def test_flow2rgb():
flow = np.array([[[0, 0], [0.5, 0.5], [1, 1], [2, 1], [3, np.inf]]],
dtype=np.float32)
flow_img = mmcv.flow2rgb(flow)
# yapf: disable
assert_array_almost_equal(
flow_img,
np.array([[[1., 1., 1.],
[1., 0.826074731, 0.683772236],
[1., 0.652149462, 0.367544472],
[1., 0.265650552, 5.96046448e-08],
[0., 0., 0.]]],
dtype=np.float32))
numpy.array(PIL.Image.open(img_second))[:, :, ::-1].transpose(
2, 0, 1).astype(numpy.float32) * (1.0 / 255.0))
tensorOutput = estimate(tensorFirst, tensorSecond)
print(arguments_strFolOut, directory_name)
outfile = os.path.join(arguments_strFolOut, '%06d.flo' % (i))
objectOutput = open(outfile, 'wb')
numpy.array([80, 73, 69, 72], numpy.uint8).tofile(objectOutput)
numpy.array([tensorOutput.size(2),
tensorOutput.size(1)],
numpy.int32).tofile(objectOutput)
numpy.array(tensorOutput.numpy().transpose(1, 2, 0),
numpy.float32).tofile(objectOutput)
objectOutput.close()
if arguments_strVisFlow:
flow = mmcv.flow2rgb(mmcv.flowread(outfile))
io.imsave(outfile[0:-3] + 'png', flow)
else:
tensorFirst = torch.FloatTensor(
numpy.array(
PIL.Image.open(arguments_strFirst))[:, :, ::-1].transpose(
2, 0, 1).astype(numpy.float32) * (1.0 / 255.0))
tensorSecond = torch.FloatTensor(
numpy.array(
PIL.Image.open(arguments_strSecond))[:, :, ::-1].transpose(
2, 0, 1).astype(numpy.float32) * (1.0 / 255.0))
tensorOutput = estimate(tensorFirst, tensorSecond)
objectOutput = open(arguments_strOut, 'wb')
