蜂鸣器是有源的3.3V

import time
from machine import Pin
#from ulab import numpy as np

buzzer = Pin("P0", Pin.OUT)

while True:
    buzzer.high()
    time.sleep(2)
    buzzer.low()

固件版本是4.5.9 IDE版本4.0.14

# Edge Impulse - OpenMV Image Classification Example
#
# 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

import sensor, image, time, os, uos, gc, ml
from ulab import numpy as np

sensor.reset()                         # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565)    # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA)      # Set frame size to QVGA (320x240)
sensor.set_windowing((240, 240))       # Set 240x240 window.
sensor.skip_frames(time=2000)          # Let the camera adjust.

net = None
labels = None

try:
    # load the model, alloc the model file on the heap if we have at least 64K free after loading
    net = ml.Model("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
except Exception as e:
    print(e)
    raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

try:
    labels = [line.rstrip('\n') for line in open("labels.txt")]
except Exception as e:
    raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

clock = time.clock()
while(True):
    clock.tick()

    img = sensor.snapshot()

    predictions_list = list(zip(labels, net.predict([img])[0].flatten().tolist()))

    for i in range(len(predictions_list)):
        print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))

    print(clock.fps(), "fps")
![0_1730909218195_捕获.PNG](https://fcdn.singtown.com/c5ff1923-0088-410f-8abb-f71c6211c5a2.PNG)