na3m 发布的帖子

要求是要加条件，进行判断如果环境改变，输出形状，如果形状被遮挡，输出颜色

import sensor, image, time, math

# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max)
# The below thresholds track in general red/green things. You may wish to tune them...
thresholds = [(0, 20, -18, 127, -8, 22), # generic_red_thresholds -> index is 0 so code == (1 << 0)
              (0, 60, -18, -48, 22, 127),
              (0, 50, 2, 127, 2, 127)]  # generic_green_thresholds -> index is 1 so code == (1 << 1)
# Codes are or'ed together when "merge=True" for "find_blobs".
#roi=(20,20,20,20)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.HQQVGA)
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()
# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" must be set to merge overlapping color blobs for color codes.
def yanse():
           for blob in img.find_blobs(thresholds, pixels_threshold=100, area_threshold=100, merge=True):
               if blob.code() == 1: # r/g code == (1 << 1) | (1 << 0)
                  print("红色")
                  ys=0
               elif blob.code() == 2: # r/g code == (1 << 1) | (1 << 0)
                  print("绿色")
                  ys=1
               elif blob.code() == 4: # r/g code == (1 << 1) | (1 << 0)
                  print("黑色")
                  ys=2
               else:
                   print("无色")
while(True):
    clock.tick()
    img = sensor.snapshot()
    for r in img.find_rects(threshold = 1000):
        img.draw_rectangle(r.rect(), color = (255, 0, 0))
        roi1=r.rect()
        yanse()
        print("矩形")
        jx=1
        print("FPS %f" % clock.fps())
    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))
        roi1=(c.x(), c.y(), c.r())
        yanse()
        print("圆形")
        yx=2

遮挡形状识别颜色，增加光线强度识别形状，这个该怎么搞！

怎么解决，for code in qrcodes()?

代码没问题，不知道如何同时识别多个二维码

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

black_threshold = (0, 20, -18, 127, -8, 22)      #black
green_threshold = (0, 70, -128, -28, 22, 127)  #green
red_threshold =   (0, 50, -128, 127, 12, 127) #red
thresholds = (0,0,50,50)
QRCode_1="www.xt.com";
QRCode_2="www.gym.com";
QRCode_3="www.gyt.com";
QRCode_4="www.jgz.com";
QRCode_5="www.njs.com";

qr = 0
a = 1

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, 115200)


#识别二维码
while(a):
    clock.tick()
    img = sensor.snapshot()
    img.lens_corr(1.8) # 1.8的强度参数对于2.8mm镜头来说是不错的。
    for code in img.find_qrcodes():
        img.draw_rectangle(code.rect(), color = (255, 0, 0))
        if code.payload() == QRCode_1 :
            qr=1;

        elif code.payload() == QRCode_2 :
            qr=2;

        elif code.payload() == QRCode_3 :
            qr=3;

        elif code.payload() == QRCode_4 :
            qr=4;


        else :
            qr=5;

        

        print("二维码",code)
        print(qr)
        output_str="%d,%d,%d,%d,%d" % (code.x(), code.y(),code.w(),code.h(),qr)

        uart.write(output_str+'\r\n')

@kidswong999 所以应该怎么做，需要用到哪几个函数

@kidswong999 如何调 老师要求是遮挡一下形状可以通过颜色识别定位，改变光线条件可以通过形状定位

@kidswong999 就是先识别颜色如果因为光线的原因或遮挡颜色达不到自己定义的阈值然后识别形状 怎么解决！

相似度阈值如何写 比如识别颜色阈值小于0.3识别颜色 识别颜色阈值小于0.6识别形状

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

black_threshold = (0, 20, -18, 127, -8, 22)      #black
green_threshold = (0, 70, -128, -28, 22, 127)  #green
red_threshold =   (0, 50, -128, 127, 12, 127) #red

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()
while(True):
    clock.tick()
    img = sensor.snapshot()
#识别形状颜色
    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))

        output_str="[%d,%d,%d]" % (c.x(),c.y(),c.r())
        print("形状：圆形",output_str)
        uart.write(output_str+'\r\n')

        statistics=img.get_statistics(roi = (c.r(),  c.r(), 2 * c.r(), 2 * c.r()))
        blobs = img.find_blobs([red_threshold,green_threshold,black_threshold],roi=(c.r(),  c.r(), 2 * c.r(), 2 * c.r()))
        if blobs:
            max_blob = find_max(blobs)
            img.draw_rectangle(max_blob[0:4]) # rect
            img.draw_cross(max_blob[5], max_blob[6]) # cx, cy

        else:
             pass
    for r in img.find_rects(threshold = 10000):
        img.draw_rectangle(r.rect(), color = (255, 0, 0))
        output_str="[%d,%d,%d,%d]" % (r.x(),r.y(),r.w(),r.h())
        print("形状:矩形",output_str)
        uart.write(output_str+'\r\n')

        area = r.rect()
        blobs = img.find_blobs([red_threshold,green_threshold,black_threshold],roi=area)
        if blobs:
            max_blob = find_max(blobs)
            img.draw_rectangle(max_blob[0:4]) # rect
            img.draw_cross(max_blob[5], max_blob[6]) # cx, cy

        else:
             pass

@kidswong999 我只是把注释了

@kidswong999 我买的成品

@kidswong999

没反应

@kidswong999 如何识别矩形圆形面积，我识别圆形有时候会打印矩形，怎么更改一下。

@kidswong999 意思是我的程序没问题？我识别二维码就不出二维码的网站

您帮忙看看我的程序有没有问题，程序进行循环后就只识别形状和颜色，不识别二维码了怎么解决这个问题，求指导

@kidswong999 代码没问题，他是有时候会接收到有时候接收不到

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

black_threshold = (0, 20, -18, 127, -8, 22)      #black
green_threshold = (0, 70, -128, -28, 22, 127)  #green
red_threshold =   (0, 50, -128, 127, 12, 127) #red

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, 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):
    clock.tick()
    img = sensor.snapshot()
    img.lens_corr(1.8) # 1.8的强度参数对于2.8mm镜头来说是不错的。
    for code in img.find_qrcodes():
        img.draw_rectangle(code.rect(), color = (255, 0, 0))
        print(code)
        output_str="%d,%d,%d,%d" % (code.x(), code.y(),code.w(),code.h())
        #output_str1=json.dumps(code.payload())
        uart.write(output_str+'\r\n')



    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))

        output_str="[%d,%d,%d]" % (c.x(),c.y(),c.r())
        print(output_str)
        uart.write(output_str+'\r\n')

        statistics=img.get_statistics(roi = (c.r(),  c.r(), 2 * c.r(), 2 * c.r()))
        blobs = img.find_blobs([red_threshold,green_threshold,black_threshold],roi=(c.r(),  c.r(), 2 * c.r(), 2 * c.r()))
        if blobs:
            max_blob = find_max(blobs)
            img.draw_rectangle(max_blob[0:4]) # rect
            img.draw_cross(max_blob[5], max_blob[6]) # cx, cy

        else:
             pass
    for r in img.find_rects(threshold = 10000):
        img.draw_rectangle(r.rect(), color = (255, 0, 0))
        output_str="[%d,%d,%d,%d]" % (r.x(),r.y(),r.w(),r.h())
        print(output_str)
        uart.write(output_str+'\r\n')

        area = r.rect()
        blobs = img.find_blobs([red_threshold,green_threshold,black_threshold],roi=area)
        if blobs:
            max_blob = find_max(blobs)
            img.draw_rectangle(max_blob[0:4]) # rect
            img.draw_cross(max_blob[5], max_blob[6]) # cx, cy

        else:
            pass