import sensor, image, time, math
from pyb import UART
import lcd
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA2) # High Res!
sensor.set_windowing((640, 200)) # V Res of 80 == less work (40 for 2X the speed).
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False)  # 必须关闭此功能，以防止图像冲洗…
sensor.set_auto_whitebal(False)  # 必须关闭此功能，以防止图像冲洗…
clock = time.clock()
uart = UART(3, 9600)
# 条形码检测可以在OpenMV Cam的OV7725相机模块的640x480分辨率下运行。
# 条码检测也将在RGB565模式下工作，但分辨率较低。 也就是说，
# 条形码检测需要更高的分辨率才能正常工作，因此应始终以640x480的灰度运行。
lcd.init()
def barcode_name(code):
    if(code.type() == image.EAN2):
        return "EAN2"
    if(code.type() == image.EAN5):
        return "EAN5"
    if(code.type() == image.EAN8):
        return "EAN8"
    if(code.type() == image.UPCE):
        return "UPCE"
    if(code.type() == image.ISBN10):
        return "ISBN10"
    if(code.type() == image.UPCA):
        return "UPCA"
    if(code.type() == image.EAN13):
        return "EAN13"
    if(code.type() == image.ISBN13):
        return "ISBN13"
    if(code.type() == image.I25):
        return "I25"
    if(code.type() == image.DATABAR):
        return "DATABAR"
    if(code.type() == image.DATABAR_EXP):
        return "DATABAR_EXP"
    if(code.type() == image.CODABAR):
        return "CODABAR"
    if(code.type() == image.CODE39):
        return "CODE39"
    if(code.type() == image.PDF417):
        return "PDF417"
    if(code.type() == image.CODE93):
        return "CODE93"
    if(code.type() == image.CODE128):
        return "CODE128"

while(True):
    clock.tick()
    img = sensor.snapshot()
    codes = img.find_barcodes() 
    for code in codes:
        img.draw_rectangle(code[0:4])
        #img.draw_cross(code[5], code[6]) # cx, cy   
        x=code[5]
        print(x)
        print_args = (barcode_name(code), code.payload(), (180 * code.rotation()) / math.pi, code.quality(), clock.fps())
        print("Barcode %s, Payload \"%s\", rotation %f (degrees), quality %d, FPS %f" % print_args)
        tiaoxinma=code.payload()
        print(tiaoxinma)
        #FZ = bytearray([0x31,0x31])
        #uart.write(FZ)
        #date = bytearray([tiaoxinma])
        #uart.write(date)
        lcd.display(sensor.snapshot()) 
        img.draw_string(100,100,str(tiaoxinma),color=(0,0,0))
    if not codes:
        print("FPS %f" % clock.fps())

在pytorch上面训练好神经网络模型可以在openmv上面运行吗？效果是否和在网站上面搭建的模型一样

openmv4 h7 plus 500万 ov5640配置的openmv最多可以识别多远的条形码

openmv可以识别条形码和自动对焦吗？如果有能给链接吗

@kidswong999 无符号的！

在openmv里面把10进制数字转换成16进制数字再取高低位然后通过串口发出去，例如2000的十六进制为7d0然后 取高低位 高位在后，低位在前。0xd0，0x07.这样格式发出去如何实现。

# Blob Detection Example
#
# This example shows off how to use the find_blobs function to find color
# blobs in the image. This example in particular looks for dark green objects.

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

# You may need to tweak the above settings for tracking green things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

#sensor.set_windowing((100, 100))

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
green_threshold   = (54, 95, -4, 30, 22, 70)
size_threshold = 1500
blue_led = pyb.LED(3)
green_led = pyb.LED(2)
red_led = pyb.LED(1)
uart = UART(3, 9600)
sensor.set_auto_exposure(True, exposure_us=5000) # make smaller to go faster

def find_max(blobs):
    max_size=0
    for blob in blobs:
        if blob[2]*blob[3] > max_size:
            max_blob=blob
            max_size = blob[2]*blob[3]
    return max_blob

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    blobs = img.find_blobs([green_threshold])
    #FZ = bytearray([0x55,0x55,0x12,0x03,0x03,0xd0,0x07,0x01,0xa1,0x02,0x02,0x04,0x05,0x03,0x6c,0x06])
    #FZ1 = bytearray([0x55,0x55,0x14,0x03,0x05,0xd0,0x07,0x01,0x05,0x09,0x02,0x4c,0x05,0x03,0xe9,0x02,0x04,0xc1,0x07,0x05,0x24,0x02])
    #FZ1 = bytearray([0x55,0x55,0x08,0x03,0x01,0xd0,0x07,0x01,0x05,0x09])
    #uart.write(FZ1)
    
