k1h5 发布的帖子

这个nn模块如何进行添加

在openmv中如何同时调用彩图和灰度图，opencv中的Mat dst=img.clone()如何在openmv中表示，我需要将二值图与彩图进行点乘运算，如何用程序来表示。我试着用遍历像素的方法弄了，但是有错误

openmv中如何对像素进行遍历

import sensor, image, time, math

sensor.reset()                      # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.VGA)   # Set frame size to QVGA (320x240)
sensor.skip_frames(time = 2000)     # Wait for settings take effect.
clock = time.clock()                # Create a clock object to track the FPS.

while(True):
    #img = sensor.snapshot()         # Take a picture and return the image.
    img = sensor.snapshot()
    #红色阈值
    for y in range(0,480,3):
        for x in range(0,640):
            #img.get_pixel(x,y)
            if img.get_pixel(x,y)>=205:
               img.get_pixel(x,y)=255
            elif img.get_pixel(x,y)<=195:
               img.get_pixel(x,y)=0
            else:
               img.get_pixel(x,y)=img.get_pixel(x,y)

import numpy as np

x = np.random.randn(20)
y = np.random.randn(20)
k = 3
#1.选取聚类中心
center0=np.array([x[0],y[0]])
center1=np.array([x[1],y[1]])

#2.开始迭代
iter = 100
while iter > 0:
print('111111')
res = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
for i in range(20):
# 2.1计算每个对象与聚类中心的距离
dis0 = np.sqrt((x[i] - center0[0]) ** 2 + (y[i] - center0[1]) ** 2)
dis1 = np.sqrt((x[i] - center1[0]) ** 2 + (y[i] - center1[1]) ** 2)

      #2.1归类
      if(dis0 > dis1):
          res[i]=1
      else:
          res[i]=0

  #2.3新的聚类中心
  res0 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
  res01 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
  res1 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
  res11 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
  n0 = 0
  n1 = 0
  for i in range(20):
      if res[i] == 0:
          res0[n0] = x[i]
          res01[n0] = y[i]
          n0 += 1
      else:
          res1[n1] = x[i]
          res11[n1] = y[i]
          n1 += 1

  center0_new = np.array([np.array(res0).mean(), np.array(res01).mean()])
  center1_new = np.array([np.array(res1).mean(), np.array(res11).mean()])

  #3.判定聚类中心位置是否发生变换
  if all((center0 == center0_new) & (center1 == center1_new)):
      # 如果没发生变换则退出循环，表示已得到最终的聚类中心
      break

  center1=center1_new
  center0=center0_new

#4.输出结果
for i in range(20):
if res[i] == 0:
print(x[i],y[i],'0')
else:
print(x[i],y[i],'1')

两张图片之间的与运算如何用程序表示

在这个里面如何调用分水岭算法或者如何自己来编写分水岭

import sensor, image, time
import json
from pyb import UART


sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 2000)
sensor.skip_frames(10)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock = time.clock()


#串口初始化
uart = UART(3,115200)  #初始化串口3，波特率115200
uart.init(115200,bits=8,parity=None,stop=1)  #8位数据位  无校验位 1位停止

def sending_data(cx,cy):
    data = ustruct.pack("<bbhhb",
                   0x2C,
                   0x12,
                   int(cx),
                   int(cy),
                   0x3C)
    uart.write(data);

while(True):
    
    sending_data(5,4)
    time.sleep_ms(1000)
    print(55555)

name 'ustruct' isn't defined如何解决