def testGifSummary(self):
for c in (1, 3):
images_shape = (1, 12, 48, 64, c) # batch, time, height, width, channels
images = np.random.randint(256, size=images_shape).astype(np.uint8)
with self.test_session():
summary = common_video.gif_summary(
"gif", tf.convert_to_tensor(images), fps=10)
summary_string = summary.eval()
summary = tf.Summary()
summary.ParseFromString(summary_string)
self.assertEqual(1, len(summary.value))
self.assertTrue(summary.value[0].HasField("image"))
encoded = summary.value[0].image.encoded_image_string
self.assertEqual(encoded, common_video._encode_gif(images[0], fps=10)) # pylint: disable=protected-access
def testGifSummary(self):
for c in (1, 3):
images_shape = (1, 12, 48, 64, c) # batch, time, height, width, channels
images = np.random.randint(256, size=images_shape).astype(np.uint8)
with self.test_session():
summary = common_video.gif_summary(
"gif", tf.convert_to_tensor(images), fps=10)
summary_string = summary.eval()
summary = tf.Summary()
summary.ParseFromString(summary_string)
self.assertEqual(1, len(summary.value))
self.assertTrue(summary.value[0].HasField("image"))
encoded = summary.value[0].image.encoded_image_string
self.assertEqual(encoded, common_video._encode_gif(images[0], fps=10)) # pylint: disable=protected-access