def classify(k, classifier_path, image):
im = Image.open(image)
e = Extractor(im)
start = datetime.datetime.now()
print '#' * 37 + ' DATA ' + '#' * 37
for s_im in e:
if (Extractor.is_whitespace(s_im)):
print s_im,
else:
classify_digit(k, classifier_path, s_im)
print '#' * 80
end = datetime.datetime.now()
print '### TIME: {} sec###'.format((end - start).total_seconds())
def train(classifier_path, image_path):
"""Train the classifier with an image.
This method extract digits from the image, then prompts the user
to classify the image. That classification is stored in the following format:
Digit: [classification]
File: [image taken from]
[PIXEL DATA]
@
Args:
classifier_path (String): path to the file holding the classifier data
image_path (String): path to the image to train on
"""
# open the classifier file
with open(classifier_path, "a+") as f:
# open the image
im_name = os.path.basename(image_path)
im = Image.open(image_path)
# create an Extractor
e = Extractor(im)
# iterate over the SimpleImages extracted
for s_im in e:
# chack that it isn't whitespace
if (not Extractor.is_whitespace(s_im)):
# print the image and have the user classify it
print s_im
digit = input("Input value ('s' to skip): ")
# skip this digit
if (digit == 's'):
continue
# write the data to the file
f.write(CLASSIFIER_FORMAT.format(digit, im_name, str(s_im)))