def test_get_data(self):
# given
test_data = np.random.randint(0, 2**16 -1, (512, 512))
im = ImageModel(
color_depth=1,
data=test_data,
height=test_data.shape[0],
width=test_data.shape[1],
)
# when
result = im.get_data()
result_t = im.get_data(transpose=True)
# then
assert result is im.data
assert_array_equal(result_t, np.transpose(im.data))
def gen_test_model_random2D():
test_data = np.random.randint(0, 2**16 -1, (512, 512)).astype(np.int64)
return ImageModel(
color_depth=1,
data=test_data,
height=test_data.shape[0],
width=test_data.shape[1],
)
def gen_test_model_random3D_RGBA():
# 250 512x512 images stored in RGBA ---> 250x4=1000
# Total array size (512, 512, 1000)
test_data = np.random.randint(0,
2**16 -1,
(512, 512, 1000)).astype(np.int64)
return ImageModel(
color_depth=4,
data=test_data,
height=test_data.shape[0],
width=test_data.shape[1],
)
def test_image_creation(self):
# given
test_data = np.random.randint(0, 2**16 - 1, (512, 512))
# when
im = ImageModel(
color_depth=1,
data=test_data,
height=test_data.shape[0],
width=test_data.shape[1],
)
# then
assert isinstance(im.data, np.ndarray)
assert im.height == im.data.shape[0]
assert im.width == im.data.shape[1]
def test_get_current_image(self):
# given
test_data = np.random.randint(0, 2**16 - 1, (512, 512, 250))
index = random.randint(0, test_data.shape[2] - 1)
ims = ImageStack(
color_depth=1,
current_image_index=0,
data=test_data,
depth=test_data.shape[2],
height=test_data.shape[0],
width=test_data.shape[1],
)
# when
ims.current_image = ImageModel(
color_depth=1,
data=test_data[:, :, index],
height=test_data.shape[0],
width=test_data.shape[1],
)
# then
assert_array_equal(ims.get_current_image(), ims.current_image)
def load_image_from_file_PIL(path):
""" Generate ImageModel from file using PIL.Image.open()."""
try:
im = Image.open(path)
except:
# TODO fill in appropriate I/O errors
pass
data = np.array(im)
# print("Loaded Data: shape - {} ndim - {}".format(data.shape, data.ndim))
if data.ndim == 2:
cd = 1 # greyscale
elif data.ndim == 3 and data.shape[2] == 3:
cd = 3 # RGB
elif data.ndim == 3 and data.shape[2] == 4:
cd = 4 # RGBA or ARGB
else:
# TODO: Handle invalid ndim
return None
return ImageModel(color_depth=cd,
data=data,
height=data.shape[0],
width=data.shape[1])