Is the input of `tf.image.resize_images` must have static shape?

Question

I run the code below, it raises an ValueError: \'images\' contains no shape. Therefore I have to add the line behind # to set the static shape, but

Answer 1

Of course you can use tensor object as size input for tf.image.resize_images.

So, by saying "turn images with different shapes to [227,227,3]", I suppose you don't want to lose their aspect ratio, right? To achieve this, you have to rescale the input image first, then pad the rest with zero.

It should be noted, though, you should consider perform image distortion and standardization before padding it.

# Rescale so that one side of image can fit one side of the box size, then padding the rest with zeros.
# target height is 227
# target width is 227
image = a_image_tensor_you_read
shape = tf.shape(image)
img_h = shape[0]
img_w = shape[1]
box_h = tf.convert_to_tensor(target_height)
box_w = tf.convert_to_tensor(target_width)
img_ratio = tf.cast(tf.divide(img_h, img_w), tf.float32)
aim_ratio = tf.convert_to_tensor(box_h / box_w, tf.float32)
aim_h, aim_w = tf.cond(tf.greater(img_ratio, aim_ratio),
                       lambda: (box_h,
                                tf.cast(img_h / box_h * img_w, tf.int32)),
                       lambda: (tf.cast(img_w / box_w * img_h, tf.int32),
                                box_w))
image_resize = tf.image.resize_images(image, tf.cast([aim_h, aim_w], tf.int32), align_corners=True)

# Perform image standardization and distortion
image_standardized_distorted = blablabla

image_padded = tf.image.resize_image_with_crop_or_pad(image_standardized_distorted, box_h, box_w)
return image_padded