upd deps

main.js

@@ -1,19 +1,19 @@
-(function(log) {
+(function (log) {
  'use strict';
- 
+
  log('reading config file ...');
- 
+
  var synaptic = require('synaptic'),
  network = require('./network.js'),
  captcha = require('./captcha.js'),
  tools = require('./tools.js'),
  PNG = require('pngjs').PNG,
  fs = require('fs'),
  config = JSON.parse(fs.readFileSync('./config.json', 'utf8'));
- 
+
  if(config === null)
  return;
- 
+
  config.training_set = config.training_set || 2000;
  config.testing_set = config.testing_set || 500;
  config.image_size = config.image_size || 20;
@@ -24,27 +24,27 @@
  config.network.hidden = config.network.hidden || 40;
  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
- config.network.output // output
+ 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 = [],
@@ -58,101 +58,101 @@
  };
 
  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'),
+
+ 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-idx3-ubyte');
- labels = fs.readFileSync('./mnist/t10k-labels-idx1-ubyte');
- 
+
+ 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) {
  if(error)
  throw error;
- 
+
  var position,
  chunk = [],
  pixel = [],
  i, j, k, x, y;
- 
+
  for(i = 0; i < config.text.length; i++) {
  for(y = 0; y < data.height; y++) {
  for(x = i * config.image_size; x < (i * config.image_size + config.image_size); x++) {
@@ -169,28 +169,31 @@
  pixel = [];
  }
  }
- 
+
  chunk = tools.center(chunk);
-
+
+ var output = Array.apply(null, new Array(config.network.output)).map(Number.prototype.valueOf, 0);
+ output[i] = 1;
+
  if(index < config.training_set) {
  training.push({
  input: chunk,
- output: ('0000' + text.charCodeAt(i).toString(2)).substr(-4).split('').map(Number)
+ output: output
  });
  } else {
  testing.push({
  input: chunk,
- output: ('0000' + text.charCodeAt(i).toString(2)).substr(-4).split('').map(Number)
+ output: output
  });
  }
- 
+
  chunk = [];
  }
- 
+
  if(index === samples - 1) {
  log('... done');
  log();
- 
+
  network.train(perceptron, training, config.network.learning_rate);
  fs.writeFileSync('./ocr.js', perceptron.standalone().toString());
  network.test(perceptron, testing);

package.json

@@ -9,9 +9,9 @@
  "author": "Mateo Gianolio",
  "license": "MIT",
  "dependencies": {
- "canvas": "^1.2.1",
- "pngjs": "^0.4.0",
- "synaptic": "^0.1.7"
+ "canvas": "^1.3.7",
+ "pngjs": "^2.2.0",
+ "synaptic": "^1.0.2"
  },
  "repository": {
  "type": "git",