openmv无法更新程序，有可能是什么问题呢？具体表现为：在IDE中可以运行程序，也能成功保存，一旦掉电后重新裸机运行，就是默认程序，打开H盘的main.py也是默认的程序

# 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)

# Load template.
# Template should be a small (eg. 32x32 pixels) grayscale image.
template = image.Image("/1.pgm")

clock = time.clock()

# 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.
    r = img.find_template(template, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
    if r:
        img.draw_rectangle(r)

    print(clock.fps())

@kidswong999 感谢解惑，有没有可能是频繁链接或断开IDE所导致的呢？

你好，我在进行颜色识别的过程中发现openmv会不时卡住，请问这是什么原因呢？自己猜想，是不是跟自己在同个图像中进行了两次分区域识别有关，希望有知道的大佬指点一下，另外，在卡住之后图像会直接与摄像头断开连接，这个问题非常致命！

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

sensor.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.
sensor.skip_frames(10) # Let new settings take affect.
#sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False)
sensor.set_vflip(True)
clock = time.clock() # Tracks FPS.

#初始化
uart = UART(3, 115200)

color_threshold1 = (0, 255, -40, -20, 10, 35)
color_threshold2 = (0, 255, -40, -20, 10, 35)

date1=0
date2=100

while(True):
    flag1=1
    flag2=0
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.

    #查看是否检测到了绿色基座
    blobs = img.find_blobs([color_threshold1],roi=[40,60,80,60], area_threshold=300)

    if blobs:   #如果找到了目标颜色
        for blob in blobs:  #迭代找到的目标颜色区域

            is_rect = 0
            rect_s=0
            max_s = -1

            for c in img.find_rects():

                is_rect = 1
                rect_s=c.y()*c.h()

                if rect_s > max_s:

                    max_s = rect_s
                    max_rect = c

            if is_rect:

                flag2=1
                img.draw_rectangle(blob.rect()) # rect # 如果有对应颜色的矩形 标记外框
                img.draw_cross(blob[5], blob[6]) # cx, cy  画出十字
                date1=int(blob.cx()-80)


    #查看是否检测到了水稻
    blobs=img.find_blobs([color_threshold2],roi=[40,0,80,60],x_stride=10,y_stride=10,area_threshold=500,merge=True,pixels_threshold=50)

    if blobs:
        flag1=0
        max_blob=-1
        mblob=0
        for blob in blobs:
            if blob.area()>max_blob:
                mblob=blob

        img.draw_rectangle(mblob.rect()) # rect


    if (flag1 and flag2):
        date=bytearray([0xDD,date1,0XDF])
        print(date1)
        #uart.write(date)
        flag1=1
        flag2=0
    else:
        date=bytearray([0xDD,date2,0XDF])
        print(date2)
        #uart.write(date)
        flag1=1
        flag2=0
        
    #print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while

@kidswong999 嗯，多谢解惑呀

我在把颜色识别和形状识别结合在一起的时候，发现可能是像素点太少的缘故，当距离较远或者角度不正的时候，会识别失败，所以想把QQVGA换成VGA,但是它会报错如下，有人知道怎么才能使用VGA模式吗？我用的7725v3和stm32H7芯片，所以不用担心处理速度的问题。

import sensor, image, time
color_threshold1 = (0, 255, 40, 80, 40, 70)
color_threshold2 = (0, 130, 40, 80, 40, 70)

sensor.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.

sensor.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.

#扩宽roi
def expand_roi(roi):

    # set for QQVGA 160*120

    extra = 5

    win_size = (160, 120)

    (x, y, width, height) = roi

    new_roi = [x-extra, y-extra, width+2*extra, height+2*extra]



    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)



while(True):

    clock.tick() # Track elapsed milliseconds between snapshots().

    img = sensor.snapshot() # Take a picture and return the image.

    #  pixels_threshold=100, area_threshold=100

    blobs = img.find_blobs([color_threshold1], area_threshold=150)



    if blobs:

    #如果找到了目标颜色

        print(blobs)

        for blob in blobs:

        #迭代找到的目标颜色区域

            is_rect = 0

            rect_s=0

            max_s = -1


            new_roi = expand_roi(blob.rect())


            for c in img.find_rects():

                is_rect = 1

                rect_s=c.y()*c.h()
                # img.draw_rectangle(x,y,w,h [,color[,thickness=1[,fill=False]]])

                if rect_s > max_s:

                    max_s = rect_s

                    max_rect = c

            if is_rect:

                # 如果有对应颜色的矩形 标记外框

                img.draw_rectangle(new_roi) # rect

                img.draw_rectangle(blob.rect()) # rect

                #用矩形标记出目标颜色区域

                img.draw_cross(blob[5], blob[6]) # cx, cy

                img.draw_rectangle(max_rect.x(), max_rect.y(), max_rect.w(),  max_rect.h(),color = (0, 255, 0))

                img.draw_rectangle(max_rect.x()-1, max_rect.y()-1, max_rect.w()+2,  max_rect.h()+2,color = (0, 255, 0))





    print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while

    # connected to your computer. The FPS should increase once disconnected.
![0_1563880779720_1.PNG](https://fcdn.singtown.com/55dd819e-826d-4e91-a4ac-083e8576c64b.PNG) 

@kidswong999 谢谢提示，我试试哦

帮顶，我也需要解决这个问题

之前在使用openMv的时候就发现，不同光照条件对颜色识别的影响很大，所以我在减少光照对颜色识别的影响的方法，望知道的高手指点一下，目前准备用ov7725V3和stm32h7来运行