter Simple Registration form using Tkinter Weight Conversion GUI Using Tkinter Color Game Using Tkinter in Python File Explorer in Python using Tkinter Making of Notepad Using Tkinter Python Simple FLAMES Game Using Tkinter Python ToDo GUI Application Using Tkinter Python

Python PyQt5

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Misc

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Python Image Processing

What is an Image?

Images are the pictures that will define the world, and it has their own story, and consists of information about them and these are useful in many ways. It is also a visual representation of anything produced by displaying it using an electronic display such as a Laptop, Television, etc. It is also an idea that pictures on our minds and keeps that as a picture or image. It is of 2D and 3D visualization.

This imaging technique is obtained by a process known as "Image Processing."

It plays an important role in a real-world scenario and is the main and important part of computer vision, like self-driving cars, robotics, face and mask detection. Image processing helps us in many ways to manipulate and processes many images at a time and has a wide range of applications in many fields.

Python programming language is most widely used for this image processing and has many Python libraries and tools to help complete the image processing process more efficiently.

In this context, we will learn about algorithms, tools and techniques that process the image to get the correct result.

What is Image Processing?

The name says that image processing means processing an image that includes different techniques and tools. This will result in an image or a type of feature that is used for future analysis.

The result will be displayed as an image and can be represented as a 2D function I(x, y), where x and y represent spatial coordinates. At some point, the intensity for images will be defined as the amplitude of "I" at a particular value of x and y. If this value of amplitude and x, y is finite, then we call it a "digital image." It consists of an array of pixels arranged in rows and columns. “Pixel” means it contains complete information about the image, like the intensity of an image at a particular point and the color of an image.

Python Image Processing

 As discussed above, an image can be in 3D where x, y and z will be spatial coordinates. The pixels of the image are arranged in the form of the matrix, known as an "RGB" image.

There are many types of images. They are:

RGB image: This consists of three layers of the 2D image, and the three layers are which are red, green, and blue channels.

Python Image Processing

Grayscale image: This image consists of shades of black and white, containing only a single channel.

Another definition for image processing is a method to perform some operation on an image, which is done to get an enhanced image or to enhance a piece of useful information from it. It is also a type of signal processing in which input is an image, and output can also be an image or characteristics or a feature associated with that particular image.

Why do we Use Image Processing?

We all know image processing is among the rapidly growing technologies and forms the core research area within engineering and computer science.

Image processing is used in various fields:

  1. It is used to track human behavior and their positions and can be further used to develop games or any security task.
  2. Another popular use case of image processing is "Driverless cars." We all are witnesses to this, and we also see that driverless cars are one of the coolest pieces of technology today. The top players in driverless cars are Tesla, Audi, Mercedes and many more.
  3. It implements image processing in medical images we use in x-ray, CT scans or MRI to find abnormalities. Suppose a person has a kind of fracture or cancer detected using an MRI. We can compare that particular image with the other images that do not have or are normal. Based on certain criteria and applying that to a deep learning model, we can determine whether any abnormalities are present.

Python for Image Processing

We have various programming languages and frameworks to work with, but one of the popular approaches is using Python. Python has many built-in libraries and tools with which we can not only perform actions on these images like thresholding and augmentation. We can also process the images using deep learning or machine learning algorithms to perform classification operations.

Some popular frameworks or libraries here are OpenCV, Py Torch, TensorFlow, NumPy and many more.

There are many python frameworks and libraries used to process an image. They are OpenCV, NumPy, Py Torch, TensorFlow, and many more.

Let us discuss these concepts one by one:

  • OpenCV: Processing an image library mainly focuses o real-time computer vision with application in a wide range of areas like 2D and 3D features, face and mask detection, Computer and human detection, Robots and mobiles, Object and human identification and any other.
  • NumPy and SciPy Libraries: These libraries manipulate and process an image.
  • Scikit: These libraries provide lots of algorithms for processing an image.
  • Python Imaging Library (PIL): These perform simple operations on images like the creation of thumbnails on pictures, resizing of an image, rotation of an image, conversion of file formats etc.

In this article, we are going to see how an image is going to process in Python.

Installing a Required Library

Firstly, we should install the required library, like OpenCV, pillow or other that we want to use for processing an image. We can also use "pip" to install the required library.

We use the following command to install the pillow

$pip install pillow

Now by installing this, we can do as many things with images. We can play with these images.

Open () and show () the Image

For example,

#Importing required library
from PIL import Image


#Opening the Image
pc = Image.open("flower.jpg")

Output

Python Image Processing

From the above example, "pc" is a pillow object, and we also retrieve some information about the opened image.

Converting the image and saving the image

We can also change the image from one form to another form.

>>>pc.save('flower.png')

When we see the folder, we observe that the same image format will be from one form to another.

When we want to change the size of the image, we use the thumbnail () method of the pillow.

>>>pc.thumbnail ((200, 200))
>>>pc.show()

The image will be as follows

Python Image Processing

Image Filtering

Image filtering is modifying an image by changing the shades of colour of the pixel. It is also used to increase brightness and contrast. In this article, we will learn about several types of filters.

