def test_recognize_training():
c.clear_temp()
seq = "JWP26"
# seq = 'K464J'
# Sticking together
# seq = 'WMQPQ'
# seq = '14FWX'
# seq = '4TJ3R'
# seq = '5PW9Y'
# seq = '6ML6X'
# seq = '48HXH'
# seq = 'Y581K'
# Isolation
# seq = 'QN4EL'
# Complicated
# seq = '2XML9'
# seq = 'W9WU4'
if seq:
image = dataset_manager.get_training_image(seq)
else:
seq, image = dataset_manager.get_training_image()
success, seq_r, weak_confidence = CaptchaRecognizer().recognize(
image, verbose=True, save_intermediate=True, force_partition=True
)
if success:
if weak_confidence:
print("Weak confidence")
print("Recognized is", seq_r)
print("Actual is", seq)
print("Result: {}".format(seq == seq_r))
def test_recognize_training():
c.clear_temp()
seq = 'JWP26'
# seq = 'K464J'
# Sticking together
# seq = 'WMQPQ'
# seq = '14FWX'
# seq = '4TJ3R'
# seq = '5PW9Y'
# seq = '6ML6X'
# seq = '48HXH'
# seq = 'Y581K'
# Isolation
# seq = 'QN4EL'
# Complicated
# seq = '2XML9'
# seq = 'W9WU4'
if seq:
image = dataset_manager.get_training_image(seq)
else:
seq, image = dataset_manager.get_training_image()
success, seq_r, weak_confidence = CaptchaRecognizer().recognize(
image, verbose=True, save_intermediate=True, force_partition=True)
if success:
if weak_confidence:
print('Weak confidence')
print('Recognized is', seq_r)
print('Actual is', seq)
print('Result: {}'.format(seq == seq_r))
def main():
c.clear_temp()
img = dataset_manager.get_training_image()
recognizer = captcha_recognizer.CaptchaRecognizer()
mpimg.imsave(c.temp_path('00.origin.png'), img)
# 1
img_01 = time_func(
'remove_noise_with_hsv',
lambda: recognizer.remove_noise_with_hsv(img)
)
mpimg.imsave(c.temp_path('01.hsv.png'), img_01, cmap=cm_greys)
# 2
img_02 = time_func(
'remove_noise_with_neighbors',
lambda: repeat(recognizer.remove_noise_with_neighbors, 2)(img_01)
)
mpimg.imsave(c.temp_path('02.neighbor.png'), img_02, cmap=cm_greys)
img_03a = time_func(
'skeletonize',
lambda: morph.skeletonize(img_02)
)
mpimg.imsave(c.temp_path('03a.skeleton.png'), img_03a, cmap=cm_greys)