I am trying to convert a model I found on TensorFlow hub to CoreML so I can use it in an iOS app I'm developing. Converting the model so far has been quite simple except that I get an NotImplementedError when specifying ImageType as output.
This is the code I used:
model = tf.keras.Sequential([
tf.keras.layers.InputLayer(input_shape=(256, 256, 3)),
tf_hub.KerasLayer(
"https://tfhub.dev/rishit-dagli/mirnet-tfjs/1"
)
])
model.build([1, 256, 256, 3]) # Batch input shape.
mlmodel = ct.convert(model, convert_to="mlprogram",
inputs=[ct.ImageType()], outputs=[ct.ImageType()])
If only the inputs are specified as ImageType, then no error occurs, but when I include a specification for the outputs as ImageType, I get this error:
NotImplementedError: Image output 'Identity' has symbolic dimensions in its shape
FYI: I'm using TensorFlow version 2.12 and CoreML 6.3
Is there any way around this? Or, am I doing this wrong?
I'm quite new to machine learning and CoreML, so any helpful input is much appreciated. Thanks in advance!