def generate_sprite(self, example_strings):
# Generate a sprite image for the examples if the examples contain the
# standard encoded image feature.
feature_list = (self.examples[0].features.feature
if self.example_class == tf.train.Example else
self.examples[0].context.feature)
self.sprite = (inference_utils.create_sprite_image(example_strings) if
(len(self.examples)
and self.image_feature_name in feature_list) else None)
def create_sprite(self):
"""Returns an encoded image of thumbnails for image examples."""
# Generate a sprite image for the examples if the examples contain the
# standard encoded image feature.
if not self.examples:
return None
example_to_check = self.json_to_proto(self.examples[0])
feature_list = (example_to_check.context.feature
if self.config.get('are_sequence_examples')
else example_to_check.features.feature)
if 'image/encoded' in feature_list:
example_strings = [
self.json_to_proto(ex).SerializeToString()
for ex in self.examples]
encoded = ensure_str(base64.b64encode(
inference_utils.create_sprite_image(example_strings)))
return 'data:image/png;base64,{}'.format(encoded)
else:
return None