Lenora  Hauck

Lenora Hauck

1597855680

Understanding and Decoding a JPEG Image using Python

Hi everyone! 👋 Today we are going to understand the JPEG compression algorithm. One thing a lot of people don’t know is that JPEG is not a format but rather an algorithm. The JPEG images you see are mostly in the JFIF format (JPEG File Interchange Format) that internally uses the JPEG compression algorithm. By the end of this article, you will have a much better understanding of how the JPEG algorithm compresses data and how you can write some custom Python code to decompress it. We will not be covering all the nuances of the JPEG format (like progressive scan) but rather only the basic baseline format while writing our decoder.

Introduction

Why write another article on JPEG when there are already hundreds of articles on the internet? Well, normally when you read articles on JPEG, the author just gives you details about what the format looks like. You don’t implement any code to do the actual decompression and decoding. Even if you do write code, it is in C/C++ and not accessible to a wide group of people. I plan on changing that by showing you how a basic JPEG decoder works using Python 3. I will be basing my decoder on this MIT licensed code but will be heavily modifying it for increased readability and ease of understanding. You can find the modified code for this article on my GitHub repo.

Different parts of a JPEG

Let’s start with this nice image by Ange Albertini. It lists all different parts of a simple JPEG file. Take a look at it. We will be exploring each segment. You might have to refer to this image quite a few times while reading this tutorial.

JPEGRGB_dissected.png

At the very basic level, almost every binary file contains a couple of markers (or headers). You can think of these markers as sort of like bookmarks. They are very crucial for making sense of a file and are used by programs like file (on Mac/Linux) to tell us details about a file. These markers define where some specific information in a file is stored. Most of the markers are followed by length information for the particular marker segment. This tells us how long that particular segment is.

File Start & File End

The very first marker we care about is FF D8. It tells us that this is the start of the image. If we don’t see it we can assume this is some other file. Another equally important marker is FF D9. It tells us that we have reached the end of an image file. Every marker, except for FFD0 to FFD9 and FF01, is immediately followed by a length specifier that will give you the length of that marker segment. As for the image file start and image file end markers, they will always be two bytes long each.

Throughout this tutorial, we will be working with this image:

#python #image using python #different parts of a jpeg

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Understanding and Decoding a JPEG Image using Python
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

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:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Lenora  Hauck

Lenora Hauck

1597855680

Understanding and Decoding a JPEG Image using Python

Hi everyone! 👋 Today we are going to understand the JPEG compression algorithm. One thing a lot of people don’t know is that JPEG is not a format but rather an algorithm. The JPEG images you see are mostly in the JFIF format (JPEG File Interchange Format) that internally uses the JPEG compression algorithm. By the end of this article, you will have a much better understanding of how the JPEG algorithm compresses data and how you can write some custom Python code to decompress it. We will not be covering all the nuances of the JPEG format (like progressive scan) but rather only the basic baseline format while writing our decoder.

Introduction

Why write another article on JPEG when there are already hundreds of articles on the internet? Well, normally when you read articles on JPEG, the author just gives you details about what the format looks like. You don’t implement any code to do the actual decompression and decoding. Even if you do write code, it is in C/C++ and not accessible to a wide group of people. I plan on changing that by showing you how a basic JPEG decoder works using Python 3. I will be basing my decoder on this MIT licensed code but will be heavily modifying it for increased readability and ease of understanding. You can find the modified code for this article on my GitHub repo.

Different parts of a JPEG

Let’s start with this nice image by Ange Albertini. It lists all different parts of a simple JPEG file. Take a look at it. We will be exploring each segment. You might have to refer to this image quite a few times while reading this tutorial.

JPEGRGB_dissected.png

At the very basic level, almost every binary file contains a couple of markers (or headers). You can think of these markers as sort of like bookmarks. They are very crucial for making sense of a file and are used by programs like file (on Mac/Linux) to tell us details about a file. These markers define where some specific information in a file is stored. Most of the markers are followed by length information for the particular marker segment. This tells us how long that particular segment is.

File Start & File End

The very first marker we care about is FF D8. It tells us that this is the start of the image. If we don’t see it we can assume this is some other file. Another equally important marker is FF D9. It tells us that we have reached the end of an image file. Every marker, except for FFD0 to FFD9 and FF01, is immediately followed by a length specifier that will give you the length of that marker segment. As for the image file start and image file end markers, they will always be two bytes long each.

Throughout this tutorial, we will be working with this image:

#python #image using python #different parts of a jpeg

How To Compare Tesla and Ford Company By Using Magic Methods in Python

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.

1. init

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

2. add

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

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python

Python Imread(): Different Ways to Load an Image using The OpenCV.imread() Method

In this tutorial, we will learn how to use imread() method of OpenCV-Python in detail and different ways to load an image using imread() method.

Table of Contents

What is Python imread()?

Importing OpenCV to use Python imread()

Syntax of the Python imread() method

Image formats supported by Python imread() method

#python modules #opencv-python #python imread() #opencv.imread() #python imread(): different ways to load an image using the opencv.imread() method #load an image