if uart.any():我试过，但是我看不到效果
if uart.any():
#uart.write("132")
#time.sleep(10)
#print(uart.read(1))
imgtarget=uart.read(1)

顶一下，我也想知道，

@kidswong999 在else里面啊，请问有没有外部给openmv串口通信，openmv接受的程序？并且可以处理字符

@yuan@网红小智智

@kidswong999 您好，在我的另一个问题里面变了（我贴代码了），这个没变，是因为我测但物体的时候，会出现kpts100 =0进不了if语句的情况，，但是我觉得语法没什么问题，不就是用退格代替大括号嘛

1我的目的是通过例程特征点检测保存和特征点检测完成已经4个物体的分别识别
2通过串口3将物体x，y坐标发到另一块32（电脑上位机也行）
3还想通过上位机发送字符来改变识别哪一个物体
4问题在于加了串口输出后特征点扫瞄函数返回的kpts10的赋值函数不稳定，会返回0也就是kpts10=0
5加了串口输入之后程序只能找1次特征点，这一次是对的，打到上位机上，没有后来了，图像还在更新
6贴两个代码，第一个可用，可以输出，但是个别情况卡死（kpts10=0）。第二个·是目标函数，错的。

# Object tracking with keypoints example.
# Show the camera an object and then run the script. A set of keypoints will be extracted
# once and then tracked in the following frames. If you want a new set of keypoints re-run
# the script. NOTE: see the docs for arguments to tune find_keypoints and match_keypoints.
import sensor, time, image
from pyb import UART
import json
# Reset sensor
sensor.reset()

# Sensor settings
sensor.set_contrast(3)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((320, 240))
sensor.set_pixformat(sensor.GRAYSCALE)

sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False, value=100)
uart = UART(3, 115200)
def draw_keypoints(img, kpts):
    if kpts:
        print(kpts)
        img.draw_keypoints(kpts)
        img = sensor.snapshot()
        time.sleep(1000)
imgtarget=2
kpts1 = None
# NOTE: uncomment to load a keypoints descriptor from file
kpts1 = image.load_descriptor("/yxxjqr1.orb")
kpts2 = image.load_descriptor("/yxxjqr2.orb")
kpts3 = image.load_descriptor("/yxxjqr3.orb")
kpts4 = image.load_descriptor("/yxxjqr4.orb")
img = sensor.snapshot()
#draw_keypoints(img, kpts1)
uart = UART(3, 115200)
clock = time.clock()
while (True):
    clock.tick()
    img = sensor.snapshot()
    if (kpts1 == None):
        # NOTE: By default find_keypoints returns multi-scale keypoints extracted from an image pyramid.
        kpts1 = img.find_keypoints(max_keypoints=150, threshold=10, scale_factor=1.2)
        draw_keypoints(img, kpts1)
    else:
        # NOTE: When extracting keypoints to match the first descriptor, we use normalized=True to extract
        # keypoints from the first scale only, which will match one of the scales in the first descriptor.
        kpts100 = img.find_keypoints(max_keypoints=150, threshold=10, normalized=1)
        if (kpts100):
            if (imgtarget==1) :
                match = image.match_descriptor(kpts1, kpts100, threshold=85)
            elif (imgtarget==2) :
                match = image.match_descriptor(kpts2, kpts100, threshold=85)
            elif (imgtarget==3) :
                match = image.match_descriptor(kpts3, kpts100, threshold=85)
            elif (imgtarget==4) :
                match = image.match_descriptor(kpts4, kpts100, threshold=85)
            if (match.count()>10):
                # If we have at least n "good matches"
                # Draw bounding rectangle and cross.
                #img.draw_rectangle(match.rect())
                img.draw_cross(match.cx(), match.cy(), size=10)
                output_str="[%d,%d]" % (match.cx(),match.cy())
                uart.write(output_str+'\r\n')
                print(kpts100, "matched:%d dt:%d"%(match.count(), match.theta()))
            # NOTE: uncomment if you want to draw the keypoints
            #img.draw_keypoints(kpts2, size=KEYPOINTS_SIZE, matched=True)

    # Draw FPS
    img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))

# Object tracking with keypoints example.
# Show the camera an object and then run the script. A set of keypoints will be extracted
# once and then tracked in the following frames. If you want a new set of keypoints re-run
# the script. NOTE: see the docs for arguments to tune find_keypoints and match_keypoints.
import sensor, time, image
from pyb import UART
import json
# Reset sensor
sensor.reset()

