def test_ground_unicode(self):
imgf = open_img(UNICODE_TEST_FILE)
self.assertEqual(imgf.is_grounded, True)
imgf.set_ground(imgf.ground.segments,
imgf.ground.classes,
write_file=False)
self.assertEqual(imgf.is_grounded, True)
imgf.remove_ground(remove_file=False)
self.assertEqual(imgf.is_grounded, False)
def test_opencv_brightness_raise(self):
image = open_img('digits1')
processor = opencv_utils.BrightnessProcessor(brightness=2.0)
self.assertRaises(AssertionError,
lambda: processor._process(image.image))
def test_opencv_brightness(self):
image = open_img('digits1')
processor = opencv_utils.BrightnessProcessor(brightness=0.5)
processor._process(image.image)
def setUp(self):
self.img = open_img('digits1')
self.img.remove_ground()
self.assertFalse(self.img.is_grounded)
self.segments = ContourSegmenter().process(self.img.image)
def test_open_img_inexistent(self):
with self.assertRaises(IOError):
open_img("inexistent")
def test_open_img(self):
# in data dir, no extension
open_img(TEST_FILE)
# in data dir, with extension
open_img(TEST_FILE_EXT)
# absolute path, no extension
data_dir = simpleocr.files.DATA_DIRECTORY
open_img(os.path.join(data_dir, TEST_FILE))
# absolute path, with extension
data_dir = simpleocr.files.DATA_DIRECTORY
open_img(os.path.join(data_dir, TEST_FILE_EXT))
#
data_dir_name = os.path.basename(data_dir)
old_cwd = os.getcwd()
os.chdir(os.path.dirname(data_dir)) # set cwd to one above data_dir
try:
# relative path, no extension
open_img(os.path.join(data_dir_name, TEST_FILE))
# relative path, with extension
open_img(os.path.join(data_dir_name, TEST_FILE_EXT))
finally:
os.chdir(old_cwd)
from simpleocr.files import open_img
from simpleocr.segmentation import ContourSegmenter
from simpleocr.feature_extraction import SimpleFeatureExtractor
from simpleocr.classification import KNNClassifier
from simpleocr.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(open_img('digits1'))
test_image = open_img('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)
def test_ocr_unicode(self):
self._test_ocr(open_img('unicode1'), open_img('unicode1'))
def test_ocr_digits(self):
self._test_ocr(open_img('digits1'), open_img('digits2'))