红线左边识别到数字发送L，右边识别到数字发送R

dymb

或者说识别到多数字时怎么判断想要的数字是在左边还是右边

kidswong999

@dymb 在红线左边识别到数字发送L，右边识别到数字发送R 中说：

或者说识别到多数字时怎么判断想要的数字是在左边还是右边

一般是通过x坐标判断。

dymb

@kidswong999 哦哦已经想到了用坐标，但是不知道用什么语句

kidswong999

@dymb 你先发一下你的代码。我看看你用的什么算法。

dymb

@kidswong999 # Template Matching Example - Normalized Cross Correlation (NCC)

#
# This example shows off how to use the NCC feature of your OpenMV Cam to match
# image patches to parts of an image... expect for extremely controlled enviorments
# NCC is not all to useful.
#
# WARNING: NCC supports needs to be reworked! As of right now this feature needs
# a lot of work to be made into somethin useful. This script will reamin to show
# that the functionality exists, but, in its current state is inadequate.

import time, sensor, image
from image import SEARCH_EX, SEARCH_DS

# Reset sensor
sensor.reset()

# Set sensor settings
sensor.set_contrast(1)
sensor.set_gainceiling(16)
# Max resolution for template matching with SEARCH_EX is QQVGA
sensor.set_framesize(sensor.QQVGA)
# You can set windowing to reduce the search image.
#sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60))
sensor.set_pixformat(sensor.GRAYSCALE)
from pyb import UART
uart = UART(3, 115200)
# Load template.
# Template should be a small (eg. 32x32 pixels) grayscale image.
template1 = image.Image("/1.pgm")
template2 = image.Image("/2.pgm")

clock = time.clock()
flag=0

# Run template matching
while (True):
    clock.tick()
    img = sensor.snapshot()



    # find_template(template, threshold, [roi, step, search])
    # ROI: The region of interest tuple (x, y, w, h).
    # Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster.
    # Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search
    #
    # Note1: ROI has to be smaller than the image and bigger than the template.
    # Note2: In diamond search, step and ROI are both ignored.



    
    if flag==0:
        r1 = img.find_template(template1, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
        r2 = img.find_template(template2, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
        if r1:
            img.draw_rectangle(r1)
            flag=1
        if r2:
            img.draw_rectangle(r2)
            flag=2
    print(clock.fps())

    if flag==1:
        uart.write("1")
        flag=999

    if flag==2:
        uart.write("2")
        flag=998
        
    r1 = img.find_template(template1, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
    r2 = img.find_template(template2, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
    if flag==999
        if r1:
            img.draw_rectangle(r1)
                if

dymb

@dymb 最下面是要开始判断左右了，但是不会，请求大佬帮助一下

kidswong999

r1 = img.find_template(template1, 0.70, step=4, search=SEARCH_EX)
cx = r1[0] + r1[2]/2

if cx < img.width()/2:
    print(左边)
else:
    print(右边)

6w3u

@kidswong999 大佬，cx=r1【0】+r1【2】/2出问题了

新发一个帖子，附上全部的代码。