def test_crop_rescale_img():
from .pipeline_aux import crop_rescale_img
from menpo.image import Image
import numpy as np
from menpo.shape import PointCloud
test_img = Image(np.random.random([100, 100]))
test_img.landmarks['PT'] = PointCloud([[20, 20], [20, 40], [40, 80], [40, 20]])
res_im = crop_rescale_img(test_img.copy()) # crop image and check reduced shapes
assert(res_im.shape[0] < test_img.shape[0])
assert(res_im.shape[1] < test_img.shape[1])
res_im2 = crop_rescale_img(test_img.copy(), crop_reading=1, pix_thres=40) # check pixel threshold
assert(res_im2.shape[0] < test_img.shape[0])
res_im3 = crop_rescale_img(test_img.copy(), crop_reading=1, pix_thres=400) # test that the image remains the same
assert(res_im3.shape[1] > test_img.shape[1]-3)
def test_image_copy():
pixels = np.ones([1, 10, 10])
landmarks = PointCloud(np.ones([3, 2]), copy=False)
im = Image(pixels, copy=False)
im.landmarks['test'] = landmarks
im_copy = im.copy()
assert (not is_same_array(im.pixels, im_copy.pixels))
assert (not is_same_array(im_copy.landmarks['test'].points,
im.landmarks['test'].points))
def test_crop_rescale_img():
from .pipeline_aux import crop_rescale_img
from menpo.image import Image
import numpy as np
from menpo.shape import PointCloud
test_img = Image(np.random.random([100, 100]))
test_img.landmarks['PT'] = PointCloud([[20, 20], [20, 40], [40, 80],
[40, 20]])
res_im = crop_rescale_img(
test_img.copy()) # crop image and check reduced shapes
assert (res_im.shape[0] < test_img.shape[0])
assert (res_im.shape[1] < test_img.shape[1])
res_im2 = crop_rescale_img(test_img.copy(), crop_reading=1,
pix_thres=40) # check pixel threshold
assert (res_im2.shape[0] < test_img.shape[0])
res_im3 = crop_rescale_img(
test_img.copy(), crop_reading=1,
pix_thres=400) # test that the image remains the same
assert (res_im3.shape[1] > test_img.shape[1] - 3)
