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