def test_of(self):
img0 = cv2.imread(path_dir_data + 'sintel1.png')[:, :, ::-1]
img1 = cv2.imread(path_dir_data + 'sintel2.png')[:, :, ::-1]
u, v = fastdeepflow.calc_flow(img0, img1)
u1, v1 = fastdeepflow.read_flow(path_dir_data + 'sintel_cmd.flo')
self.assertTrue(numpy.allclose(u, u1, atol=1e-8))
self.assertTrue(numpy.allclose(v, v1, atol=1e-8))
def test_wrap_grayscale(self):
img0 = cv2.imread(path_dir_data + 'sintel1.png')[:, :, ::-1]
img1 = cv2.imread(path_dir_data + 'sintel2.png')[:, :, ::-1]
u, v = fastdeepflow.read_flow(path_dir_data + 'sintel_cmd.flo')
img1warped = fastdeepflow.warp_image(img1, u, v)
z = [fastdeepflow.warp_image(img1[:, :, k], u, v) for k in range(3)]
zz = numpy.dstack(z, )
self.assertTrue(numpy.allclose(img1warped, zz, atol=1e-8))
def prepare(self, dir_name, path_flow_reference):
img0 = imread(
os.path.join(path_dir_data, 'artificial/%s/img0.png' % dir_name))
img1 = imread(
os.path.join(path_dir_data, 'artificial/%s/img1.png' % dir_name))
flow_reference = fastdeepflow.read_flow(
os.path.join(path_dir_data,
('artificial/%s/' + path_flow_reference) % dir_name))
return img0, img1, flow_reference
def test_read_write(self):
path_tmp_flow = os.path.join(path_dir_data, 'flow_read_write_test.flo')
if os.path.exists(path_tmp_flow):
os.remove(path_tmp_flow)
self.assertFalse(os.path.exists(path_tmp_flow))
self.assertEqual(self.u.shape, self.v.shape)
fastdeepflow.write_flow(path_tmp_flow, self.u, self.v)
self.assertTrue(os.path.exists(path_tmp_flow))
u_loaded, v_loaded = fastdeepflow.read_flow(path_tmp_flow)
self.assertTrue(numpy.array_equal(self.u, u_loaded))
self.assertTrue(numpy.array_equal(self.v, v_loaded))
def test_read_write(self):
with self.assertRaises(Exception):
fastdeepflow.write_flow('123123/123/123123', self.u, self.v)
with self.assertRaises(Exception):
res = fastdeepflow.read_flow('123123/234234')
def setUp(self):
self.u, self.v = fastdeepflow.read_flow(path_dir_data +
'sintel_cmd.flo')
self.assertTrue(self.u.max() - self.u.min() > 5)