[FIXED] How would I convert this TensorFlow image classification model to Core ML?

Issue

I’m learning TensorFlow and want to convert an image classification model to Core ML for use in an iOS app.

This TensorFlow image classification tutorial is a close match to what I want to do for the training, but I haven’t been able to figure out how to convert that to Core ML.

Here’s what I’ve tried, adding the following to the end of the Colab notebook for the tutorial:

# install coremltools
!pip install coremltools

# import coremltools
import coremltools as ct

# define the input type
image_input = ct.ImageType()

# create classifier configuration with the class labels
classifier_config = ct.ClassifierConfig(class_names)

# perform the conversion
coreml_model = ct.convert(
    model, inputs=[image_input], classifier_config=classifier_config,
)

# print info about the converted model
print(coreml_model)

# save the file
coreml_model.save('my_coreml_model')

That successfully creates an mlmodel file, but when I download the file and open it in Xcode to test it (under the “Preview” tab) it shows results like “Roses 900% Confidence” and “Tulips 1,120% Confidence”. For my uses, the confidence percentage needs to be from 0 to 100%, so I think I’m missing some parameter for the conversion.

On import coremltools as ct I do get some warnings like “WARNING:root:TensorFlow version 2.8.2 has not been tested with coremltools. You may run into unexpected errors.” but I’m guessing that’s not the problem since the conversion doesn’t report any errors.

Based on information here, I’ve also tried setting a scale on the image input:

image_input = ct.ImageType(scale=1/255.0)

… but that made things worse as it then has around 315% confidence that every image is a dandelion. A few other attempts at setting a scale / bias all resulted in the same thing.

At this point I’m not sure what else to try. Any help is appreciated!

Solution

The last layer of your model should be something like this:

layers.Dense(num_classes, activation='softmax')

The softmax function transforms your output into the probabilities you need.

Answered By - Andrei Pascale