dca76ad8ebe547f400682f09e27d497254905d1d,models/official/detection/serving/inputs.py,,raw_image_tensor_input,#Any#Any#Any#,59

Before Change

    images_info = tf.constant([image_info_per_image], dtype=tf.float32)
    if batch_size is None:
      batch_size = tf.shape(placeholder)[0]
    images_info = tf.tile(images_info, [batch_size, 1, 1])

  images = placeholder
  return placeholder, {"images": images, "image_info": images_info}

After Change

    images_info = tf.constant([image_info_per_image], dtype=tf.float32)
  else:
    images_info = tf.constant(
        [image_info_per_image for _ in range(batch_size)],
        dtype=tf.float32)

  images = placeholder

Instances