nga5 发布的帖子

@kidswong999 如果我想把识别的结果发送到去其他单片机用串口怎么做，希望提供相关代码参考

通过语音指令控制0号舵机转90度1号舵机转180度

想通过语音指令控制舵机工作，不知道用什么型号，不知道具体怎么加入.

@kidswong999 为什么显示未定义

为什么报错，求解答

@kidswong999 为什么我的显示伺服未定义，我需要怎么办

请在这里粘贴代码import sensor, image, time
import network, usocket, ujson
from servo import Servos

s1 = Servo(1) # P7
s2 = Servo(2) # P8

# 初始化摄像头和PWM输出口
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 2000)

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 = tf.load("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) + ')')


s1.angle(0)
clock = time.clock()

shuji_index = 0

while(True):
    img = sensor.snapshot()
    for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
        print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
        img.draw_rectangle(obj.rect())
        if obj.output()[shuji_index] > 0.6:
            s1.angle(180)
        else:
            s1.angle(0)
        time.sleep(1)
这个代码为什么报错，怎么解决希望提供代码支持。
项目:垃圾分拣edge impulse训练的模型用OPEN MV H4 plus 识别，然后控制舵机进行旋转90°，用的是官方配的舵机和舵机扩展版，一共需要两个舵机![0_1680437091605_123456.jpg](https://fcdn.singtown.com/fcc94313-d10a-4539-8bf4-712b1af1b3b3.jpg) 

@kidswong999 edge lmpulse建立的模型是通过你给的代码直接到进去的吗，没看到模型导入的代码，只看到了标签的

@kidswong999 只需要改标签对吧，其他的不用动

@kidswong999 在 edge lmpulse建立的模型部署到OPEN MV H7 PLUS信号传递问题 中说：

s1 = Servo(1) # P7
s2 = Servo(2) # P8
你这个是定义到open mv 上的吗。还是说舵机扩展版上的

import sensor, image, time
import network, usocket, ujson
from servo import Servos

s1 = Servo(1) # P7
s2 = Servo(2) # P8

# 初始化摄像头和PWM输出口
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 2000)

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 = tf.load("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) + ')')


s1.angle(0)
clock = time.clock()

shuji_index = 0

while(True):
    img = sensor.snapshot()
    for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
        print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
        img.draw_rectangle(obj.rect())
        if obj.output()[shuji_index] > 0.6:
            s1.angle(180)
        else:
            s1.angle(0)
        time.sleep(1)

这个代码为什么报错，怎么解决希望提供代码支持。
项目:垃圾分拣edge impulse训练的模型用OPEN MV H4 plus 识别，然后控制舵机进行旋转90°，用的是官方配的舵机和舵机扩展版，一共需要两个舵机

@kidswong999 你这个OPENMV 用的传感器扩展板吗，如果用扩展版怎么搞

@kidswong999
我用的官方配的舵机扩展版。这种情况怎么搞。

具体用什么代码，我小白一个，请帮助一下，万分感谢

import sensor, image, time
import network, usocket, ujson
from servo import Servos
from machine import I2C, Pin
i2c = I2C(sda=Pin('P5'), scl=Pin('P4'))


# 初始化摄像头和PWM输出口
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 2000)
tim = pyb.Timer(4, freq=50)
channel = tim.channel(1, pyb.Timer.PWM, pin=P5.Pin.board.PA10)

# 加载模型和标签
model_path = "/trained_model/ei_image_classification"
labels_path = "/trained_model/labels.txt"
with open(labels_path, "r") as f:
    labels = [line.strip() for line in f.readlines()]

# 加载模型到OpenMV中
net = tf.load(model_path, load_to_fb=True)

# 设置舵机初始位置
channel.pulse_width_percent(5)

# 识别循环
while(True):
    img = sensor.snapshot()
    # 对图像进行预处理以及模型推理
    input_tensor = tf.keras.preprocessing.image.img_to_array(img)
    input_tensor = np.expand_dims(input_tensor, axis=0)
    input_tensor /= 255.
    output_tensor = net(input_tensor).numpy()[0]
    for i, label in enumerate(labels):
        if label == "shouji" and output_tensor[i] > 0.6:
            # 控制舵机旋转180度
            channel.pulse_width_percent(10)
            time.sleep(1)
            channel.pulse_width_percent(5)

在做垃圾分拣项目——智能家电垃圾桶通过OPENMV 识别到物品，控制1号舵机旋转垃圾桶，控制2号舵机旋转控制托盘。
遇到的问题：我想知道edge lmpulse建立的模型部署到OPEN MV H7 PLUS识别到标签数据，怎么控制ST90S舵机旋转一定角度；
求具体代码，万分感谢！

openmv4 H7 plus做垃圾分拣项目EdgeImpulse建立的模型，导入openmv中识别物体，怎么把识别到的信号传递给舵机，如果用串口的话具体怎么做。