def test_to_float_unknown_dtype():
img = np.ones((100, 100, 3), dtype=np.int16)
with pytest.raises(RuntimeError) as exc_info:
F.to_float(img)
assert str(exc_info.value) == (
"Can't infer the maximum value for dtype int16. You need to specify the maximum value manually by passing "
"the max_value argument")
def test_no_resize_pad():
mask = AF.to_float(
cv2.imread('data/train/masks/0b73b427d1.png', cv2.IMREAD_GRAYSCALE))
processor = D.DatasetResizePad(101,
128,
border_mode=cv2.BORDER_REFLECT101,
interpolation=cv2.INTER_LINEAR)
mask_pad = processor.forward(image=mask, mask=mask)['image']
mask_torch = torch.from_numpy(mask_pad).unsqueeze(0).unsqueeze(0).float()
mask_back = processor.backward(mask_torch).numpy().squeeze()
f, ax = plt.subplots(3, 1, figsize=(12, 20))
f.suptitle('test_resize_pad', fontsize=16)
ax[0].imshow(mask)
ax[1].imshow(mask_pad)
ax[2].imshow(mask_back)
f.tight_layout()
f.subplots_adjust(top=0.88)
f.show()
assert np.allclose(mask, mask_back)
def test_to_float_unknown_dtype_with_max_value(max_value):
img = np.ones((100, 100, 3), dtype=np.int16)
expected = img.astype("float32") / max_value
assert_array_almost_equal_nulp(F.to_float(img, max_value=max_value),
expected)
def test_to_float_without_max_value_specified(dtype, divider):
img = np.ones((100, 100, 3), dtype=dtype)
expected = img.astype("float32") / divider
assert_array_almost_equal_nulp(F.to_float(img), expected)
def test_to_float_with_max_value_specified(max_value):
img = np.ones((100, 100, 3), dtype=np.uint16)
expected = img.astype('float32') / max_value
assert_array_almost_equal_nulp(F.to_float(img, max_value=max_value),
expected)
