import sensor, image, time from pyb import UART import json yellow_threshold = (79, 100, -7, 6, 4, 41) sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(10) sensor.set_auto_whitebal(False) clock = time.clock() uart = UART(3, 115200) def find_max(blobs): max_size=0 for blob in blobs: if blob.pixels() > max_size: max_blob=blob max_size = blob.pixels() return max_blob while(True): img = sensor.snapshot() blobs = img.find_blobs([yellow_threshold]) if blobs: max_blob=find_max(blobs) print('sum :', len(blobs)) img.draw_rectangle(max_blob.rect()) img.draw_cross(max_blob.cx(), max_blob.cy()) output_str="[%d,%d]" % (max_blob.cx(),max_blob.cy()) print('you send:',output_str) uart.write(output_str+'\r\n') else: print('not found!')

IIC.zip_IIC_PYB_iic 串口显示_串口at24c02

PYB.rar_Winpy.txt_delphi TXT_十六进制_拼音输入法

拼音处理模块原理及补充说明：原理：根据操作系统拼音输入法的对照表。提取出简单的单字对照表，用于待开发系统的拼音汉字转换。主要用途：输入拼音头的汉字检索拼音对照表（简表）结构： ...

Python库 | pybuilder_radon-0.2.3-py3-none-any.whl

from pybuilder.core import use_plugin, init use_plugin("python.core") use_plugin("python.unittest") use_plugin("pybuilder_radon") @init def initialize(project): project.set_property("radon.enabled...

import sensor import image import time from pyb import UART sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) clock = time.clock() # 初始化UART uart = UART(3, 115200) # 根据实际情况修改UART的端口和波特率 while True: clock.tick() img = sensor.snapshot().lens_corr(1.8) # 检测圆形 circles = img.find_circles(threshold=3500, x_margin=10, y_margin=10, r_margin=10, r_min=2, r_max=100, r_step=2) for c in circles: img.draw_circle(c.x(), c.y(), c.r(), color=(255, 0, 0)) uart.write("1") # 发送圆形标识为1 print('圆形') img = sensor.snapshot() # 检测矩形 rects = img.find_rects(threshold=10000) for r in rects: img.draw_rectangle(r.rect(), color=(255, 0, 0)) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color=(0, 255, 0)) uart.write("2") # 发送矩形标识为2 print('矩形') # 检测三角形 sum_theta = 0 count = 0 lines = img.find_line_segments(merge_distance=10, max_theta_diff=10) for l in lines: img.draw_line(l.line(), color=(255, 0, 0)) sum_theta += l.theta() count += 1 avg_theta = sum_theta / count if count > 0 else 0 if 1 < avg_theta < 75: uart.write("3") # 发送三角形标识为3 print('三角形') print("FPS %f" % clock.fps())

它使用了OpenMV的库来进行图像处理和形状检测，并通过UART与其他设备进行通信。代码的主要逻辑如下： 1. 初始化摄像头和串口。 2. 进入无限循环，每次循环读取一帧图像。 3. 在图像中检测圆形，如果检测到，则向...

THRESHOLD = (22, 0, -128, 127, -128, 127) import sensor, image, time from pyb import LED import time from pyb import UART import math LED(1).on() LED(2).on() LED(3).on() uart = UART(3,115200) sensor.reset() sensor.set_vflip(True) sensor.set_hmirror(True) sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQQVGA) sensor.skip_frames(time = 2000) clock = time.clock() while(True): clock.tick() img = sensor.snapshot().binary([THRESHOLD]) line = img.get_regression([(100,100)], robust = True) if (line): rho_err = abs(line.rho())-img.width()/2 if line.theta()>90: theta_err = line.theta()-180 else: theta_err = line.theta() img.draw_line(line.line(), color = 127) print(rho_err,line.magnitude(),rho_err) pass 帮我分析这段代码

代码首先导入了所需的库和模块，包括sensor、image、time、pyb和math。然后定义了一个阈值THRESHOLD，用于图像二值化。接下来，代码进行了一些初始化设置，包括重置传感器、设置图像格式和帧大小等。在主循环中...

