线段识别问题：在图像上画一条直线之后识别这条直线，设置阈值为什么没有作用？

[z5l4]

thresholds = (35, 79)

sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.VGA)
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock = time.clock()

# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" merges all overlapping blobs in the image.

while(True):
    i=0 # 定义变量i，色块个数
    thresholds = (35, 79)#第一次查找阈值
    clock.tick()
    img = sensor.snapshot()
    for blob in img.find_blobs([thresholds],roi = [120,62,359,300], pixels_threshold=300, area_threshold=100, merge=True):#pixels像素个数阈值，area返回色块边框面积阈值(w * h)，merge=True多种颜色时显示一个框框

        img.draw_rectangle(120,62, 359, 300, color=127)# 在图像上绘制ROI区域
        # These values depend on the blob not being circular - otherwise they will be shaky.
        if blob.elongation() > 0.5:
            #img.draw_edges(blob.min_corners(), color=255)# 返回的角列表之间绘制线边
            img.draw_line(blob.major_axis_line(), color=153)# 返回blob的主轴(这条线穿过最小面积矩形的最长边)的行元组(x1, y1, x2, y2)，可以使用 image.draw_line() 来绘制它。
            #img.draw_line(blob.minor_axis_line(), color=0)#返回blob的次轴(这条线穿过最小面积矩形的最短边)的行元组(x1, y1, x2, y2)，可以使用 image.draw_line() 来绘制它。
            print('I长比 %s'%blob.elongation)

        # These values are stable all the time.
        #img.draw_rectangle(blob.rect(), color=200)# 在图像上绘制一个矩形。 您可以单独传递x，y，w，h或作为元组(x，y，w，h)传递。
        #img.draw_cross(blob.cx(), blob.cy(), color=227)# 在图像上绘制一个十字
        # Note - the blob rotation is unique to 0-180 only.
        #img.draw_keypoints([(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=40, color=1)
        #绘制圆，size 控制特征点的大小，将 fill 设置为True以填充特征点，
        #print(blob.cx())#逐个打印色块中心坐标
        #print(blob.cy())#
        #print('框高%s'%blob.h())#打印刀头高度

        #在特定roi找到坡口中心位置
        shang =0 # blob.x()  blob.y() 宽blob.w() 高blob.h()
        xia = 0
        zuo = 0
        you = 0
        shang = blob.x()-5
        zuo = blob.y()-5
        xia = blob.h()+5+5
        you = blob.w()+5+5
        #print('框xia %s'%xia)
        #print('框shang %s'%shang)
        #print('框X %s'%blob.x())
        #print('框y %s'%blob.y())
        k=0 # 定义变量k

        thresholds = (0, 39)# 第二次筛选阈值
        i——cx = blob.cx()
        i——cy = blob.cy()



        for blob in img.find_blobs([thresholds],roi = [shang,zuo,you,xia], pixels_threshold=75, area_threshold=10, merge=True):#pixels像素个数阈值，area返回色块边框面积阈值(w * h)，merge=True多种颜色时显示一个框框
            #img.draw_rectangle(shang,zuo,you,xia, color=15) # 在图像上绘制第二次ROI区域
            #if blob.elongation() > 0.5:#越像圆，这个值越小，越不像圆，这个值越大。
            #img.draw_edges(blob.min_corners(), color=255)# 返回的角列表之间绘制线边
                #img.draw_line(blob.major_axis_line(), color=233)# 返回blob的主轴(这条线穿过最小面积矩形的最长边)的行元组(x1, y1, x2, y2)，可以使用 image.draw_line() 来绘制它。

            #img.draw_rectangle(blob.rect(), color=227)# 在图像上绘制一个矩形。 您可以单独传递x，y，w，h或作为元组(x，y，w，h)传递。
            #img.draw_cross(blob.cx(), blob.cy(), color=227)# 在图像上绘制一个十字
            k=k+1
            k——cx = blob.cx()
            k——cy = blob.cy()
        i=i+1 # 每个色块加1
        #print('k数量 %s'%k) # k色块个数

        #过滤掉距离近的

        #在坡口中心至刀头中心画一条直线
        img.draw_line((k——cx, k——cy, i——cx, i——cy))# 画白线
        #img.draw_line((80, 50, 100, 100), color=(255,0,0))# 画红线

#确定线的朝向/角度
    thresholds = (200, 255) # 第三次筛选阈值
    #img = sensor.snapshot()
    j = 0 # 定义线段数量
    #if enable_lens_corr: img.lens_corr(1.8) # 镜头畸变矫正
    for l in img.find_line_segments( roi = [120,62,359,300], merge_distance=-5, max_theta_difference=-5):#`threshold`控制从霍夫变换中监测到的直线。只返回大于或等于阈值的直线

        img.draw_line(l.line(), color=200)
        #img.draw_line(x0, y0, x1, y1[, color[, thickness=1]])
        j += 1
        #print('打印l %s'%l)
    print('线段数量 %s'%j)![0_1671399275661_snipaste_20221219_053423.jpg](https://fcdn.singtown.com/0dca2393-0287-4561-9bce-7a226f7f1c5a.jpg) 
```![0_1671399329158_snipaste_20221219_053423.jpg](https://fcdn.singtown.com/d9adb9b6-db41-4730-9c86-f6d6166b0eff.jpg)

[z5l4]

[z5l4]

请大神指教，怎样识别物体上画出的白色线段

[kidswong999]

可以识别：

enable_lens_corr = False # turn on for straighter lines...

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # grayscale is faster
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

# All lines also have `x1()`, `y1()`, `x2()`, and `y2()` methods to get their end-points
# and a `line()` method to get all the above as one 4 value tuple for `draw_line()`.

while(True):
    clock.tick()
    img = sensor.snapshot()
    if enable_lens_corr: img.lens_corr(1.8) # for 2.8mm lens...

    # `merge_distance` controls the merging of nearby lines. At 0 (the default), no
    # merging is done. At 1, any line 1 pixel away from another is merged... and so
    # on as you increase this value. You may wish to merge lines as line segment
    # detection produces a lot of line segment results.

    # `max_theta_diff` controls the maximum amount of rotation difference between
    # any two lines about to be merged. The default setting allows for 15 degrees.
    
    img.draw_line(10,10,100,100,(0,0,0))
    

    for l in img.find_line_segments(merge_distance = 0, max_theta_diff = 5):
        img.draw_line(l.line(), color = (255, 0, 0))
        # print(l)

    print("FPS %f" % clock.fps())

另外你识别你画的直线做什么？这是已知的啊。