def test_ground(self):
imgf = ImageFile(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)
class TestGrounding(unittest.TestCase):
def setUp(self):
self.img = ImageFile('digits1')
self.img.remove_ground()
self.assertFalse(self.img.is_grounded())
self.segments = ContourSegmenter().process(self.img.image)
def test_textgrounder(self):
grounder = TextGrounder()
characters = "0" * len(self.segments)
grounder.ground(self.img, self.segments, characters)
self.assertTrue(self.img.is_grounded())
self.assertEquals(reconstruct_chars(self.img.ground.classes),
characters)
def test_textgrounder_wrong_len(self):
grounder = TextGrounder()
characters = "0" * len(self.segments)
with self.assertRaises(ValueError):
grounder.ground(self.img, self.segments, characters[:-4])
self.assertFalse(self.img.is_grounded())
def test_usergrounder(self):
ESC_KEY = 27
ZERO_KEY = 48
keys = [ZERO_KEY] * len(self.segments) + [ESC_KEY]
mock_generator = iter(keys)
def mock_input(*args):
return next(mock_generator)
grounder = UserGrounder()
with mock.patch('cv2.waitKey', mock_input):
with mock.patch('cv2.imshow'):
grounder.ground(self.img, self.segments)
self.assertTrue(self.img.is_grounded())
self.assertEquals(reconstruct_chars(self.img.ground.classes),
"0" * len(self.segments))
def test_terminal_grounder(self):
terminal = TerminalGrounder()
characters = "0" * len(self.segments)
mock_input_gen = iter(characters)
def mock_input(prompt):
return next(mock_input_gen)
with mock.patch('__builtin__.raw_input', mock_input):
terminal.ground(self.img, self.segments)
self.assertTrue(self.img.is_grounded())
self.assertEquals(reconstruct_chars(self.img.ground.classes),
"0" * len(self.segments))
def test_ocr_digits(self):
# get data from images
img1 = ImageFile('digits1')
img2 = ImageFile('digits2')
ground_truth = img2.ground.classes
img2.remove_ground()
# create OCR
segmenter = ContourSegmenter()
extractor = SimpleFeatureExtractor()
classifier = KNNClassifier()
ocr = OCR(segmenter, extractor, classifier)
# train and test
ocr.train(img1)
chars, classes, _ = ocr.ocr(img2, show_steps=False)
self.assertEqual(list(classes), list(ground_truth))
self.assertEqual(chars, reconstruct_chars(ground_truth))