tx3i 发布的帖子

没有，roi能打印在图现上，我怀疑roi的11值11不稳定，导致报错，如果是超出，是不是因为我设置了窗口的大小sensor.set_windowing((160, 120))

你这个i+1写哪在

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

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.set_auto_whitebal(False)
sensor.set_auto_gain(False)
#sensor.set_windowing((160, 120))
sensor.skip_frames(time = 2000)
clock = time.clock()
uart = UART(3, 9600)

#阈值设置
color = (0, 43, -128, 127, -128, 127)
mode = 0
rois = []



#------------------------------定义缩小四边形函数

def shrink_rect(corners, shrink_by):
    # 计算中心点
    cx = int(sum(p[0] for p in corners) / len(corners))
    cy = int(sum(p[1] for p in corners) / len(corners))
    # 缩小每个顶点
    new_corners = []
    for p in corners:
        dx = p[0] - cx
        dy = p[1] - cy
        distance = math.sqrt(dx * dx + dy * dy)
        scale = (distance - shrink_by) / distance if distance > 0 else 0
        new_x = int(cx + dx * scale)
        new_y = int(cy + dy * scale)
        new_corners.append((new_x, new_y))
    return new_corners, cx, cy



#------------------------------求两点中点坐标

def Make_dian(new_xy):
    mid2x = abs((new_xy[2][0] + new_xy[3][0]) / 2)
    mid4x = abs((new_xy[3][0] + new_xy[0][0]) / 2)
    mid6x = abs((new_xy[2][0] + new_xy[1][0]) / 2)
    mid8x = abs((new_xy[1][0] + new_xy[0][0]) / 2)

    mid2y = abs((new_xy[2][1] + new_xy[3][1]) / 2)
    mid4y = abs((new_xy[3][1] + new_xy[0][1]) / 2)
    mid6y = abs((new_xy[2][1] + new_xy[1][1]) / 2)
    mid8y = abs((new_xy[1][1] + new_xy[0][1]) / 2)

    newmid = [int(mid2x), int(mid2y),int(mid4x), int(mid4y), int(mid6x), int(mid6y), int(mid8x), int(mid8y)]
#    print(newmid)
    return newmid


#def find_rois(max_rect):


#def color_blob(color, roi_r):

#    for blobs in img.find_blobs([color], pixels_threshold=100, area_threshold=100):
#        if blobs:
#            cx = blobs.cx()
#            cy = blobs.cy()
#            img.draw_cross(cx,cy,color= (255,255,255))
#            return cx,cy



#-----------------------------通过面积进行识别最大的矩形

def find_max_rect():
    max_rect = None #初始化返回的最大矩形
    rect_max_w = 0  #通过比较矩形的面积来判断矩形大小
    rect_max_h = 0
    for black_rect in img.find_rects(threshold = 25000):
        if (black_rect.w()*black_rect.h()) > (rect_max_w*rect_max_h):
            rect_max_w = black_rect.w()
            rect_max_h = black_rect.h()
            max_rect = black_rect
#            print(max_rect)
            return max_rect


#------------------------------------画矩形---------------------------------#

def four_corners_draw(a):
    img.draw_line(a[0][0], a[0][1], a[1][0], a[1][1], (255, 0, 0), 1)
    img.draw_line(a[1][0], a[1][1], a[2][0], a[2][1], (255, 0, 0), 1)
    img.draw_line(a[2][0], a[2][1], a[3][0], a[3][1], (255, 0, 0), 1)
    img.draw_line(a[3][0], a[3][1], a[0][0], a[0][1], (255, 0, 0), 1)
#    print(a)


while(True):
    clock.tick()
    img = sensor.snapshot()

    max1_rect = find_max_rect()


    if max1_rect:
        mode = 1
        img.draw_rectangle(max1_rect.rect(), color=(255, 0, 0))
        a = max1_rect.corners()
        four_corners_draw(a)                                        #画矩形
#        print(a)

        new_xy, cx, cy =  shrink_rect(max1_rect.corners(), 10)     #计算等比例矩形
        new0_xy =new_xy           #打印四角点7 9 3 1
#        print(new0_xy)

        newmid = Make_dian(new_xy)
#        print(newmid)                       #打印2，4，6，8 点

#        for w in range(0,7,2):
#            img.draw_cross(newmid[w],newmid[w+1],5,color=(255,0,0))
#        img.draw_cross(cx, cy, 5, color=(255, 0, 0))               #画出中心点
#        for new1 in new_xy:
#            img.draw_cross(new1[0], new1[1], 5, color=(255, 0, 0)) #画出缩小后矩形的点（十字）
#            print(new1)

#------------------------棋盘坐标9点


    




    if mode == 1:
        #------棋盘1---------------------------棋盘2------------------棋盘3--------------------------棋盘4
        data = [new0_xy[3][0], new0_xy[3][1], newmid[0], newmid[1], new0_xy[2][0], new0_xy[2][1], newmid[2], newmid[3],
       #棋盘5---棋盘6------------------棋盘7--------------------------棋盘8-----------------棋盘9
        cx, cy, newmid[4], newmid[5], new0_xy[0][0], new0_xy[0][1], newmid[6], newmid[7], new0_xy[1][0], new0_xy[1][1]]
        print(data)
        rois = [(data[0]-2,data[1]-2,5,5),
                (data[2]-2,data[3]-2,5,5),
                (data[4]-2,data[5]-2,5,5),
                (data[6]-2,data[7]-2,5,5),
                (data[8]-2,data[9]-2,5,5),
                (data[10]-2,data[11]-2,5,5),
                (data[12]-2,data[13]-2,5,5),
                (data[14]-2,data[15]-2,5,5),
                (data[16]-2,data[17]-2,5,5),]
        for r in rois :
            img.draw_rectangle(r,color = (255,255,255))
            for blobs in img.find_blobs([(10, 0, -76, 114, -118, 99)],roi = r):
                img.draw_cross(blobs.cx(),blobs.cy())
            
        mode = 2


##-----------------------更新棋盘上的落子---------------

       
#            for t in range(0,8):
#                for blobs in img.find_blobs([(10, 0, -76, 114, -118, 99)], roi=rois[t]):
#                    img.draw_cross(blobs.cx(), blobs.cy(),color = (0,255,0))
#                    print(blobs.cx(), blobs.cy())
#    if mode == 2:
        
#        for t in range(0,8):
#           for blobs in img.find_blobs([(10, 0, -76, 114, -118, 99)], roi=rois[t]):
#                img.draw_cross(blobs.cx(), blobs.cy(),color = (0,255,0))
#                print(blobs.cx(), blobs.cy())