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Eager execution coverage for image_ops_test.py. Removed run_deprecated_v1 decorators.

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Part 15 (class PSNRTest, SSIMTest)

PiperOrigin-RevId: 338354491
Change-Id: I3a447655b93c597c2c15dcb5e8c0db39b2968fb4
This commit is contained in:
Hye Soo Yang 2020-10-21 15:38:05 -07:00 committed by TensorFlower Gardener
parent c244a4a242
commit be10b788f7
1 changed files with 18 additions and 22 deletions
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40
tensorflow/python/ops/image_ops_test.py
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@ -5119,7 +5119,6 @@ class PSNRTest(test_util.TensorFlowTestCase):
"""Returns an image or image batch with given shape."""
return np.random.rand(*shape).astype(np.float32) * max_val
@test_util.run_deprecated_v1
def testPSNRSingleImage(self):
image1 = self._RandomImage((8, 8, 1), 1)
image2 = self._RandomImage((8, 8, 1), 1)
@ -5130,10 +5129,9 @@ class PSNRTest(test_util.TensorFlowTestCase):
dtype=dtypes.float32)
tf_image2 = constant_op.constant(image2, shape=image2.shape,
dtype=dtypes.float32)
tf_psnr = image_ops.psnr(tf_image1, tf_image2, 1.0, "psnr").eval()
tf_psnr = self.evaluate(image_ops.psnr(tf_image1, tf_image2, 1.0, "psnr"))
self.assertAllClose(psnr, tf_psnr, atol=0.001)
@test_util.run_deprecated_v1
def testPSNRMultiImage(self):
image1 = self._RandomImage((10, 8, 8, 1), 1)
image2 = self._RandomImage((10, 8, 8, 1), 1)
@ -5144,10 +5142,9 @@ class PSNRTest(test_util.TensorFlowTestCase):
dtype=dtypes.float32)
tf_image2 = constant_op.constant(image2, shape=image2.shape,
dtype=dtypes.float32)
tf_psnr = image_ops.psnr(tf_image1, tf_image2, 1, "psnr").eval()
tf_psnr = self.evaluate(image_ops.psnr(tf_image1, tf_image2, 1, "psnr"))
self.assertAllClose(psnr, tf_psnr, atol=0.001)
@test_util.run_deprecated_v1
def testGoldenPSNR(self):
q20, q72, q95 = self._LoadTestImages()
@ -5165,23 +5162,21 @@ class PSNRTest(test_util.TensorFlowTestCase):
tf_q20 = constant_op.constant(q20, shape=q20.shape, dtype=dtypes.float32)
tf_q72 = constant_op.constant(q72, shape=q72.shape, dtype=dtypes.float32)
tf_q95 = constant_op.constant(q95, shape=q95.shape, dtype=dtypes.float32)
tf_psnr1 = image_ops.psnr(tf_q20, tf_q72, 1, "psnr1").eval()
tf_psnr2 = image_ops.psnr(tf_q20, tf_q95, 1, "psnr2").eval()
tf_psnr3 = image_ops.psnr(tf_q72, tf_q95, 1, "psnr3").eval()
tf_psnr1 = self.evaluate(image_ops.psnr(tf_q20, tf_q72, 1, "psnr1"))
tf_psnr2 = self.evaluate(image_ops.psnr(tf_q20, tf_q95, 1, "psnr2"))
tf_psnr3 = self.evaluate(image_ops.psnr(tf_q72, tf_q95, 1, "psnr3"))
self.assertAllClose(psnr1, tf_psnr1, atol=0.001)
self.assertAllClose(psnr2, tf_psnr2, atol=0.001)
self.assertAllClose(psnr3, tf_psnr3, atol=0.001)
@test_util.run_deprecated_v1
def testInfinity(self):
q20, _, _ = self._LoadTestImages()
psnr = self._PSNR_NumPy(q20, q20, 1)
with self.cached_session(use_gpu=True):
tf_q20 = constant_op.constant(q20, shape=q20.shape, dtype=dtypes.float32)
tf_psnr = image_ops.psnr(tf_q20, tf_q20, 1, "psnr").eval()
tf_psnr = self.evaluate(image_ops.psnr(tf_q20, tf_q20, 1, "psnr"))
self.assertAllClose(psnr, tf_psnr, atol=0.001)
@test_util.run_deprecated_v1
def testInt(self):
img1 = self._RandomImage((10, 8, 8, 1), 255)
img2 = self._RandomImage((10, 8, 8, 1), 255)
@ -5193,7 +5188,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
psnr_float32 = image_ops.psnr(img1, img2, 1.0)
with self.cached_session(use_gpu=True):
self.assertAllClose(
psnr_uint8.eval(), self.evaluate(psnr_float32), atol=0.001)
self.evaluate(psnr_uint8), self.evaluate(psnr_float32), atol=0.001)
class SSIMTest(test_util.TensorFlowTestCase):
@ -5223,18 +5218,21 @@ class SSIMTest(test_util.TensorFlowTestCase):
"""Returns an image or image batch with given shape."""
return np.random.rand(*shape).astype(np.float32) * max_val
@test_util.run_deprecated_v1
def testAgainstMatlab(self):
"""Tests against values produced by Matlab."""
img = self._LoadTestImages()
expected = self._ssim[np.triu_indices(3)]
ph = [array_ops.placeholder(dtype=dtypes.float32) for _ in range(2)]
ssim = image_ops.ssim(
*ph, max_val=1.0, filter_size=11, filter_sigma=1.5, k1=0.01, k2=0.03)
def ssim_func(x):
return image_ops.ssim(
*x, max_val=1.0, filter_size=11, filter_sigma=1.5, k1=0.01, k2=0.03)
with self.cached_session(use_gpu=True):
scores = [ssim.eval(dict(zip(ph, t)))
for t in itertools.combinations_with_replacement(img, 2)]
scores = [
self.evaluate(ssim_func(t))
for t in itertools.combinations_with_replacement(img, 2)
]
self.assertAllClose(expected, np.squeeze(scores), atol=1e-4)
def testBatch(self):
@ -5292,7 +5290,6 @@ class SSIMTest(test_util.TensorFlowTestCase):
with self.cached_session(use_gpu=True):
self.assertAllClose(expected, self.evaluate(ssim), atol=1e-4)
@test_util.run_deprecated_v1
def testNegative(self):
"""Tests against negative SSIM index."""
step = np.expand_dims(np.arange(0, 256, 16, dtype=np.uint8), axis=0)
@ -5311,9 +5308,8 @@ class SSIMTest(test_util.TensorFlowTestCase):
k1=0.01,
k2=0.03)
with self.cached_session(use_gpu=True):
self.assertLess(ssim.eval(), 0)
self.assertLess(self.evaluate(ssim), 0)
@test_util.run_deprecated_v1
def testInt(self):
img1 = self._RandomImage((1, 16, 16, 3), 255)
img2 = self._RandomImage((1, 16, 16, 3), 255)
@ -5327,7 +5323,7 @@ class SSIMTest(test_util.TensorFlowTestCase):
img1, img2, 1.0, filter_size=11, filter_sigma=1.5, k1=0.01, k2=0.03)
with self.cached_session(use_gpu=True):
self.assertAllClose(
ssim_uint8.eval(), self.evaluate(ssim_float32), atol=0.001)
self.evaluate(ssim_uint8), self.evaluate(ssim_float32), atol=0.001)
class MultiscaleSSIMTest(test_util.TensorFlowTestCase):