def test_defaults():
path = 'mlxtend/image/tests/data/'
eyepad = EyepadAlign()
target_image = imageio.imread(
os.path.join(path, 'celeba-subset/000001.jpg'))
eyepad.fit_image(target_image)
img = imageio.imread(os.path.join(path, 'lena-small.png'))
img_tr = eyepad.transform(img)
landmarks_tr = extract_face_landmarks(img_tr)
true_vals = np.array(
[[35, 113], [33, 126], [34, 140], [36, 154], [41, 166], [51, 176],
[61, 184], [72, 189], [82, 190], [90, 186]],
dtype=np.int32)
if os.name == 'nt':
# on windows, imageio parses jpgs sometimes differently so pixel values
# maybe slightly different
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 2) == 0
else:
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0) == 0, \
np.sum(np.abs(landmarks_tr[:10] - true_vals))
np.testing.assert_array_equal(landmarks_tr[:10], true_vals)
def test_fit2dir():
path = 'mlxtend/image/tests/data/'
eyepad = EyepadAlign()
eyepad.fit_directory(target_img_dir=os.path.join(path, 'celeba-subset/'),
target_width=178,
target_height=218,
file_extension='.jpg')
img = imageio.imread(os.path.join(path, 'lena-small.png'))
img_tr = eyepad.transform(img)
landmarks_tr = extract_face_landmarks(img_tr)
true_vals = np.array(
[[30, 115], [28, 130], [29, 145], [31, 160], [38, 173], [48, 182],
[59, 191], [71, 196], [82, 197], [90, 193]],
dtype=np.int32)
if os.name == 'nt':
# on windows, imageio parses jpgs sometimes differently so pixel values
# maybe slightly different
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 3) == 0
else:
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0) == 0, \
np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0)
np.testing.assert_array_equal(landmarks_tr[:10], true_vals)
def test_fit2dir():
path = 'mlxtend/image/tests/data/'
eyepad = EyepadAlign()
eyepad.fit_directory(target_img_dir=os.path.join(path, 'celeba-subset/'),
target_width=178,
target_height=218,
file_extension='.jpg')
img = imageio.imread(os.path.join(path, 'lena-small.png'))
img_tr = eyepad.transform(img)
landmarks_tr = extract_face_landmarks(img_tr)
true_vals = np.array([[30, 115],
[28, 130],
[29, 145],
[31, 160],
[38, 173],
[48, 182],
[59, 191],
[71, 196],
[82, 197],
[90, 193]], dtype=np.int32)
if os.name == 'nt':
# on windows, imageio parses jpgs sometimes differently so pixel values
# maybe slightly different
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 3) == 0
else:
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0) == 0, \
np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0)
np.testing.assert_array_equal(landmarks_tr[:10], true_vals)
def test_defaults():
path = 'mlxtend/image/tests/data/'
eyepad = EyepadAlign()
target_image = imageio.imread(os.path.join(path,
'celeba-subset/000001.jpg'))
eyepad.fit_image(target_image)
img = imageio.imread(os.path.join(path, 'lena-small.png'))
img_tr = eyepad.transform(img)
landmarks_tr = extract_face_landmarks(img_tr)
true_vals = np.array([[35, 113],
[33, 126],
[34, 140],
[36, 154],
[41, 166],
[51, 176],
[61, 184],
[72, 189],
[82, 190],
[90, 186]], dtype=np.int32)
if os.name == 'nt':
# on windows, imageio parses jpgs sometimes differently so pixel values
# maybe slightly different
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 2) == 0
else:
assert np.sum(np.abs(landmarks_tr[:10] - true_vals) > 0) == 0, \
np.sum(np.abs(landmarks_tr[:10] - true_vals))
np.testing.assert_array_equal(landmarks_tr[:10], true_vals)
def test_empty_dir():
path = 'mlxtend/image/tests/data/'
eyepad = EyepadAlign()
def tmp_func():
eyepad.fit_directory(target_img_dir=os.path.join(path,
'celeba-subset/'),
target_width=178,
target_height=218,
file_extension='.PNG')
assert_raises(ValueError, tmp_func)
import imageio
from mlxtend.image import EyepadAlign
### Fit EyepadAlign on a single target image
eyepad = EyepadAlign()
target_image = imageio.imread('celeba-subset/000001.jpg')
print('Target image shape: ', target_image.shape)
eyepad.fit_image(target_image);
import imageio
import os
import numpy as np
from mlxtend.image import EyepadAlign
import pyprind
morph_orig_dir = 'morph2-unaligned'
morph_aligned_dir = 'morph2-aligned'
# Get average image
eyepad = EyepadAlign(verbose=1)
eyepad.fit_directory(target_img_dir=morph_orig_dir,
target_width=200,
target_height=240,
file_extension='.JPG') # note the capital letters
# Center nose of the average image
nose_coord = eyepad.target_landmarks_[33].copy()
disp_vec = np.array([100, 120]) - nose_coord
translated_shape = eyepad.target_landmarks_ + disp_vec
eyepad_centnoise = EyepadAlign(verbose=1)
eyepad_centnoise.fit_values(target_landmarks=translated_shape,
target_width=200,
target_height=240)
# Align images to centered average image
flist = [f for f in os.listdir(morph_orig_dir) if f.endswith('.JPG')]
pbar = pyprind.ProgBar(len(flist), title='Aligning images ...')