4. 运行程序时报错咋处理
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    • 运行程序时报错咋处理

    • R

      从SD卡里导入文件进行特征点检测，提示运行内存不足，除了降低图片分辨率外，还有其他技巧可以解决这个问题吗？
      0_1590548509854_8cb4f6c44a18e6d14aad6c4ea263aca.png

      import sensor, time, image
from pid import PID
from pyb import Servo
pan_servo=Servo(1)
tilt_servo=Servo(2)
pan_pid = PID(p=0.10, i=0, imax=90)
tilt_pid = PID(p=0.10, i=0, imax=90)
sensor.reset()
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)
kpts1 = image.load_descriptor("/A1.orb")
kpts2 = image.load_descriptor("/A2.orb")
kpts3 = image.load_descriptor("/A3.orb")
kpts4 = image.load_descriptor("/A4.orb")
kpts5 = image.load_descriptor("/A5.orb")
kpts6 = image.load_descriptor("/A6.orb")
kpts7 = image.load_descriptor("/A7.orb")
kpts8 = image.load_descriptor("/A8.orb")
kpts9 = image.load_descriptor("/B1.orb")
kpts10 = image.load_descriptor("/B2.orb")
kpts11 = image.load_descriptor("/B3.orb")
kpts12 = image.load_descriptor("/B4.orb")
kpts13 = image.load_descriptor("/B5.orb")
kpts14 = image.load_descriptor("/B6.orb")
kpts15 = image.load_descriptor("/B7.orb")
kpts16 = image.load_descriptor("/B8.orb")
kpts17 = image.load_descriptor("/C1.orb")
kpts18 = image.load_descriptor("/C2.orb")
kpts19 = image.load_descriptor("/C3.orb")
kpts20 = image.load_descriptor("/C4.orb")
kpts21 = image.load_descriptor("/C5.orb")
kpts22 = image.load_descriptor("/C6.orb")
kpts23 = image.load_descriptor("/C7.orb")
kpts24 = image.load_descriptor("/C8.orb")
kpts25 = image.load_descriptor("/D1.orb")
kpts26 = image.load_descriptor("/D2.orb")
kpts27 = image.load_descriptor("/D3.orb")
kpts28 = image.load_descriptor("/D4.orb")
kpts29 = image.load_descriptor("/D5.orb")
kpts30 = image.load_descriptor("/D6.orb")
kpts31 = image.load_descriptor("/D7.orb")
kpts32 = image.load_descriptor("/D8.orb")
img = sensor.snapshot()
clock = time.clock()
while (True):
    clock.tick()
    img = sensor.snapshot()
    pan_servo.angle(0)
    time.sleep(200)
    tilt_servo.angle(-17)
    time.sleep(200)
    kptsA = img.find_keypoints(max_keypoints=150, threshold=10, normalized=True)
    if (kptsA):
        match1 = image.match_descriptor(kpts1, kptsA, threshold=85)
        match2 = image.match_descriptor(kpts2, kptsA, threshold=85)
        match3 = image.match_descriptor(kpts3, kptsA, threshold=85)
        match4 = image.match_descriptor(kpts4, kptsA, threshold=85)
        match5 = image.match_descriptor(kpts5, kptsA, threshold=85)
        match6 = image.match_descriptor(kpts6, kptsA, threshold=85)
        match7 = image.match_descriptor(kpts7, kptsA, threshold=85)
        match8 = image.match_descriptor(kpts8, kptsA, threshold=85)
        match9 = image.match_descriptor(kpts9, kptsA, threshold=85)
        match10 = image.match_descriptor(kpts10, kptsA, threshold=85)
        match11 = image.match_descriptor(kpts11, kptsA, threshold=85)
        match12 = image.match_descriptor(kpts12, kptsA, threshold=85)
        match13 = image.match_descriptor(kpts13, kptsA, threshold=85)
        match14 = image.match_descriptor(kpts14, kptsA, threshold=85)
        match15 = image.match_descriptor(kpts15, kptsA, threshold=85)
        match16 = image.match_descriptor(kpts16, kptsA, threshold=85)
        match17 = image.match_descriptor(kpts17, kptsA, threshold=85)
        match18 = image.match_descriptor(kpts18, kptsA, threshold=85)
        match19 = image.match_descriptor(kpts19, kptsA, threshold=85)
        match20 = image.match_descriptor(kpts20, kptsA, threshold=85)
        match21 = image.match_descriptor(kpts21, kptsA, threshold=85)
        match22 = image.match_descriptor(kpts22, kptsA, threshold=85)
        match23 = image.match_descriptor(kpts23, kptsA, threshold=85)
        match24 = image.match_descriptor(kpts24, kptsA, threshold=85)
        match25 = image.match_descriptor(kpts25, kptsA, threshold=85)
        match26 = image.match_descriptor(kpts26, kptsA, threshold=85)
        match27 = image.match_descriptor(kpts27, kptsA, threshold=85)
        match28 = image.match_descriptor(kpts28, kptsA, threshold=85)
        match29 = image.match_descriptor(kpts29, kptsA, threshold=85)
        match30 = image.match_descriptor(kpts30, kptsA, threshold=85)
        match31 = image.match_descriptor(kpts31, kptsA, threshold=85)
        match32 = image.match_descriptor(kpts32, kptsA, threshold=85)
        if (match1.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match2.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match3.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match4.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match5.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match6.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match7.count()>10):
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match8.count()>10):        
            pan_servo.angle(40)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)            
        elif (match9.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match10.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match11.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match12.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match13.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match14.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match15.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match16.count()>10):
            tilt_servo.angle(-47)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match17.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match18.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match19.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match20.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match21.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match22.count()>10):        
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match23.count()>10):        
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)
        elif (match24.count()>10):
            pan_servo.angle(-35)
            time.sleep(400)
            pan_servo.angle(0)
            time.sleep(400)            
        elif (match25.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match26.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match27.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match28.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match29.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match30.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match31.count()>10):        
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)
        elif (match32.count()>10):
            tilt_servo.angle(13)
            time.sleep(400)
            tilt_servo.angle(-17)
            time.sleep(400)    
        else :
            pan_servo.angle(0)
            time.sleep(200)
            tilt_servo.angle(-17)
            time.sleep(200)
        print(kptsA, "matched:%d dt:%d"%(match4.count(), match4.theta()))
    img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))
      0

    • 不要在一开始全部把特征点读取进来。内存不够。

      在循环里添加for循环。参考这个代码：https://book.openmv.cc/image/mulity-template-match.html

      0