Model load_to_fb


I saved a .tflite and I am trying to store model in the cam’s frame buffer stack. However, the syntax in the documentation, tf.load(path[, load_to_fb=False]), returns a syntax error. When I use the person_detection network in the syntax, tf.load(path, load_to_fb=True), there is no error. However, with my model used as, tf.load(“fmnist.tflite”, load_to_fb=True), I get a strange error, “OSError: Input dimension [c] should be 1 or 3!” I don’t think this is an issue with my network because it was made from a google tutorial. Is there any other explanation for this?
Screenshot from 2020-07-27 17-27-26.png

It’s an error with your network.

That error is generated by this line of code here:

So, our loader noticed your model has 3 dims. Then we say the first and second channels are w and h. So, the third must be the number of channels. 1 for grayscale and 3 for rgb.

You’re network doesn’t have 1 or 3 channels. So, we don’t know how to process it then.

Note, we are using Edge Impulse to generate models for the OpenMV Cam now:

Please try using this service. It will actually generate useful networks for you that run on the camera.

MNIST is just a test example for running on the PC. It’s not really useful in real world situations.