def test_warp_car():
flow = M.KITTI.open_flow(TEST_PNG16_FILE)
car = M.open_png16('./data/kitti_car/c_11.png')
flow = flow.reshape([1, *flow.shape])
car = car.reshape([1, *car.shape])
car_bar = M.warp(car, flow[..., 0], flow[..., 1], True)
with tf.Session() as sess:
car_bar = sess.run(car_bar)[0]
car_bar = car_bar.astype('uint8')
def test_warp_chair():
flow = M.open_flo(TEST_FLO_FILE)
img1 = Image.open('./data/flying_chair/pair/0000/img1.png')
ch0 = np.array(img1).astype('float32')
flow = flow.reshape([1, *flow.shape])
ch0 = np.expand_dims(ch0, 0)
ch1 = M.warp(ch0, flow[..., 0], flow[..., 1], True)
with tf.Session() as sess:
ch1 = sess.run(ch1)[0]
ch1 = ch1.astype('uint8')
def test_grid():
G = np.meshgrid(range(5), range(5))
G = np.stack(G, -1)
G_bar = M._grid(5, 5)[0]
with tf.Session() as sess:
G_bar = sess.run(G_bar)
assert np.all(G == G_bar.transpose([1, 0, 2]))
def test_sample():
G = np.meshgrid(range(5), range(5))
G = np.stack(G, -1)
G = np.expand_dims(G, 0)
G.transpose([0, 2, 1, 3])
X = np.random.rand(1, 5, 5, 3).astype('float32')
X_bar = M._sample(X, G[..., 0], G[..., 1])
with tf.Session() as sess:
X_bar = sess.run(X_bar)
assert np.all(X == X_bar)
def test_open_png16():
X = M.open_png16(TEST_PNG16_FILE)
assert X.shape == (375, 1242, 3)
def test_open_flo():
X = M.open_flo(TEST_FLO_FILE)
assert X.shape == (384, 512, 2)