    #FZ2 = bytearray([0x55,0x55,0x08,0x03,0x02,0xd0,0x07,0x02,0x4c,0x05])
    #uart.write(FZ2)
    #time.sleep_ms(1000)
    #FZ3 = bytearray([0x55,0x55,0x08,0x03,0x03,0xd0,0x07,0x03,0xe9,0x02])
    #uart.write(FZ3)
    #time.sleep_ms(1000)
    #FZ4 = bytearray([0x55,0x55,0x08,0x03,0x04,0xd0,0x07,0x04,0xc1,0x07])
    #uart.write(FZ)
    time.sleep_ms(1000)
    xiangshu=0
    
    if blobs:
        max_blob = find_max(blobs)
        max_blob1=find_max1(blobs)
        xiangshu = max_blob.blob[4]
        img.draw_rectangle(max_blob[0:4]) # rect
        img.draw_cross(max_blob[5], max_blob[6]) # cx, cy
        if xiangshu > size_threshold:
                    #FZ = bytearray([0x55,0x55,0x05,0x06,0x64,0x01,0x00])
                    #art.write(FZ)
                    red_led.on()
                    time.sleep_ms(150)#延时150ms
                    red_led.off()
        else:
                    blue_led.on()
                    time.sleep_ms(150)     #延时150ms    
                    blue_led.off()
        
    else:
        green_led.on()
        time.sleep_ms(150)     #延时150ms    
        green_led.off()

如何做到，在运动中物体出现在镜头正对的方向时，开始识别物体颜色大小

如何提高openmv刷新帧数，让openmv识别颜色快速反应

如果可以需要怎么做！

我就是没有单独查到openmv上啊，就是有三个孔，舵机正负极就单独插电源

openmv驱动舵机，舵机单独供给电源可以吗？6-7.4v的，如何操作呢

而且我感觉openmv循环里的判断语句不能一直持续判断，感觉就像只判断一次就没了

# Blob Detection Example
#
# This example shows off how to use the find_blobs function to find color
# blobs in the image. This example in particular looks for dark green objects.

import sensor, image, time, pyb

# You may need to tweak the above settings for tracking green things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
green_threshold   = (75, 96, -43, -0, -1, 55)
size_threshold = 2000
blue_led = pyb.LED(3)
green_led = pyb.LED(2)
red_led = pyb.LED(1)

def find_max(blobs):
    max_size=0
    for blob in blobs:
        if blob[2]*blob[3] > max_size:
            max_blob=blob
            max_size = blob[2]*blob[3]
    return max_blob
def find_max1(blobs):
        max_size=0
        for blob in blobs:
            if blob[2]*blob[3] > max_size:
                max_blob=blob
                max_size = blob[2]*blob[3]
                max_blob1=blob[4]
        return max_blob1返回像素点大小


while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    blobs = img.find_blobs([green_threshold])
    if blobs:
        max_blob = find_max(blobs)
        max_blob1=find_max1(blobs)
        xiangshu = max_blob1
        img.draw_rectangle(max_blob[0:4]) # rect
        img.draw_cross(max_blob[5], max_blob[6]) # cx, cy
        if xiangshu > size_threshold:
                    red_led.on()
        else:
                    blue_led.on()                   
        
    else:
        green_led.on()

# Blob Detection Example
#
# This example shows off how to use the find_blobs function to find color
# blobs in the image. This example in particular looks for dark green objects.

import sensor, image, time, pyb

# You may need to tweak the above settings for tracking green things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
green_threshold   = (76, 96, -110, -30, 8, 66)
size_threshold = 2000
blue_led = pyb.LED(3)
green_led = pyb.LED(2)
red_led = pyb.LED(1)

def find_max(blobs):
    max_size=0
    for blob in blobs:
        if blob[2]*blob[3] > max_size:
            max_blob=blob
            max_size = blob[2]*blob[3]
    return max_blob

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    blobs = img.find_blobs([green_threshold])
    if blobs:
        max_blob = find_max(blobs)
        xiangshu = max_blob.blob[4]
        img.draw_rectangle(max_blob[0:4]) # rect
        img.draw_cross(max_blob[5], max_blob[6]) # cx, cy
        if xiangshu > size_threshold
                    red_led.on()
        else:
                    blue_led.on()                   
        
    else:
        green_led.on()

我单独运行颜色检测也可以，单独运行led灯也行，合在一起就是不行了

希望解答，实在不明白

@hmxd 就是这个main.py 的原文件。我删了换成驱动舵机的代码了，就不行了，所以求一下原代码。

有谁可以分享一下openmv里面的main原来的代码吗？

买了舵机拓展板，没有焊接就是直接插上去。
这是main中编的代码

Servo Shield Example.

This example demonstrates the servo shield. Please follow these steps:

1. Connect a servo to any PWM output.

2. Connect a 3.7v battery (or 5V source) to VIN and GND.

3. Copy pca9685.py and servo.py to OpenMV and reset it.

4. Connect and run this script in the IDE.

import time
from servo import Servos
from machine import I2C, Pin

i2c = I2C(sda=Pin('P5'), scl=Pin('P4'))
servo = Servos(i2c, address=0x40, freq=50, min_us=500, max_us=2500, degrees=180)

while True:
servo.position(0, 0)
time.sleep_ms(500)
servo.position(0, 180)
time.sleep_ms(500)

openmv连接电脑直接说未检测到我的openmv cam 然后闪灯绿白红，这是怎么回事