fix #9

config.json

@@ -5,8 +5,8 @@
  "sans-serif",
  "serif"
  ],
- "training_set": 20000,
- "testing_set": 500,
+ "training_set": 2000,
+ "testing_set": 1000,
  "image_size": 16,
  "threshold": 400,
  "network": {

main.js

@@ -1,14 +1,7 @@
-<<<<<<< HEAD
-(function (log) {
- 'use strict';
-
- log('reading config file ...');
-=======
 (function () {
  'use strict';
 
  console.log('reading config file ...');
->>>>>>> softmax
 
  var synaptic = require('synaptic'),
  network = require('./network.js'),
@@ -29,131 +22,6 @@
  config.fonts = config.fonts || ['serif', 'sans-serif'];
  config.distortion = config.distortion === undefined ? true : config.distortion;
  config.network.hidden = config.network.hidden || 40;
-<<<<<<< HEAD
- config.network.output = config.network.output || 8;
- config.network.learning_rate = config.network.learning_rate || 0.1;
-
- log('... done');
- log();
-
- var perceptron;
-
- if(config.mnist === true) {
- perceptron = new synaptic.Architect.Perceptron(
- (config.image_size * config.image_size), // input
- config.network.hidden, // hidden
- 4 // output
- );
-
- mnist();
- } else {
- perceptron = new synaptic.Architect.Perceptron(
- (config.image_size * config.image_size), // input
- config.network.hidden, // hidden
- config.network.output // output
- );
-
- var index,
- samples = config.training_set + config.testing_set,
- training = [],
- testing = [],
- settings = {
- size: config.text.length,
- height: config.image_size,
- text: config.text,
- fonts: config.fonts,
- distortion: config.distortion
- };
-
- log('generating images ...');
-
- for(index = 0; index < samples; index++)
- captcha.generate(settings, generate(index));
- }
-
- // captcha callback
- function generate(index) {
- return function(text, data) {
- var png = new PNG({ filterType: 4 });
- png.parse(data, parse(text, index));
-
- if(index === 0)
- fs.writeFileSync('./examples/' + text + '.png', data, 'base64');
- };
- }
-
- // parse MNIST data
- function mnist() {
- log('parsing MNIST data ...');
-
- var data = fs.readFileSync('./mnist/train-images.idx3-ubyte'),
- labels = fs.readFileSync('./mnist/train-labels.idx1-ubyte'),
- training = [],
- testing = [],
- pixels = [],
- image,
- x, y;
-
- config.training_set = 60000;
- config.testing_set = 10000;
- config.threshold = 50;
- config.image_size = 20;
-
- for(image = 0; image < config.training_set; image++) {
- for(y = 4; y < config.image_size + 4; y++)
- for(x = 4; x < config.image_size + 4; x++)
- pixels.push(data[(image * 28 * 28) + (x + (y * 28)) + 15]);
-
- pixels = tools.center(
- pixels.map(function(pixel) {
- return pixel > config.threshold ? 1 : 0;
- })
- );
-
- training.push({
- input: pixels,
- output: ('0000' + parseInt(labels[image + 8]).toString(2)).substr(-4).split('').map(Number)
- });
-
- pixels = [];
- }
-
- data = fs.readFileSync('./mnist/t10k-images-2.idx3-ubyte');
- labels = fs.readFileSync('./mnist/t10k-labels.idx1-ubyte');
-
- for(image = 0; image < config.testing_set; image++) {
- for(y = 4; y < config.image_size + 4; y++)
- for(x = 4; x < config.image_size + 4; x++)
- pixels.push(data[(image * 28 * 28) + (x + (y * 28)) + 15]);
-
- pixels = tools.center(
- pixels.map(function(pixel) {
- return pixel > config.threshold ? 1 : 0;
- })
- );
-
- testing.push({
- input: pixels,
- output: ('0000' + parseInt(labels[image + 8]).toString(2)).substr(-4).split('').map(Number)
- });
-
- pixels = [];
- }
-
- log('... done', '\n');
-
- tools.validate(perceptron, training);
- tools.validate(perceptron, testing);
-
- network.train(perceptron, training, config.network.learning_rate);
- fs.writeFileSync('./ocr.js', perceptron.standalone().toString());
- network.test(perceptron, testing);
- }
-
- // 'parsed' event callback
- function parse(text, index) {
- return function(error, data) {
-=======
  config.network.output = config.network.output || 10;
  config.network.learning_rate = config.network.learning_rate || 0.1;
 
@@ -187,18 +55,13 @@
  var png = new PNG({ filterType: 4 });
 
  png.parse(data, function(error, data) {
->>>>>>> softmax
  if(error)
  throw error;
 
  var position,
  chunk = [],
  pixel = [],
-<<<<<<< HEAD
- i, j, k, x, y;
-=======
  i, j, x, y;
->>>>>>> softmax
 
  for(i = 0; i < config.text.length; i++) {
  for(y = 0; y < data.height; y++) {
@@ -222,11 +85,7 @@
  var output = Array.apply(null, new Array(config.network.output)).map(Number.prototype.valueOf, 0);
  output[i] = 1;
 
-<<<<<<< HEAD
- if(index < config.training_set) {
-=======
  if(k < config.training_set) {
->>>>>>> softmax
  training.push({
  input: chunk,
  output: output
@@ -241,29 +100,19 @@
  chunk = [];
  }
 
-<<<<<<< HEAD
- if(index === samples - 1) {
- log('... done');
- log();
-=======
  if(k++ === samples - 1) {
  console.log('... done');
  console.log();
->>>>>>> softmax
 
  network.train(perceptron, training, config.network.learning_rate);
  fs.writeFileSync('./ocr.js', 'module.exports = ' + perceptron.standalone().toString());
  network.test(perceptron, testing);
  }
  });
  }
-<<<<<<< HEAD
-})(console.log);
-=======
 
  console.log('generating images ...');
 
  for(index = 0; index < samples; index++)
  captcha.generate(settings, generate);
 })();
->>>>>>> softmax