# 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 Person Detection Example # # This example runs on the OpenMV RT1062 to detect people # using the built-in MobileNet model. import sensor import time import ml sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time=2000) model = ml.Model("/rom/person_detect.tflite") print(model) clock = time.clock() while True: clock.tick() img = sensor.snapshot() # This combines the labels and confidence values into a list of tuples # and then sorts that list by the confidence values. scores = sorted( zip(model.labels, model.predict([img])[0].flatten().tolist()), key=lambda x: x[1], reverse=True ) print(clock.fps(), "fps\t", "%s = %f\t" % (scores[0][0], scores[0][1]))