Handwritten Digit Recognition Project in Python Source Code

In Python, Handwritten Digit Recognition Project is a deep learning project which aims to provide a easiest way to recognized a handwritten digit.

Further, the handwritten digit recognition also refers to a program which has the capacity to recognize human handwritten digits from a variety of sources, such as photographs, papers, and touch displays, and classify them into ten specified categories (0-9). In the realm of deep learning, this has been a topic of inexhaustible investigation.

What is Handwritten Digit Recognition Project in Python?

The handwritten digit recognition system is deep learning project with the used of (MINIST dataset), the project was design to basically recognized or detects scanned fingerprints, images of handwritten numbers or a digits.

What is MNIST handwritten dataset?

A MINIST dataset is stands for (Modified National Institute of Standards and Technology dataset). This is popular dataset with at least 10,000 images for testing and training images of handwritten testing sets.

What is the use of handwritten digit recognition using Python?

This handwritten digit recognition it can be used as a major solution for recognizing scanned images of a single digit or number which has been present on the images of handwritten digits.

Further, the handwritten digit recognition has the ability to easily recognized human handwritten of a digits or a numbers.

Why do we use handwritten digit recognition?

A handwritten digit recognition in Python is needed for recognizing digits or a number, the project can provide the ability to recognized primarily (human handwritten digits).

In addition, there are some instances that the machine could not recognized the handwritten perfectly because there are some number or handwritten digits are not perfect and recognizable for training and testing.

What are the features of handwritten digit recognition?

The following are the main features of handwritten digit recognition

  • Preprocessing step
  • Feature extraction and selection step
  • Classification and verification step

What is future scope of handwritten digit recognition?

There are some future scope of handwritten digit recognition using a scanned images and have a great importance and use in online and offline handwritten recognition on many platforms.

Further, It can also be used for recognizing zip codes on mail and postal mail sorting, numeric entries in by filling in forms by hand and the most important is for processing bank account for checking amounts.

Importance of Handwritten Digit Recognition?

In practically every industry, machine learning and deep learning are reducing human effort. Furthermore, a system based on ML and DL may power multiple applications at the same time, minimizing human labor and enhancing the solution’s versatility.

Handwritten Digit Recognition: Project Details and Technology

Project Name:Handwritten Digit Recognition Project In Python With Source Code
AbstractHandwriting Digit Recognition Python is to convert handwritten digits into machine readable formats.
Language/s Used:Python Deep Learning
Python version (Recommended):3.8/3.9
Type:Desktop Application
Developer:Source Code Hero
Handwritten Digit Recognition Project – Project Information

Handwritten Digit Recognition In Python : About the project

This Handwritten Digit Recognition In Python was created with Python Deep Learning, and we will use the MNIST dataset to design a handwritten digit recognition software. Convolutional Neural Networks are a sort of deep neural network that we will use. Finally, we’ll create a user interface that allows you to draw a digit and instantly recognize it.

The capacity of computers to detect human handwritten digits is known as handwritten digit recognition. Because handwritten digits are not flawless and can be generated with a variety of tastes, it is a difficult assignment for the machine. The solution to this problem is handwritten digit recognition, which uses an image of a digit to recognize the digit present in the image.

This Handwritten Digit Recognition also includes a downloadable Project With Source Code for free, just find the downloadable source code below and click to start downloading.

By the way, if you are new to python programming and you don’t have any idea what Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS for you. Additionally, I also have here How to Download and Install Latest Version of Python on Windows.

To start executing a Handwritten Digit Recognition In Python With Source Code, make sure that you have installed Python in your computer.

Handwritten Digit Recognition In Python With Source Code : Steps on how to run the project

Time needed: 5 minutes.

These are the steps on how to run Handwritten Digit Recognition In Python With Source Code

  • Step 1Download Source Code

    First, download the provided source code below.
    handwritten digit download source code

  • Step 2Extract File

    Next, after the download finished extract the zip file.
    handwritten digit extract file

  • Step 3: Import the project to your PyCharm IDE.

    Next, import the source code you’ve download to your PyCharm IDE.
    handwritten digit open project

  • Step 4: Install all Libraries.

    Next, install all libraries given below.
    handwritten digit import libraries

  • Step 5: Open cmd.

    Next, click the folder directory of the project and type cmd.
    handwritten digit open cmd

  • Step 6: Run Project.

    last, run the project with the command “py main.py”

    handwritten digit run project

Download Source Code below


In this article, we have successfully built a Python deep learning project on handwritten recognition app. We have built and trained the Convolutional neural network which is very effective for image classification purposes. Later on, we build the GUI where we draw a digit on the canvas then we classify the digit and show the results.


If you have any questions or suggestions about Handwritten Digit Recognition In Python With Source Code, please feel free to leave a comment below.

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