handwritten-MNIST-digit-recognition

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handwritten-MNIST-digit-recognition

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Real time MNIST digit recognition with OpenCV and Support Vector Machine (SVM) algorithm.

handwritten-MNIST-digit-recognition 최신버젼 다운로드

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# Handwritten Digit Recognition Using OpenCV and Python

## Dataset used
For this project I used the MNIST dataset. It is freely available on the Internet.

## Requirements
1. Python 3
2. Sklearn
3. OpenCV 3
4. numpy
5. Jupyter-Notebook

## Training SVM model
1. SVM_Classifier.ipynb - This is a ipython notebook so you need jupyter-notebook installed to use this file. Use this file if you want to retrain the model.
2. digits_cls1.pkl - This is a saved SVM model file.

## Digit recognition using OpenCV
dig_rec.ipynb - This is a ipython notebook for recognising handwritten digit in images using OpenCV .This file is using trained SVM model digits_cls1.pkl.

## Real time single digit recognition using OpenCV
dig_rec_vid.ipynb - This is a ipython notebook for recognising single handwritten digit using webcam and OpenCV .This file is also using trained SVM model digits_cls1.pkl.

## Real time multi digit recognition using OpenCV
multidig_rec_vid.ipynb - This is a ipython notebook for recognising multi handwritten digit using webcam and OpenCV .This file is also using trained SVM model digits_cls1.pkl.

## How to use these projects
You can use these projects direct opening the perticular ipython notebook dig_rec.ipynb or dig_rec_vid.ipynb or multidig_rec_vid.ipynb.

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