How to pass base64 encoded image to Tensorflow prediction?

Question

I have a google-cloud-ml model that I can run prediction by passing a 3 dimensional array of float32...

{ \'instances\' [ { \'input\' : \'[ [ [ 0.0 ], [ 0.5 ],

Answer 1

The TensorFlow model does not have to be trained on base64 data. Leave your training graph as is. However, when exporting the model, you'll need to export a model that can accept png or jpeg (or possibly raw, if it's small) data. Then, when you export the model, you'll need to be sure to use a name for the output that ends in _bytes. This signals to CloudML Engine that you will be sending base64 encoded data. Putting it all together would like something like this:

from tensorflow.contrib.saved_model.python.saved_model import utils

# Shape of [None] means we can have a batch of images.
image = tf.placeholder(shape=[None], dtype=tf.string)
# Decode the image.
decoded = tf.image.decode_jpeg(image, channels=3)
# Do the rest of the processing.
scores = build_model(decoded)

# The input name needs to have "_bytes" suffix.
inputs = {'image_bytes': image}
outputs = {'scores': scores}
utils.simple_save(session, export_dir, inputs, outputs)

The request you send will look something like this:

{"instances": [{"b64": "x0welkja..."}]}