Character Recognizer

Character Recognizer is a Python-based project for recognizing characters from images using OpenCV and machine learning. This project involves training a model on a set of character images and then using that trained model to recognize characters in new images.

Table of Contents

• Character Recognizer
  • Table of Contents
  • Introduction
  • Features
  • Installation
  • Usage
    • Training the Model
    • Testing the Model

Introduction

The Character Recognizer project utilizes OpenCV for image processing and machine learning techniques to recognize characters in images. The project consists of two main parts:

1. Training a model using character images.
2. Using the trained model to recognize characters in new images.

Features

• Training a character recognition model from a set of character images.
• Recognizing characters from new images using the trained model.
• Visualization of the training process and recognition results.

Installation

To get started with the Character Recognizer, follow these steps:

1. Clone the repository:

   git clone https://github.com/DevadattaP/Character_recognizer.git
   cd character-recognizer

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

Training the Model

To train the model, run the TrainModel.py script with a training image containing characters.

python TrainModel.py

Note

When the training program is run, segmented image will be shown, and you have to tell the machine what the highlighted letter/digit/character is by pressing corresponding key.

Testing the Model

To recognize characters from a new image, run the TestModel.py script with the test image.

python TestModel.py

Tip

You can change the image names in the both the python files, to test and train model on different images.