Image processing filters are mainly used to suppress high frequencies, that is, by smoothing an image or by lowering and enhancing or detecting the edges in that particular image that can filter either by using a frequency domain or in a spatial domain.

The frequency domain involves transforming that particular image into a frequency domain by multiplying that frequency with a frequency filter. Once that is done-transforming the result into a spatial domain.

The spatial domain is nothing but a matrix the other way to filter our image is by using a kernel, or it can also be referred to as a filter used to extract any information from this. We have the mode and maximum filters for some of the popular filters.

We have various programming languages and frameworks to work with, but one of the popular approaches is using Python. Python has many built-in libraries and tools with which we can not only perform actions on these images like thresholding and augmentation. We can also process the images using deep learning or machine learning algorithms to perform classification operations.

LayerPadding

We have discussed many filters above so that filters move through this image across the grids. Most of the time, our image gets cropped, and when an image gets cropped, these particular pixels will get cropped.

When an image gets cropped, most of the features are lost. What if there is an important feature which is present at this edge? To prevent that, we will add some extra layers of pixels. All of these external layers will include in our final transformation.

This imaging technique is obtained by a process known as "Image Processing."

It plays an important role in a real-world scenario and is the main and important part of computervision, like self-driving cars, robotics and face and mask detection. Image processing helps us in many ways to manipulate and processes many images at a time and has a wide range of applications in many fields.

Python programming language is most widely used for this image processing and has many Python libraries and tools to help complete the image processing process more efficiently.

In this context, we will learn about algorithms, tools and techniques that process the image to get the correct result.

Python Image Library

Python Image Library is used for manipulating images and working with the different formats of images. In the new version, it is known as "PILLOW". There are two methods to display the images in python that is:

  1. The first one is the photo viewer
  2. The second one is the "Tkinter window".

PIL displays the image in the photo viewer like the default image viewer software. Still, we will mostly use the "matplotlib" library of python to display the images within the console.

from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

Here we are going to import the necessary imports. So, from the pill, we will import images which are the main component of the pill and image. We get to create an image object, and then you can manipulate the image object with different methods.

We will import matplotlib because when you display an image in pill, it usually uses your default operating systems application. These images will open from an operating system to view images.

We also have numpy, matplotlib and inline to show all the images.

We have steps to follow in this python image library.

1.Reading

We can read the image using the Python image library's open function of the image module. This function takes the URL path of the image as a parameter. We can also pass all the image file extensions like jpeg, jpg and png. This method is going to create an image object.

flower=Image.open("flower.jpg")
flower2=Image.open('flower2.jpg')
Python Image Processing

We have a path to the image. Here we have two images and two objects, so we want to display the images.

We have another method for displaying the images that are"Displaying."

2. Displaying

There are two methods to display the image, as we discussed already. One is to show the function of the image object displays image in the photo viewer that will be the function called show(), and "imshow()" is a function of Matlab plot library, and it takes the image as a parameter and plots the image in axes.

Here we go by using these methods.

image.show() # this will open photo viewer
plt.imshow(flower)
plt.imshow(flower2)

Output

Python Image Processing

image. Show () method will usually open up our default operating system image viewer, Windows Image Viewer and IrfanView.

Displaying Properties of Image

We can see images' properties like size, format and mode.

Size given the (length, width)
The format gives file format (like png, jpeg, jpg)
The mode gives the channel format (HSV (hue saturation values), RGB, BGR etc)
print(image.size)
print(image.format)
print(image.mode)

It displays width by height. We already have rows followed by columns, but in pill, there will be columns followed by rows.

When we display an image, we should save an image.

3. Saving

We can store the image using the save function that takes the directory path, including file(filename+file format)

image.save("newimage.jpg")

Here newimage.jpg is the path name.

4. Copying

We can also copy an image. That is, we can duplicate an image using the copy function of PIL. It has no parameter, and it returns an image object.

copied image=image. Copy ()
plt.imshow(copied_ image)


Sometimes we want to make transformations to the image, and we don't want to disturb the original image objects so that we can make a copy of it, which is a very simple image. copy().

We are displaying it with PLT.

5. Transposing

We can change the orientation of the image using the transpose function. The transpose function takes one parameter, which is a method of transpose. There are six transposing methods we can use. They are as follows:

Image.FLIP_LEFT_RIGHT(This is the inverse of the rows of image)
Image.FLIP_TOP_BOTTOM(This inverse the columns of the image)
Image.ROTATE_90(This rotates the image by an angle of 90)
Image.ROTATE_180(This rotates the image by the angle of 180)
Image.ROTATE_270(This rotates the image angle by 270)
Image.TRANSPOSE(This converts the rows into columns)
With this, it returns the image object.

Advantages of Image Processing

  1. Digital image processing makes digital images can be noise-free.
  2. It can be made available in any desired format. (X-rays, Photo negatives, improved image)
  3. Digital imaging is the ability of the operator.
  4. It is easy to learn and use and has an extensive library.
  5. Images can be stored in computer memory and easily retrieved on the same computer screen.
  6. It allows the electronic transmission of images to third-party providers.