这段代码哪里有问题 import pyb import sensor, image, time, math from machine import UART from pyb import LED import os, tf void main(){ uart_num = uart.any() # 获取当前串口数据数量 uart_str = None while(1): if(uart_num): uart_str = uart.read(uart_num).strip() # 读取串口数据 print(str(uart_str)) SendArray[i] += 128 print(" 发送数据：", SendArray) uart.write(bytearray(SendArray)) SendModel = 0 SendArray = [0,0,0,0,0,0] # 数组归零 FinalNumResult = [] }

import sensor, image, time, math from machine import UART from pyb import LED import os, tf def main(): uart = UART(1) # 初始化 UART 对象 SendArray = [0, 0, 0, 0, 0, 0] # 初始化 SendArray ...

结合以下代码 import sensor import image import time from pyb import UART import struct # 导入struct模块 typecode ='bi' code = '' sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) clock = time.clock() # 初始化UART uart = UART(3, 115200) # 根据实际情况修改UART的端口和波特率 # 定义一个结构体类型和一个结构体变量 class OpenmvDataStruct: def init(self, shape, num): self.shape = shape self.num = num data = OpenmvDataStruct('N', 0) # 初始值为shape为'N'，num为0 while True: clock.tick() img = sensor.snapshot().lens_corr(1.8) # 检测圆形 for c in img.find_circles(threshold=3500, x_margin=10, y_margin=10, r_margin=10, r_min=2, r_max=100, r_step=2): img.draw_circle(c.x(), c.y(), c.r(), color=(255, 0, 0)) print('圆形') data.shape = 'C' #标识为C data.num = 1 img = sensor.snapshot() # 检测矩形 for r in img.find_rects(threshold=10000): img.draw_rectangle(r.rect(), color=(255, 0, 0)) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color=(0, 255, 0)) print('矩形') data.shape = 'R' #标识为2 data.num = 2 # 检测三角形 sum_theta = 0 count = 0 for l in img.find_line_segments(merge_distance=10, max_theta_diff=10): img.draw_line(l.line(), color=(255, 0, 0)) sum_theta += l.theta() count += 1 avg_theta = sum_theta / count if count > 0 else 0 if 1 < avg_theta < 75: print('三角形') data.shape = 'T' #标识为T data.num = 3 print("FPS %f" % clock.fps()) # 将结构体变量data打包成字节流，并发送给Arduino # 打包data为字节流 packed_data = struct.pack(typecode, ord(data.shape), data.num) print(ord(data.shape)) uart.write(packed_data) # 发送数据

这段代码是一个综合示例，使用OpenMV进行图像处理，并通过UART将数据发送给Arduino。在这段代码中，你已经定义了一个结构体类型OpenmvDataStruct，并创建了一个结构体变量data来存储数据。在最后的部分，你...

可以把这段代码精简吗import sensor, image, time, lcd from pyb import UART sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time = 2000) lcd.init() sensor.set_auto_gain(False) sensor.set_auto_whitebal(False) clock = time.clock() uart = UART(3, 19200, timeout_char=2000) while(True): clock.tick() img = sensor.snapshot().lens_corr(1.8) lcd.display(img) for c in img.find_circles(threshold = 3500, x_margin = 10, y_margin = 10, r_margin = 10, r_min = 2, r_max = 100, r_step = 2): area = (c.x()-c.r(), c.y()-c.r(), 2c.r(), 2c.r()) statistics = img.get_statistics(roi=area) print(statistics) if 0<statistics.l_mode()<100 and 0<statistics.a_mode()<127 and 0<statistics.b_mode()<127: img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0)) uart.write("find red cirl!\n") time.sleep_ms(2000) else: img.draw_rectangle(area, color = (255, 255, 255)) uart.write("nothing!\n") time.sleep_ms(2000) print("FPS %f" % clock.fps())

from pyb import UART sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) lcd.init() sensor.set_auto_gain(False) sensor.set_auto_...

