I want to create an image classification model for facial recognition with a OpenMV Cam H7 and tensorflow. It's explained in the tensorflow documentation that "TensorFlow Lite for Microcontrollers currently supports a limited subset of TensorFlow operations, which impacts the model architectures that it is possible to run"
"The supported operations can be seen in the file all_ops_resolver.cc"
so what are supported operations?, and how do I know which supported operations I'm using in my model
If you open the link to the all_ops_resolver.cc file you just shared you will be able to see the list of supported operations. The list includes the basic building blocks needed to design a facial recognition model, like the layers Conv2D/DepthwiseConv2D and FullyConnected, and activations as Relu and Softmax.
To see the layers being used in a model you can just call model.summary() in Tensorflow/Keras.
I recommend you to start by looking for a simple Tensorflow example showing how to build a face recognition model and try to build a similar one just using operations supported by Tensorflow-lite for Microcontrollers.