# Sensor settings
sensor.set_contrast(3)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((320, 240))
sensor.set_pixformat(sensor.GRAYSCALE)

sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False, value=100)
def draw_keypoints(img, kpts):
    if kpts:
        print(kpts)
        img.draw_keypoints(kpts)
        img = sensor.snapshot()
        time.sleep(1000)
imgtarget='2'
kpts1 = None
# NOTE: uncomment to load a keypoints descriptor from file
kpts1 = image.load_descriptor("/yxxjqr1.orb")
kpts2 = image.load_descriptor("/yxxjqr2.orb")
kpts3 = image.load_descriptor("/yxxjqr3.orb")
kpts4 = image.load_descriptor("/yxxjqr4.orb")
img = sensor.snapshot()
#draw_keypoints(img, kpts1)
uart = UART(3, 115200)
clock = time.clock()
while (True):
    clock.tick()
    img = sensor.snapshot()
    if (kpts1 == None):
        # NOTE: By default find_keypoints returns multi-scale keypoints extracted from an image pyramid.
        kpts1 = img.find_keypoints(max_keypoints=150, threshold=10, scale_factor=1.2)
        draw_keypoints(img, kpts1)
    else:
        # NOTE: When extracting keypoints to match the first descriptor, we use normalized=True to extract
        # keypoints from the first scale only, which will match one of the scales in the first descriptor.
        kpts100 = img.find_keypoints(max_keypoints=150, threshold=10, normalized=1)
        if (kpts100):
            if (imgtarget=='1') :
                match = image.match_descriptor(kpts1, kpts100, threshold=85)
            elif (imgtarget=='2') :
                match = image.match_descriptor(kpts2, kpts100, threshold=85)
            elif (imgtarget=='3') :
                match = image.match_descriptor(kpts3, kpts100, threshold=85)
            elif (imgtarget=='4') :
                match = image.match_descriptor(kpts4, kpts100, threshold=85)
            if (match.count()>10):
                # If we have at least n "good matches"
                # Draw bounding rectangle and cross.
                #img.draw_rectangle(match.rect())
                img.draw_cross(match.cx(), match.cy(), size=10)
                output_str="[%d,%d]" % (match.cx(),match.cy())
                uart.write(output_str+'\r\n')
                print(kpts100, "matched:%d dt:%d"%(match.count(), match.theta()))
            # NOTE: uncomment if you want to draw the keypoints
            #img.draw_keypoints(kpts2, size=KEYPOINTS_SIZE, matched=True)
    #imgtarget=uart.readchar()
    # Draw FPS
    if uart.any():
        #uart.write("132")
        #time.sleep(10)
        #print(uart.read(1))
        imgtarget=uart.read(1)
    img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))

# Object tracking with keypoints example.
# Show the camera an object and then run the script. A set of keypoints will be extracted
# once and then tracked in the following frames. If you want a new set of keypoints re-run
# the script. NOTE: see the docs for arguments to tune find_keypoints and match_keypoints.
import sensor, time, image
from pyb import UART
import json
# Reset sensor
sensor.reset()

# Sensor settings
sensor.set_contrast(3)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((320, 240))
sensor.set_pixformat(sensor.GRAYSCALE)

sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False, value=100)

def draw_keypoints(img, kpts):
    if kpts:
        print(kpts)
        img.draw_keypoints(kpts)
        img = sensor.snapshot()
        time.sleep(1000)
imgtarget=4
kpts1 = None
# NOTE: uncomment to load a keypoints descriptor from file
kpts1 = image.load_descriptor("/yxxjqr1.orb")
kpts2 = image.load_descriptor("/yxxjqr2.orb")
kpts3 = image.load_descriptor("/yxxjqr3.orb")
kpts4 = image.load_descriptor("/yxxjqr4.orb")
img = sensor.snapshot()
#draw_keypoints(img, kpts1)
uart = UART(3, 115200)
clock = time.clock()
while (True):
    clock.tick()
    img = sensor.snapshot()
    if (kpts1 == None):
        # NOTE: By default find_keypoints returns multi-scale keypoints extracted from an image pyramid.
        kpts1 = img.find_keypoints(max_keypoints=150, threshold=10, scale_factor=1.2)
        draw_keypoints(img, kpts1)
    else:
        # NOTE: When extracting keypoints to match the first descriptor, we use normalized=True to extract
        # keypoints from the first scale only, which will match one of the scales in the first descriptor.
        kpts100 = img.find_keypoints(max_keypoints=150, threshold=10, normalized=True)
        if (kpts100):
            if (imgtarget==1) :
                match = image.match_descriptor(kpts1, kpts100, threshold=85)
            elif (imgtarget==2) :
                match = image.match_descriptor(kpts2, kpts100, threshold=85)
            elif (imgtarget==3) :
                match = image.match_descriptor(kpts3, kpts100, threshold=85)
            elif (imgtarget==4) :
                match = image.match_descriptor(kpts4, kpts100, threshold=85)
            if (match.count()>10):
                # If we have at least n "good matches"
                # Draw bounding rectangle and cross.
                #img.draw_rectangle(match.rect())
                img.draw_cross(match.cx(), match.cy(), size=10)
                output_str="[%d,%d]" % (match.cx(),match.cy())
                uart.write(output_str+'\r\n')

            print(kpts100, "matched:%d dt:%d"%(match.count(), match.theta()))
            # NOTE: uncomment if you want to draw the keypoints
            #img.draw_keypoints(kpts2, size=KEYPOINTS_SIZE, matched=True)

    # Draw FPS
    #img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))
    time.sleep(10)

就是传图没事，寻找特征点的程序，kpts10=（）这里执行几次就会不再执行，或者值恒为零，进不了if。如果去掉uart可以持续执行