import sensor, image, time,math,pyb from pyb import UART,LED import json import ustruct sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time = 2000) sensor.set_auto_gain(False) # must be turned off for color tracking sensor.set_auto_whitebal(False) # must be turned off for color tracking red_threshold_01=(10, 100, 127, 32, -43, 67) clock = time.clock() uart = UART(3,115200) #定义串口3变量 uart.init(115200, bits=8, parity=None, stop=1) # init with given parameters def find_max(blobs): #定义寻找色块面积最大的函数 max_size=0 for blob in blobs: if blob.pixels() > max_size: max_blob=blob max_size = blob.pixels() return max_blob def sending_data(cx,cy,cw,ch): global uart; #frame=[0x2C,18,cx%0xff,int(cx/0xff),cy%0xff,int(cy/0xff),0x5B]; #data = bytearray(frame) data = ustruct.pack("<bbhhhhb", #格式为俩个字符俩个短整型(2字节) 0x2C, #帧头1 0x12, #帧头2 int(cx), # up sample by 4 #数据1 int(cy), # up sample by 4 #数据2 int(cw), # up sample by 4 #数据1 int(ch), # up sample by 4 #数据2 0x5B) uart.write(data); #必须要传入一个字节数组 while(True): clock.tick() img = sensor.snapshot() blobs = img.find_blobs([red_threshold_01]) cx=0;cy=0; if blobs: max_b = find_max(blobs) #如果找到了目标颜色 cx=max_b[5] cy=max_b[6] cw=max_b[2] ch=max_b[3] img.draw_rectangle(max_b[0:4]) # rect img.draw_cross(max_b[5], max_b[6]) # cx, cy FH = bytearray([0x2C,0x12,cx,cy,cw,ch,0x5B]) #sending_data(cx,cy,cw,ch) uart.write(FH)

blobs = img.find_blobs([red_threshold_01]) cx=0;cy=0; if blobs: max_b = find_max(blobs) # 如果找到了目标颜色 cx=max_b[5] cy=max_b[6] cw=max_b[2] ch=max_b[3] img.draw_rectangle(max_b[0:4]) # ...

用UART库将你的代码通过串口发送给arduino import sensor import image import time sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) clock = time.clock() while True: clock.tick() img = sensor.snapshot().lens_corr(1.8) # 检测圆形 for c in img.find_circles(threshold=3500, x_margin=10, y_margin=10, r_margin=10, r_min=2, r_max=100, r_step=2): img.draw_circle(c.x(), c.y(), c.r(), color=(255, 0, 0)) print(c) img = sensor.snapshot() # 检测矩形 for r in img.find_rects(threshold=10000): img.draw_rectangle(r.rect(), color=(255, 0, 0)) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color=(0, 255, 0)) print(r) # 检测三角形 sum_theta = 0 count = 0 for l in img.find_line_segments(merge_distance=10, max_theta_diff=10): img.draw_line(l.line(), color=(255, 0, 0)) sum_theta += l.theta() count += 1 avg_theta = sum_theta / count if count > 0 else 0 if 1 < avg_theta < 110: print('三角形') print("FPS %f" % clock.fps())

from pyb import UART uart = UART(3, 115200) # 根据你的实际情况选择正确的串口和波特率 # 你的代码 code = ''' import sensor import image import time sensor.reset() sensor.set_pixformat(sensor.RGB565) ...

openMV用UART库将以下代码通过串口发送给arduino import sensor import image import time sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) clock = time.clock() while True: clock.tick() img = sensor.snapshot().lens_corr(1.8) # 检测圆形 for c in img.find_circles(threshold=3500, x_margin=10, y_margin=10, r_margin=10, r_min=2, r_max=100, r_step=2): img.draw_circle(c.x(), c.y(), c.r(), color=(255, 0, 0)) print(c) img = sensor.snapshot() # 检测矩形 for r in img.find_rects(threshold=10000): img.draw_rectangle(r.rect(), color=(255, 0, 0)) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color=(0, 255, 0)) print(r) # 检测三角形 sum_theta = 0 count = 0 for l in img.find_line_segments(merge_distance=10, max_theta_diff=10): img.draw_line(l.line(), color=(255, 0, 0)) sum_theta += l.theta() count += 1 avg_theta = sum_theta / count if count > 0 else 0 if 1 < avg_theta < 110: print('三角形') print("FPS %f" % clock.fps())

from pyb import UART uart = UART(3, 115200) # 根据你的实际情况选择正确的串口和波特率 # 你的代码 code = ''' import sensor import image import time sensor.reset() sensor.set_pixformat(sensor.RGB565) ...

