# This work is licensed under the MIT license. # Copyright (c) 2013-2024 OpenMV LLC. All rights reserved. # https://github.com/openmv/openmv/blob/master/LICENSE # # TensorFlow Lite Regression Example # # This example shows off running a regression model on the OpenMV Cam. # A regression model takes an input list of numbers and produces an # output list of numbers. You may pass ndarrays arrays to predict() # and you will get a list of the results back. # # Note: The input list of numbers must be the same size as the input # tensor size of the model. import ml from ulab import numpy as np # The model is built-in on the RT1062. On other OpenMV Cam's with limited flash space please grab # the model from here: https://github.com/openmv/openmv/tree/master/src/lib/tflm/models and # copy it to the OpenMV Cam's file system. E.g. model = ml.Model("force_int_quant.tflite") model = ml.Model("force_int_quant") print(model) i = np.array([-3, -1, -2, 5, -2, 10, -1, 9, 0, # noqa 2, 0, 9, 1, 10, 2, -1, 3, 5, # noqa 3, 9, 3, 9, 6, 2, 6, 7, 5, # noqa 10, 6, -1, 7, 4, 7, 8, 5, 7], # noqa dtype=np.int8).reshape(model.input_shape[0]) # noqa print(model.predict([i])[0]) # Should print 53.78332