17826808312 发布的帖子

这是我二值化以后的图像，请问可以用边缘检测算法检测出格子里面的圆吗，如果可以的话，应该怎么做呢

回复: 请问如何统计二值化图像的白色像素点
我看到可以用statistics来进行统计的，但是它只有灰度值的平均数、众数这些并没有我要的像素点的总数，请问还有其他方法吗？

要识别的物体因为灯光原因，反光比较严重，如何去除图像中的反光

老师，请问openmv识别到的圆可以通过返回的圆相对于镜头的坐标c.x()和c.y()来计算圆到镜头的距离吗？我知道apriltag标签是可以的，它有返回x，y，z三个方向上的坐标，但是圆只有x和y，没有z，想知道是否可以计算出距离呢？

老师理论上可以用画矩形的这个函数把我想要的roi区域给框起来吗？我试了下面这个报错了。。

img.draw_rectangle(roi=(0,000,160,80), color = (0, 255, 0))

@kidswong999 老师理论上可以用画矩形的这个函数把我想要的roi区域给框起来吗？我试了下面这个报错了。。

img.draw_rectangle(roi=(0,000,160,80), color = (0, 255, 0))

@kidswong999 老师你看一下，为什么我这边的ROI不起作用，是程序写得不对吗？

import sensor, image, time, math
ROI = [(50,100,50,80)]

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA) # we run out of memory if the resolution is much bigger...
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False)  # must turn this off to prevent image washout...
sensor.set_auto_whitebal(False)  # must turn this off to prevent image washout...
clock = time.clock()

tag_families = 0
tag_families |= image.TAG16H5 # comment out to disable this family
tag_families |= image.TAG25H7 # comment out to disable this family
tag_families |= image.TAG25H9 # comment out to disable this family
tag_families |= image.TAG36H10 # comment out to disable this family
tag_families |= image.TAG36H11 # comment out to disable this family (default family)
tag_families |= image.ARTOOLKIT # comment out to disable this family

def family_name(tag):
    if(tag.family() == image.TAG16H5):
        return "TAG16H5"
    if(tag.family() == image.TAG25H7):
        return "TAG25H7"
    if(tag.family() == image.TAG25H9):
        return "TAG25H9"
    if(tag.family() == image.TAG36H10):
        return "TAG36H10"
    if(tag.family() == image.TAG36H11):
        return "TAG36H11"
    if(tag.family() == image.ARTOOLKIT):
        return "ARTOOLKIT"

for t in ROI:    
    while(True):
        clock.tick()
        img = sensor.snapshot()
        for tag in img.find_apriltags(families=tag_families): # defaults to TAG36H11 without "families".
            img.draw_rectangle(tag.rect(), color = (255, 0, 0))
            img.draw_cross(tag.cx(), tag.cy(), color = (0, 255, 0))
            print_args = (family_name(tag), tag.id(), (180 * tag.rotation()) / math.pi)
            print("Tag Family %s, Tag ID %d, rotation %f (degrees)" % print_args)
        print(clock.fps())

@kidswong999 有获取矩形ROI区域的例程吗？

有没有现有的例程啊？

老师问一下有没有什么方法能够只截取我下图中红色框中的图像，让openmv只对红框中的图像内容进行各种识别呢？是用roi还是其他什么？
0_1562512602733_微信图片_20190707231301.jpg

老师问一下，我这边代码最后一个else不起作用是为什么？

import sensor, image, time
from pyb import UART

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # grayscale is faster
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

uart = UART(4, 115200)

while(True):
    clock.tick()
    if uart.any():
        a = uart.read().decode()
        b = int(a)-8
        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):
            img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))
            if c:
                output_str="[%d]" % (b)
                uart.write(output_str+'\r\n')
            else:
                output_str="[%d]" % (0)
                uart.write(output_str+'\r\n')

@kidswong999 老师我改了缩进以后可以同时识别tag标签和圆形了，但是出来的图像一抖一抖的是为什么

老师我都是用一个tab缩进的，是这样缩进有问题吗

为什么在识别圆形的程序后面加上一个串口接收数据的程序，我向openmv发送了66，77这两个数据，符合if中的条件判断，但串口调试助手上收不到我想要openmv发送的这个数据2呢？是程序有问题吗？

import sensor, image, time
from pyb import UART

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # grayscale is faster
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

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):
        img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))
        uart = UART(3, 115200)
        if uart.any():
            a = uart.read().decode().split(',')
            x = int(a[0])
            y = int(a[1])
            if 50<x<100&50<y<100:
                t = 2
                output_str="[%d]" % (t)
                uart.write(output_str+'\r\n')

请问如何编写程序才能让openmv同时识别apriltag和圆形？我把识别圆形的程序放到识别apriltag的程序后面，在openmv的视野中没有apriltag只有圆形的情况下，发现识别不了圆形。

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

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA) # we run out of memory if the resolution is much bigger...
sensor.skip_frames(30)
sensor.set_auto_gain(False)  # must turn this off to prevent image washout...
sensor.set_auto_whitebal(False)  # must turn this off to prevent image washout...
clock = time.clock()


f_x = (2.8 / 3.984) * 160 # 默认值
f_y = (2.8 / 2.952) * 120 # 默认值
c_x = 160 * 0.5 # 默认值(image.w * 0.5)
c_y = 120 * 0.5 # 默认值(image.h * 0.5)

def degrees(radians):
    return (180 * radians) / math.pi

while(True):
    clock.tick()
    img = sensor.snapshot()
    for tag in img.find_apriltags(families=image.TAG25H9, fx=f_x, fy=f_y, cx=c_x, cy=c_y): # 默认为TAG36H11
        img.draw_rectangle(tag.rect(), color = (255, 0, 0))
        img.draw_cross(tag.cx(), tag.cy(), color = (0, 255, 0))
        degress = tag.rotation()
        print_args = (tag.x_translation(), tag.y_translation(), tag.z_translation(), \
            degrees(tag.x_rotation()), degrees(tag.y_rotation()), degrees(tag.z_rotation()))
        # 位置的单位是未知的，旋转的单位是角度
        #print("Tx: %f, Ty %f, Tz %f, Rx %f, Ry %f, Rz %f" % print_args)
        #print(tag.id(),degress)
        x = 0
        y = 0
        def tag_id(t):
            global x
            global y
            if (t == 0):
                x = 27.5
                y = 27.5
            elif (t == 1):
                x = 127.5
                y = 27.5
            elif (t == 2):
                x = 227.5
                y = 27.5
        tag_id(tag.id())
        o = tag.x_translation()
        p = tag.y_translation()
        q = tag.z_translation()
        a = o*o + p*p + q*q
        k = 30
        b = k*math.sqrt(a)
        c = b*b-10*10
        d = math.sqrt(c)
        #print(d)
        α = tag.rotation()
        if 0 < α < math.pi/2:
           m = x - d*math.sin(α)
           n = y + d*math.cos(α)
        if 3*math.pi/2 < α < 2*math.pi:
           m = x + d*math.sin(360-α)
           n = y + d*math.cos(360-α)
        if math.pi/2 < α < math.pi:
           m = x - d*math.sin(180-α)
           n = y - d*math.cos(180-α)
        if math.pi < α < 3*math.pi/2:
           m = x + d*math.sin(α-180)
           n = y - d*math.cos(α-180)
        #print(m, n)
        uart = UART(3, 115200)
        #output_str="[%d%03d%03d%03d]" % (1,m,n,α)
        #uart.write(output_str+'\r\n')
        time.sleep(100)
        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):
           img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))
           print(c)