可以把这段代码精简吗import sensor, image, time from pyb import UART sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time = 2000) 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() uart = UART(3, 19200, timeout_char=2000) while(True): clock.tick() img = sensor.snapshot().lens_corr(1.8) for c in img.find_circles(threshold = 3500, x_margin = 10, y_margin = 10, r_margin = 10, r_min = 2, r_max = 100, r_step = 2): area = (c.x()-c.r(), c.y()-c.r(), 2c.r(), 2c.r()) #area为识别到的圆的区域，即圆的外接矩形框 statistics = img.get_statistics(roi=area)#像素颜色统计 print(statistics) #(0,100,0,120,0,120)是红色的阈值，所以当区域内的众数（也就是最多的颜色），范围在这个阈值内，就说明是红色的圆。 #l_mode()，a_mode()，b_mode()是L通道，A通道，B通道的众数。 if 0<statistics.l_mode()<100 and 0<statistics.a_mode()<127 and 0<statistics.b_mode()<127:#if the circle is red img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))#识别到的红色圆形用红色的圆框出来 uart.write("Hello esp32!\r") time.sleep_ms(2000) else: img.draw_rectangle(area, color = (255, 255, 255)) #将非红色的圆用白色的矩形框出来 print("FPS %f" % clock.fps())

from pyb import UART sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time=2000) sensor.set_auto_gain(False) sensor.set_auto_whitebal(False) ...

from pyb import UART import sensor, image, time, os, tf, pyb sensor.reset() sensor.set_pixformat(sensor.GRAYSCALE) sensor.set_framesize(sensor.QVGA) sensor.set_windowing((160,160)) sensor.skip_frames(time=2000) sensor.set_contrast(3) uart = UART(3, 115200) clock = time.clock() flag = 0 while True: clock.tick() img = sensor.snapshot().binary([(0,64)]) img.lens_corr(1.8) for obj in tf.classify("shuzishibie.tflite", img, min_scale=1.0, scale_mul=0.5, x_overlap=0.6, y_overlap=0.5): output = obj.output() number = output.index(max(output)) confidence = int(max(output) * 100) if confidence > 75: uart.write(str(number)) print(str(number)) else: uart.write('0') print('0') pyb.delay(10) # 添加延时，单位为毫秒在这里面添加无法识别红色的代码

red_threshold = (30, 100, 15, 127, 15, 127) # 设置红色阈值 for blob in img.find_blobs([red_threshold], pixels_threshold=200, area_threshold=200): # 在此处添加您的处理代码，例如打印坐标或执行其他操作 ...

import sensor, image, time, os, tf, pyb from pyb import UART sensor.reset() # Reset and initialize the sensor. sensor.set_pixformat(sensor.GRAYSCALE) # 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. uart = UART(3, 15200) clock = time.clock() while(True): clock.tick() img = sensor.snapshot().binary([(0,64)]) img.lens_corr(1.8) for obj in tf.classify("shuzishibie.tflite", img, min_scale=1.0, scale_mul=0.5, x_overlap=0.0, y_overlap=0.0): output = obj.output() number = output.index(max(output)) if number==1: uart.write('1') print(number) elif number==2: uart.write('2') print(number) elif number==3: uart.write('3') print(number) elif number==4: uart.write('4') print(number) elif number==5: uart.write('5') print(number) elif number==6: uart.write('6') print(number) elif number==7: uart.write('7') print(number) else: uart.write('8') print(number)

每次循环中，通过sensor.snapshot()获取图像，并对图像进行二值化处理。然后使用TensorFlow模型对图像进行分类，得到一个输出结果。根据输出结果的最大值，判断识别结果是哪个数字，然后通过UART发送相应的数字给...

import time from pyb import UART # 初始化串口 uart = UART(3, 115200) # 根据实际情况选择串口号和波特率 def send_serial_data(data1, data2): frame_start = bytes([0x02]) # 帧头 frame_end = bytes([0x03]) # 帧尾 payload = bytes([ord(data1), data2]) # 字符和数字作为有效载荷 frame = frame_start + payload + frame_end uart.write(frame) time.sleep(0.01) # 等待传输完成 # 调用函数发送数据 send_serial_data('A', 123) 该代码为什么无法运行

你可以通过在代码开头添加 import time 和 from pyb import UART 来导入这些模块。 2. 串口初始化错误：请确保你正确初始化了串口对象。在你的代码中，使用了 UART(3, 115200) 初始化了一个串口对象。请根据...

