Blob Detection Example#by:王雨晴 2019年7月16日import sensor, image, time,pyb,mathfrom pyb import UARTfrom pyb import Pinred_threshold_01 = (58, 72, 44, 70, -1, 38)yellow_threshold_01 = (70, 98, -16, 7, 58, 72)#设置红色的阈值，括号里面的数值分别是L A B 的最大值和最小值（minL, maxL, minA,# maxA, minB, maxB），LAB的值在图像左侧三个坐标图中选取。如果是灰度图，则只需#设置（min, max）两个数字即可。# You may need to tweak the above settings for tracking green things...# Select an area in the Framebuffer to copy the color settings.K=800sensor.reset() # Initialize the camera sensor.sensor.set_pixformat(sensor.RGB565) # use RGB565.sensor.set_framesize(sensor.QQVGA) # use QVGA for quailtiy ,use QQVGA for speed.分辨率为120160sensor.skip_frames(10) # Let new settings take affect.sensor.set_auto_whitebal(False)#关闭白平衡。白平衡是默认开启的，在颜色识别中，需要关闭白平衡。clock = time.clock() # Tracks FPS.uart3= UART(3, 9600)uart1= UART(1, 9600)uart1= UART(1, 9600, timeout_char=1000)''' 扩宽roi'''def expand_roi(roi): # set for QQVGA 160120 extra = 5 win_size = (160, 120) (x, y, width, height) = roi new_roi = [x-extra, y-extra, width+2extra, height+2extra] if new_roi[0] < 0: new_roi[0] = 0 if new_roi[1] < 0: new_roi[1] = 0 if new_roi[2] > win_size[0]: new_roi[2] = win_size[0] if new_roi[3] > win_size[1]: new_roi[3] = win_size[1] return tuple(new_roi)AH = bytearray([0x40])uart1.write(AH)while(True): if uart1.any(): a=uart1.readline().decode().strip() print(a) else: a=0 if a==0: clock.tick() img = sensor.snapshot()#.lens_corr(1.8) # Take a picture and return the image. blobs = img.find_blobs([red_threshold_01], area_threshold=150)#如果返回的边界框小于area_threshold就返回none if blobs: #如果找到了目标颜色 for b in blobs: x = b.cx() y = b.cy() print(x,y) if x>=60 and x<=100: is_circle = False max_circle = None max_radius = -1 new_roi = expand_roi(b.rect()) for c in img.find_circles(threshold = 3500, x_margin = 20, y_margin = 20, r_margin = 10, roi=new_roi): is_circle = True if c.r() > max_radius: max_radius = c.r() max_circle = c if is_circle: # 如果有对应颜色的圆形 标记外框 # Draw a rect around the blob. img.draw_rectangle(new_roi) # rect img.draw_rectangle(b.rect()) # rect #用矩形标记出目标颜色区域 img.draw_rectangle(b[0:4]) img.draw_cross(b[5], b[6]) # cx, cy img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r(), color = (0, 255, 0)) img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r() + 1, color = (0, 255, 0)) Lm = (b[2]+b[3])/2 #b2是色块的长，b3是色块的宽 length =(K/Lm) print(length) str='%d'%(length) print(length) #uart1.write(str) if a==0: clock.tick() img = sensor.snapshot()#.lens_corr(1.8) # Take a picture and return the image. blobs = img.find_blobs([yellow_threshold_01], area_threshold=150)#如果返回的边界框小于area_threshold就返回none if blobs: #如果找到了目标颜色 for b in blobs: x = b.cx() y = b.cy() print(x,y) if x>=60 and x<=100: uart3.write('1') is_circle = False max_circle = None max_radius = -1 new_roi = expand_roi(b.rect()) for c in img.find_circles(threshold = 3500, x_margin = 20, y_margin = 20, r_margin = 10, roi=new_roi): is_circle = True # img.draw_circle(c.x(), c.y(), c.r(), color = (255, 255, 255)) if c.r() > max_radius: max_radius = c.r() max_circle = c if is_circle: img.draw_rectangle(new_roi) # rect img.draw_rectangle(b.rect()) # rect img.draw_rectangle(b[0:4]) img.draw_cross(b[5], b[6]) # cx, cy img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r(), color = (0, 255, 0)) img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r() + 1, color = (0, 255, 0)) Lm = (b[2]+b[3])/2 #b2是色块的长，b3是色块的宽 length =(K/Lm) print(length) str='%d'%(length) print(length)

-- coding: utf-8 --

import sensor, image, time, pyb, json

from pyb import UART

from pyb import Pin

yellow_threshold = (60 ,83 , -9, 46, 31, 72)

sensor.reset()

sensor.set_pixformat(sensor.RGB565)

sensor.set_framesize(sensor.QQVGA)

sensor.skip_frames(time = 2000 )

sensor.set_auto_whitebal(False)

sensor.set_auto_whitebal(False)

#关闭白平衡。白平衡是默认开启的，在颜色识别中，需要关闭白平衡。

uart = UART(3, 9600, timeout_char=1000)
uart = UART(3,9600)

clock = time.clock()

while(True):
clock.tick()
#FH = 0x55
#str='%d'%(FH)
uart.write('U')
if uart.any():
a=uart.readline().decode().strip()#首先是一个字节串，加入decode变为字符串，strip删掉回车和换行
print(a)
m = a[2:7]
print(m)
#n=int(m)
# if n>=00000 and n<00130:
# yellow_threshold = (39 ,72 , -11, 11, -46, -34)
# print(1)
#if n>=00130 and n<00200:
# yellow_threshold = (19 ,68 , -9, 12, -40, -13)
# print(2)
#if n>=00450 and n<00650:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(3)
#if n>=00650 and n<00850:
# yellow_threshold = (0 ,0 , -11, 3, -33, -23)
# print(4)
#if n>=00850 and n<01050:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(5)
#if n>=01050 and n<01250:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(6)
#if n>=01250 and n<01450:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(7)
#if n>=01450 and n<01650:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(8)
#if n>=01650 and n<01850:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(9)
#if n>=01850 and n<02000:
# yellow_threshold = (60 ,23 , -9, 46, 31, 72)
# print(10)

img = sensor.snapshot().lens_corr(1.9)
blob= img.find_blobs([yellow_threshold])#寻找黄色最大的色块
if blob: #如果找到了目标颜色
    for b in blob:
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy这是我的代码

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