data_generator.reset()
print('Predict data time: %.3f s' % (time.time() - start_time))
del model2
# Save to .corpus
print 'Create corpus'
sys.stdout.flush()
save_corpus(CORPUS_FILE,X_data_gap)
# Create inverted index
print 'Create inverted index'
sys.stdout.flush()
smhHelper.createInvertedIndex(CORPUS_FILE,INVERT_INDEX_FILE)
# Create model
print 'Create model'
start_time = time.time()
smhHelper.createModel(CORPUS_FILE,INVERT_INDEX_FILE,MODEL_FILE)
print('Create model time: %.3f s' % (time.time() - start_time))
sys.stdout.flush()
# Create ranking file
start_time = time.time()
Y_data = selectModels.selectModels(NUM_CLASSES,MODEL_FILE,INVERT_INDEX_FILE,TOTAL_IMAGES)
print('Select models time: %.3f s' % (time.time() - start_time))
sys.stdout.flush()
# Evaluate MAPP
start_time = time.time()
execfile('rankingImages.py')
print('ranking images time: %.3f s' % (time.time() - start_time))
sys.stdout.flush()
import sys
sys.path.append('../common/')
import smhHelper
smhHelper.createModel('google.corpus', 'google.ifs', 'google.model')