给以下代码加循环 import time from pyb import UART # 初始化串口 uart = UART(1, 115200) # 根据实际情况选择串口号和波特率 def send_serial_data(data1, data2): frame_start = bytes([0x02]) # 帧头 frame_end = bytes([0x03]) # 帧尾 payload = bytes([ord(data1)]) + bytes([data2]) # 字符和数字作为有效载荷 frame = frame_start + payload + frame_end uart.write(frame) time.sleep(0.01) # 等待传输完成 # 调用函数发送数据 send_serial_data('A', 123)

from pyb import UART # 初始化串口 uart = UART(1, 115200) # 根据实际情况选择串口号和波特率 def send_serial_data(data1, data2): frame_start = bytes([0x02]) # 帧头 frame_end = bytes([0x03]) # 帧尾 ...

from pyb import Pin, Timer inverse_left=False #change it to True to inverse left wheel inverse_right=False #change it to True to inverse right wheel ain1 = Pin('P0', Pin.OUT_PP) ain2 = Pin('P1', Pin.OUT_PP) bin1 = Pin('P2', Pin.OUT_PP) bin2 = Pin('P3', Pin.OUT_PP) ain1.low() ain2.low() bin1.low() bin2.low() pwma = Pin('P7') pwmb = Pin('P8') tim = Timer(4, freq=1000) ch1 = tim.channel(1, Timer.PWM, pin=pwma) ch2 = tim.channel(2, Timer.PWM, pin=pwmb) ch1.pulse_width_percent(0) ch2.pulse_width_percent(0) def run(left_speed, right_speed): if inverse_left==True: left_speed=(-left_speed) if inverse_right==True: right_speed=(-right_speed) if left_speed < 0: ain1.low() ain2.high() else: ain1.high() ain2.low() ch1.pulse_width_percent(int(abs(left_speed))) if right_speed < 0: bin1.low() bin2.high() from pyb import Pin, Timer inverse_left=False #change it to True to inverse left wheel inverse_right=False #change it to True to inverse right wheel ain1 = Pin('P0', Pin.OUT_PP) ain2 = Pin('P1', Pin.OUT_PP) bin1 = Pin('P2', Pin.OUT_PP) bin2 = Pin('P3', Pin.OUT_PP) ain1.low() ain2.low() bin1.low() bin2.low() pwma = Pin('P7') pwmb = Pin('P8') tim = Timer(4, freq=1000) ch1 = tim.channel(1, Timer.PWM, pin=pwma) ch2 = tim.channel(2, Timer.PWM, pin=pwmb) ch1.pulse_width_percent(0) ch2.pulse_width_percent(0) def run(left_speed, right_speed): if inverse_left==True: left_speed=(-left_speed) if inverse_right==True: right_speed=(-right_speed) if left_speed < 0: ain1.low() ain2.high() else: ain1.high() ain2.low() ch1.pulse_width_percent(int(abs(left_speed))) if right_speed < 0: bin1.low() bin2.high() else: bin1.high() bin2.low() ch2.pulse_width_percent(int(abs(right_speed))) 帮我分析这段代码

代码中使用了pyb库来控制引脚和定时器。代码的功能是根据输入的左右电机速度来控制电机的转动方向和转速。首先，代码定义了四个引脚ain1、ain2、bin1、bin2，分别对应左右电机的控制引脚。然后定义了两个...

import time from pyb import UART import ustruct # 初始化串口 uart = UART(3, 115200) # 根据实际情况选择串口号和波特率 def send_serial_data(data1, data2): frame_start = bytes([0x02]) # 帧头 frame_end = bytes([0x03]) # 帧尾 payload = bytes([ord(data1), data2]) # 字符和数字作为有效载荷 frame = frame_start + payload + frame_end uart.write(frame) time.sleep(0.01) # 等待传输完成 # 调用函数发送数据 send_serial_data('A', 123) 完善该代码

from pyb import UART # 初始化串口 uart = UART(3, 115200) # 根据实际情况选择串口号和波特率 def send_serial_data(data1, data2): frame_start = bytes([0x02]) # 帧头 frame_end = bytes([0x03]) # 帧尾 ...

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