def test_flow_warp():
img = np.zeros((5, 5, 3))
img[2, 2, 0] = 1
flow = np.ones((5, 5, 2))
res_nn = mmcv.flow_warp(img, flow, interpolate_mode='nearest')
res_bi = mmcv.flow_warp(img, flow, interpolate_mode='bilinear')
assert_array_almost_equal(res_nn, res_bi, decimal=5)
img = np.zeros((5, 5, 1))
img[2, 2, 0] = 1
img[2, 3, 0] = 0.75
flow = np.zeros((5, 5, 2))
flow[2, 2, :] = [0.5, 0.7]
res_ = np.copy(img)
res_[2, 2] = 0.5 * 0.3 + 0.75 * 0.5 * 0.3
res_bi = mmcv.flow_warp(img, flow, interpolate_mode='bilinear')
assert_array_almost_equal(res_, res_bi, decimal=5)
with pytest.raises(NotImplementedError):
_ = mmcv.flow_warp(img, flow, interpolate_mode='xxx')
with pytest.raises(AssertionError):
_ = mmcv.flow_warp(img, flow[:, :, 0], interpolate_mode='xxx')
def test_flow_warp():
def np_flow_warp(flow, img):
output = np.zeros_like(img, dtype=img.dtype)
height = flow.shape[0]
width = flow.shape[1]
grid = np.indices((height, width)).swapaxes(0, 1).swapaxes(1, 2)
dx = grid[:, :, 0] + flow[:, :, 1]
dy = grid[:, :, 1] + flow[:, :, 0]
sx = np.floor(dx).astype(int)
sy = np.floor(dy).astype(int)
valid = (sx >= 0) & (sx < height - 1) & (sy >= 0) & (sy < width - 1)
output[valid, :] = img[dx[valid].round().astype(int),
dy[valid].round().astype(int), :]
return output
dim = 500
a = np.random.randn(dim, dim, 3) * 10 + 125
b = np.random.randn(dim, dim, 2) + 2 + 0.2
c = mmcv.flow_warp(a, b, interpolate_mode='nearest')
d = np_flow_warp(b, a)
simple_a = np.zeros((5, 5, 3))
simple_a[2, 2, 0] = 1
simple_b = np.ones((5, 5, 2))
simple_res_c = np.zeros((5, 5, 3))
simple_res_c[1, 1, 0] = 1
res_c = mmcv.flow_warp(simple_a, simple_b, interpolate_mode='bilinear')
assert_array_equal(c, d)
assert_array_equal(res_c, simple_res_c)