runMinicontest.py

# runMinicontest.py
# -----------------
# Licensing Information: Please do not distribute or publish solutions to this
# project. You are free to use and extend these projects for educational
# purposes. The Pacman AI projects were developed at UC Berkeley, primarily by
# John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html

# This file is for running the minicontest submission.

import minicontest
import samples
import sys
import util
import pickle
from dataClassifier import DIGIT_DATUM_HEIGHT,DIGIT_DATUM_WIDTH,contestFeatureExtractorDigit

TEST_SIZE = 1000

MINICONTEST_PATH = "minicontest_output.pickle"


if __name__ == '__main__':
  print "Loading training data"
  rawTrainingData = samples.loadDataFile("digitdata/trainingimages", 5000,DIGIT_DATUM_WIDTH,DIGIT_DATUM_HEIGHT)
  trainingLabels = samples.loadLabelsFile("digitdata/traininglabels", 5000)
  rawValidationData = samples.loadDataFile("digitdata/validationimages", 100,DIGIT_DATUM_WIDTH,DIGIT_DATUM_HEIGHT)
  validationLabels = samples.loadLabelsFile("digitdata/validationlabels", 100)
  rawTestData = samples.loadDataFile("digitdata/testimages", TEST_SIZE,DIGIT_DATUM_WIDTH,DIGIT_DATUM_HEIGHT)
    
 
  featureFunction = contestFeatureExtractorDigit
  legalLabels = range(10)
  classifier = minicontest.contestClassifier(legalLabels)

  print "Extracting features..."
  trainingData = map(featureFunction, rawTrainingData)
  validationData = map(featureFunction, rawValidationData)
  testData = map(featureFunction, rawTestData)

  print "Training..."
  classifier.train(trainingData, trainingLabels, validationData, validationLabels)
  print "Validating..."
  guesses = classifier.classify(validationData)
  correct = [guesses[i] == validationLabels[i] for i in range(len(validationLabels))].count(True)
  print str(correct), ("correct out of " + str(len(validationLabels)) + " (%.1f%%).") % (100.0 * correct / len(validationLabels))
  print "Testing..."
  guesses = classifier.classify(testData)

  print "Writing classifier output..."
  outfile = open(MINICONTEST_PATH,'w')
  output = {}
  output['guesses'] = guesses;
  pickle.dump(output,outfile)
  outfile.close()
  print "Write successful."