def test_alignment(self):
"""
Tests if the ImageSet info is correct except the image, as this is a little unpredictable
"""
rand_im = (np.random.rand(225, 225, 4) * 255).astype(np.uint8)
rand_im[:, :, -1] = 1
input_im = np.zeros((4,) + rand_im.shape, dtype=np.uint8)
for i in range(0, input_im.shape[0]):
input_im[i] = rand_im
input_im[1, :-2, :] = input_im[1, 2:, :]
input_im[1, -3:, :] = 0
input_im[3] = np.rot90(input_im[3])
input_im_set = ImageSet(input_im)
input_im_set.original_shape = input_im.shape[1:]
input_im_set.shutter_speed = np.array([1, 2, 3, 4])
expected_im_set = ImageSet(input_im) # ignoring the returned image here
expected_im_set.original_shape = (222, 222, 4)
expected_im_set.shutter_speed = input_im_set.shutter_speed.copy()
output_image_set = input_im_set.aligned_image_set()
self.assertEqual(expected_im_set.original_shape, output_image_set.original_shape)
self.assertTrue(np.array_equal(expected_im_set.shutter_speed, output_image_set.shutter_speed))
def random_image_set(x, y, colors, n):
"""
Creates a image set
:param x: The width of the image
:param y: The height of the image
:param colors: IF the image needs colors
:param n: The number of images
:return: A ImageSet
"""
max_value = 255
rand_im = np.random.rand(x, y)
exposure_im = np.zeros((n, x, y), dtype=int)
if colors:
rand_im = np.random.rand(x, y, 3)
exposure_im = np.zeros((n, x, y, 3), dtype=int)
rand_im = rand_im
exposures = np.zeros(n)
for i in range(1, n + 1):
exposure_im[i - 1] = (rand_im * max_value * 2**(i - 1)).astype(int)
exposure_im[i - 1][exposure_im[i - 1] > max_value] = max_value
exposures[i - 1] = 2**(i - 1)
im_set = ImageSet(exposure_im)
im_set.shutter_speed = np.log(exposures)
im_set.original_shape = rand_im.shape
return rand_im, im_set
def test_gray_images(self):
"""
Tests ImageSet.gray_images()
"""
image = np.array([[[ # One image with shape (1, 3, 3)
[1, 2, 3], [2, 3, 4], [100, 100, 100]
]]])
image_set = ImageSet(image)
image_set.original_shape = (1, 3, 3)
image_set.shutter_speed = [1]
expected_image = np.array([[ # Shape (1, 3)
2, 3, 100
]]).astype(float)
output = image_set.gray_images()
self.assertTrue(np.array_equal(output.images[0], expected_image))
