handwritten_digit_recognizer's Introduction

Handwritten Digit Recognizer

This is a small tool I've written for learning Tensorflow to recognize handwritten digits. You can write a digit in the box with mouse or tablet, and the program will recognize it and display the probabilities of each categories. Press the right mouse button to clear the image. Click the button on the right, and the program will save the image in the corresponding directory.

Requirements:

Python
PySide
Tensorflow
python-opencv
numpy

Running:

Before use, you need to execute the following command to install dependencies.

sudo pip install -r requirements.txt

Then you can run the tool by the following command:

python recognize.py

Theory

The tool uses a simple neural network architecture shown in the table below to recognize digits. The network is trained on the MNIST dataset (http://yann.lecun.com/exdb/mnist/).

layer	parameter	shape
input		28x28x1
conv	kernel 5x5 filters 6 strides 1 padding 2	28x28x6
relu		28x28x6
pool	max_pooling stride 2	14x14x6
conv	kernel 5x5 filters 16 strides 1 padding 0	10x10x16
relu		10x10x16
pool	max_pooling stride 2	5x5x16
conv	kernel 5x5 filters 32 strides 1 padding 0	1x1x32
flatten		32
dense	hidden_units 64	64
relu		64
dense	hidden_units 10	10
output

You can modify the relevant code in tf_predict.py to use your own neural network architecture.

Thanks to Yann LeCun, for both MNIST and LeNet-5.

Recommend Projects

jsyzgaochao / handwritten_digit_recognizer Goto Github PK