def test_numpy_batch_ch(data_format):
if data_format == "nhwc":
X = np.random.randn(5,100,100,4)
else:
X = np.random.randn(5,4,100,100)
f = Transform2d()
p = f.forward_channels(X, data_format=data_format, include_scale=True)
f1 = Transform2d_np()
for i in range(5):
for j in range(4):
if data_format == "nhwc":
p1 = f1.forward(X[i,:,:,j], include_scale=True)
np.testing.assert_array_almost_equal(
p.lowpass[i,:,:,j], p1.lowpass, decimal=PRECISION_DECIMAL)
for x,y in zip(p.highpasses, p1.highpasses):
np.testing.assert_array_almost_equal(
x[i,:,:,j], y, decimal=PRECISION_DECIMAL)
for x,y in zip(p.scales, p1.scales):
np.testing.assert_array_almost_equal(
x[i,:,:,j], y, decimal=PRECISION_DECIMAL)
else:
p1 = f1.forward(X[i,j], include_scale=True)
np.testing.assert_array_almost_equal(
p.lowpass[i,j], p1.lowpass, decimal=PRECISION_DECIMAL)
for x,y in zip(p.highpasses, p1.highpasses):
np.testing.assert_array_almost_equal(
x[i,j], y, decimal=PRECISION_DECIMAL)
for x,y in zip(p.scales, p1.scales):
np.testing.assert_array_almost_equal(
x[i,j], y, decimal=PRECISION_DECIMAL)
def test_results_match_invmask(biort,qshift,gain_mask):
im = mandrill
f_np = Transform2d_np(biort=biort, qshift=qshift)
p_np = f_np.forward(im, nlevels=4, include_scale=True)
X_np = f_np.inverse(p_np, gain_mask)
f_tf = Transform2d(biort=biort, qshift=qshift)
p_tf = f_tf.forward(im, nlevels=4, include_scale=True)
X_tf = f_tf.inverse(p_tf, gain_mask)
np.testing.assert_array_almost_equal(
X_np, X_tf, decimal=PRECISION_DECIMAL)
def test_results_match_endtoend(test_input, biort, qshift):
im = test_input
f_np = Transform2d_np(biort=biort, qshift=qshift)
p_np = f_np.forward(im, nlevels=4, include_scale=True)
X_np = f_np.inverse(p_np)
in_p = tf.placeholder(tf.float32, [im.shape[0], im.shape[1]])
f_tf = Transform2d(biort=biort, qshift=qshift)
p_tf = f_tf.forward(in_p, nlevels=4, include_scale=True)
X = f_tf.inverse(p_tf)
with tf.Session() as sess:
X_tf = sess.run(X, feed_dict={in_p: im})
np.testing.assert_array_almost_equal(
X_np, X_tf, decimal=PRECISION_DECIMAL)
def test_results_match_inverse(test_input,biort,qshift):
im = test_input
f_np = Transform2d_np(biort=biort, qshift=qshift)
p_np = f_np.forward(im, nlevels=4, include_scale=True)
X_np = f_np.inverse(p_np)
# Use a zero input and the fwd transform to get the shape of
# the pyramid easily
f_tf = Transform2d(biort=biort, qshift=qshift)
p_tf = f_tf.forward(im, nlevels=4, include_scale=True)
# Create ops for the inverse transform
X_tf = f_tf.inverse(p_tf)
np.testing.assert_array_almost_equal(
X_np, X_tf, decimal=PRECISION_DECIMAL)
def test_results_match(test_input, biort, qshift):
"""
Compare forward transform with numpy forward transform for mandrill image
"""
im = test_input
f_np = Transform2d_np(biort=biort,qshift=qshift)
p_np = f_np.forward(im, include_scale=True)
f_tf = Transform2d(biort=biort,qshift=qshift)
p_tf = f_tf.forward(im, include_scale=True)
np.testing.assert_array_almost_equal(
p_np.lowpass, p_tf.lowpass, decimal=PRECISION_DECIMAL)
[np.testing.assert_array_almost_equal(
h_np, h_tf, decimal=PRECISION_DECIMAL) for h_np, h_tf in
zip(p_np.highpasses, p_tf.highpasses)]
[np.testing.assert_array_almost_equal(
s_np, s_tf, decimal=PRECISION_DECIMAL) for s_np, s_tf in
zip(p_np.scales, p_tf.scales)]
def test_numpy_in():
X = np.random.randn(100,100)
f = Transform2d()
p = f.forward(X)
f1 = Transform2d_np()
p1 = f1.forward(X)
np.testing.assert_array_almost_equal(
p.lowpass, p1.lowpass, decimal=PRECISION_DECIMAL)
for x,y in zip(p.highpasses, p1.highpasses):
np.testing.assert_array_almost_equal(x,y,decimal=PRECISION_DECIMAL)
X = np.random.randn(100,100)
p = f.forward(X, include_scale=True)
p1 = f1.forward(X, include_scale=True)
np.testing.assert_array_almost_equal(
p.lowpass, p1.lowpass, decimal=PRECISION_DECIMAL)
for x,y in zip(p.highpasses, p1.highpasses):
np.testing.assert_array_almost_equal(x,y,decimal=PRECISION_DECIMAL)
for x,y in zip(p.scales, p1.scales):
np.testing.assert_array_almost_equal(x,y,decimal=PRECISION_DECIMAL)
def __init__(self, biort='near_sym_a', qshift='qshift_a'):
self.xfm = Transform2d_np(biort, qshift)