def create_histogram(self, normalize_histogram=False):
counts = []
words = []
word_occurences = []
hists = []
words_1 = []
self.logger.info('Start histogram creation...')
fe = ExtractFeatures(self.feature_type)
for idx, image_name in enumerate(self.im_list):
self.logger.debug('Processing image %s, %s out of %s', image_name,
idx, len(self.im_list))
try:
img = np.array(Image.open(image_name))
except Exception as e:
self.logger.error('Failed to load image %s', e)
features = fe.extractFeature(img)
words = self.km.predict(features.reshape(-1, 200))
histogram = np.bincount(words, minlength=self.vocab_size)
if normalize_histogram:
histogram = self.normalize_histogram(histogram)
hists.append(histogram)
words_1.append(words)
self.logger.debug('')
self.logger.info('Finished histogram creation')
return hists
def feature_extraction(self):
self.logger.info('Start feature extraction...')
feature_extractor = ExtractFeatures(self.feature_type)
#Feature list
all_features = []
for idx, image_name in enumerate(self.im_list):
self.logger.debug('Processing image %s, %s out of %s', image_name,
idx, len(self.im_list))
try:
img = np.array(Image.open(image_name))
except Exception as e:
self.logger('Failed to load image %s', e)
features = feature_extractor.extractFeature(img)
self.logger.debug('Feature shape %s', features.shape)
all_features.append(features.reshape(-1, 200))
self.logger.info('Finished feature extraction')
return all_features