from segmentation import ContourSegmenter, draw_segments
from feature_extraction import SimpleFeatureExtractor
from classification import KNNClassifier
from ocr import OCR, accuracy, show_differences, reconstruct_chars
segmenter= ContourSegmenter( blur_y=5, blur_x=5, block_size=11, c=10)
extractor= SimpleFeatureExtractor( feature_size=10, stretch=False )
classifier= KNNClassifier()
ocr= OCR( segmenter, extractor, classifier )
ocr.train( ImageFile('digits1') )
test_image= ImageFile('digits2')
test_classes, test_segments= ocr.ocr( test_image, show_steps=True )
print "accuracy:", accuracy( test_image.ground.classes, test_classes )
print "OCRed text:\n", reconstruct_chars( test_classes )
show_differences( test_image.image, test_segments, test_image.ground.classes, test_classes)
########NEW FILE########
__FILENAME__ = feature_extraction
import numpy
import cv2
from segmentation import region_from_segment
from opencv_utils import background_color
FEATURE_DATATYPE= numpy.float32
#FEATURE_SIZE is defined on the specific feature extractor instance
FEATURE_DIRECTION= 1 #horizontal - a COLUMN feature vector
FEATURES_DIRECTION= 0 # vertical - ROWS of feature vectors
from files import ImageFile
from segmentation import ContourSegmenter
from feature_extraction import SimpleFeatureExtractor
from classification import KNNClassifier
from ocr import OCR, accuracy, show_differences
segmenter = ContourSegmenter(blur_y=5, blur_x=5, block_size=11, c=10)
extractor = SimpleFeatureExtractor(feature_size=10, stretch=False)
classifier = KNNClassifier()
ocr = OCR(segmenter, extractor, classifier)
ocr.train(ImageFile('digits1'))
test_image = ImageFile('digits2')
test_chars, test_classes, test_segments = ocr.ocr(test_image, show_steps=True)
print("accuracy:", accuracy(test_image.ground.classes, test_classes))
print("OCRed text:\n", test_chars)