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
import car
from pid import PID
from pyb import Servo

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()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(10)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)
sensor.set_auto_exposure(False,2000)#这里设置曝光时间

#sensor.skip_frames(time = 2000)

s3 = Servo(3) # servo on position 1 (P9)

clock = time.clock()

For color tracking to work really well you should ideally be in a very, very,

very, controlled enviroment where the lighting is constant...

red_threshold = (17, 50, -40, 110, 34, 127)
size_threshold = 2500
x_pid = PID(p=3, i=1, imax=100)
h_pid = PID(p=0.03, i=0.1, imax=50)
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):
s3.angle(90) # move to 90 degrees
clock.tick() # Track elapsed milliseconds between snapshots().
img = sensor.snapshot() # Take a picture and return the image.

blobs = img.find_blobs([red_threshold])
if blobs:
    max_blob = find_max(blobs)
    x_error = max_blob[5]-img.width()/2
    h_error = max_blob[2]*max_blob[3]-size_threshold
    print("x error: ", x_error)
    '''
    for b in blobs:
        # Draw a rect around the blob.
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy
    '''
    img.draw_rectangle(max_blob[0:4]) # rect
    img.draw_cross(max_blob[5], max_blob[6]) # cx, cy
    x_output=x_pid.get_pid(x_error,1)
    h_output=h_pid.get_pid(h_error,1)
    print("h_output",h_output)
    car.run(-h_output-x_output-50,-h_output+x_output-50)

else:
    s3.angle(-90) # move to -90 degrees
    car.run(500,-500)

这个size=2000是指多大？还有就是画质偏白怎么调整曝光度？

请问一下openmv看到的图像画质偏白我设置的阈值是红色的，经常受白光影响， 要调整哪些参数？还有就是追小球的例程里面size=2000是指多大？怎么算的

@yuan 大神帮忙看看，墙壁是白色，但是摄像头可以识别到，我阈值设定是红色的，我是根据一个红色信标灯调的阈值。

@yuan 墙壁是红色的

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

For color tracking to work really well you should ideally be in a very, very,

very, controlled enviroment where the lighting is constant...

red_threshold = (100, 92, 104, -5, -7, 94)

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.

uart = UART(3, 115200)

def find_max(blobs): #寻找最大的色块
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([red_threshold])
if blobs:
    max_blob = find_max(blobs)
    print('sum : %d'% len(blobs))
    data=[]
    for b in blobs:
        # Draw a rect around the blob.
        img.draw_rectangle(max_blob[0:4]) # rect
        img.draw_cross(max_blob[5], max_blob[6]) # cx, cy
        data.append((b.cx(),b.cy()))

    #{(1,22),(-3,33),(22222,0),(9999,12),(0,0)}
    data_out = json.dumps(set(data))
    uart.write(data_out +'\n')
    print(data_out)
else:
    print("not found!")

OPENMV怎么用SPI通信发送色块坐标给arduino,串口通信太慢了，想用SPI但是不知道怎么解析，有大神有参考程序吗？

OPENMV识别红色的时候会有问题，看见墙壁也是红色，请问大神们这个是镜头的问题还是程序的问题？我是用来识别红色的灯

@kidswong999 传回来是这这些数值，我不知道怎么对这些数值进行计算

@kidswong999 就是openmv通过串口发送给arduino的数据是数组，我在arduino要怎么写程序提取这些数值并且计算