def test_freeimage():
img = np.arange(256).reshape((16,16)).astype(np.uint8)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_as_grey(tmpdir):
fname = tmpdir.join('mahotas_test.png')
colour = np.arange(16 * 16 * 3).reshape((16, 16, 3))
freeimage.imsave(fname, colour.astype(np.uint8))
c2 = freeimage.imread(fname, as_grey=True)
assert len(c2.shape) == 2
assert c2.shape == colour.shape[:-1]
def test_freeimage():
img = np.arange(256).reshape((16, 16)).astype(np.uint8)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_save_load_rgba(tmpdir):
fname = tmpdir.join('mahotas_test.png')
img = np.arange(256).reshape((8, 8, 4)).astype(np.uint8)
freeimage.imsave(fname, img)
img_ = freeimage.imread(fname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_rgba():
rgba = path.join(
path.dirname(__file__),
'data',
'rgba.png')
rgba = imread(rgba)
assert np.all(np.diff(rgba[:,:,3].mean(1)) < 0 ) # the image contains an alpha gradient
def test_uint16():
img = np.zeros((32, 32), dtype=np.uint16)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert img.dtype == img_.dtype
assert np.all(img == img_)
def test_freeimage(tmpdir):
img = np.arange(256).reshape((16, 16)).astype(np.uint8)
fname = tmpdir.join('mahotas_test.png')
freeimage.imsave(fname, img)
img_ = freeimage.imread(fname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_uint16():
img = np.zeros((32,32), dtype=np.uint16)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert img.dtype == img_.dtype
assert np.all(img == img_)
def test_1bpp():
bpp = path.join(
path.dirname(__file__),
'data',
'1bpp.bmp')
bpp = imread(bpp)
assert bpp.sum()
assert bpp.sum() < bpp.size
def test_uint16():
img = np.zeros((32, 32), dtype=np.uint16)
fname = tmpdir.join('mahotas_test.png')
freeimage.imsave(fname, img)
img_ = freeimage.imread(fname)
assert img.shape == img_.shape
assert img.dtype == img_.dtype
assert np.all(img == img_)
def test_save_load_rgba():
img = np.arange(256).reshape((8,8,4)).astype(np.uint8)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_1bpp():
bpp = path.join(path.dirname(__file__), 'data', '1bpp.bmp')
bpp = imread(bpp)
assert bpp.sum()
assert bpp.sum() < bpp.size
def test_save_load_rgba():
img = np.arange(256).reshape((8, 8, 4)).astype(np.uint8)
freeimage.imsave(_testimgname, img)
img_ = freeimage.imread(_testimgname)
assert img.shape == img_.shape
assert np.all(img == img_)
def test_rgba():
rgba = path.join(path.dirname(__file__), 'data', 'rgba.png')
rgba = imread(rgba)
assert np.all(np.diff(rgba[:, :, 3].mean(1)) <
0) # the image contains an alpha gradient
def test_as_grey():
colour = np.arange(16 * 16 * 3).reshape((16, 16, 3))
imsave(_testimgname, colour.astype(np.uint8))
c2 = imread(_testimgname, as_grey=True)
assert len(c2.shape) == 2
assert c2.shape == colour.shape[:-1]
def test_1bpp():
bpp = path.join(path.dirname(__file__), "data", "1bpp.bmp")
bpp = freeimage.imread(bpp)
assert bpp.sum()
assert bpp.sum() < bpp.size
def test_as_grey():
colour = np.arange(16*16*3).reshape((16,16,3))
imsave(_testimgname, colour.astype(np.uint8))
c2 = imread(_testimgname, as_grey=True)
assert len(c2.shape) == 2
assert c2.shape == colour.shape[:-1]
