# Measure the distance
#
# This example shows off how to measure the distance through the size in imgage
# This example in particular looks for yellow pingpong ball.

import sensor, image, time

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
yellow_threshold   = (33, 96, -34, 42, -13, 28)
# You may need to tweak the above settings for tracking green things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

K=3920 #the value should be measured

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

    blobs = img.find_blobs([yellow_threshold])
    if len(blobs) == 1:
        # Draw a rect around the blob.
        b = blobs[0]
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy
        Lm = (b[2]+b[3])/2
        length = K/Lm
        print(length)
        #print(Lm)请在这里粘贴代码

而且使用上面的例程，摄像头捕捉到的是整个显示框，不是物体大小的size

使用这个例程之后，移动物体与摄像头之间的距离，串口返回的数值不变的，这是为什么？

# Measure the distance
#
# This example shows off how to measure the distance through the size in imgage
# This example in particular looks for yellow pingpong ball.

import sensor, image, time

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
yellow_threshold   = (33, 96, -34, 42, -13, 28)
# You may need to tweak the above settings for tracking green things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

K=3920 #the value should be measured

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

    blobs = img.find_blobs([yellow_threshold])
    if len(blobs) == 1:
        # Draw a rect around the blob.
        b = blobs[0]
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy
        Lm = (b[2]+b[3])/2
        length = K/Lm
        print(length)
        #print(Lm)

    #print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
    # connected to your computer. The FPS should increase once disconnected.请在这里粘贴代码

寻找最大的矩形

沿矩形边框绘制线条

import sensor, image, time

相机初始化

sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE) # 设置图像格式为灰度
sensor.set_framesize(sensor.QQQVGA) # 设置图像大小
sensor.skip_frames(time=2000) # 等待设置生效
clock = time.clock() # 用于跟踪帧率

while(True):
clock.tick()
img = sensor.snapshot().lens_corr(1.8)

# 使用find_rects()方法寻找图像中的矩形
rects = img.find_rects(threshold = 10000)

# 初始化变量来存储最大矩形的信息
max_area = 0
max_rect = None

# 遍历所有找到的矩形，找出面积最大的矩形
for rect in rects:
    # 计算当前矩形的面积
    area = rect.w() * rect.h()
    # 如果当前矩形的面积大于之前记录的最大面积，则更新最大矩形和最大面积
    if area > max_area:
        max_area = area
        max_rect = rect

# 如果找到了最大的矩形，则绘制它的边框
if max_rect:
    corners = max_rect.corners()    # 获取最大矩形的四个角点
    # 绘制最大矩形的四条边
    for i in range(len(corners)):
        start_point = corners[i]
        end_point = corners[(i+1) % 4]
        img.draw_line(start_point[0], start_point[1], end_point[0], end_point[1], color = 255)

    print(corners)

为什么openmv不能进行物体距离测量

import sensor, image, time

# 此处通过识别物体的颜色来测大小
target_threshold = (91, 65, -15, 33, 89, 47)   # 此处以黄色为例

K = 0.07                                  # 当测另一个物体的大小时，需要将该物体放在求比例系数K时的那个距离处，此处我们使用的是10cm处
# 实际大小 = 直径的像素 * K。
# 第一次时，可以将小球放在距离摄像头10cm处的位置，测得Lm的大小之后，K = 实际大小 / Lm
# 比如在10cm处时，直径的像素为43，小球实际大小为3cm，则K = 3 / 43 = 0.07，具体情况以你的实际情况为准

# 初始化函数
def init_setup():
    global sensor, clock                  # 设置为全局变量
    sensor.reset()                        # 初始化感光元件
    sensor.set_pixformat(sensor.RGB565)   # 将图像格式设置为彩色
    sensor.set_framesize(sensor.QQVGA)    # 将图像大小设置为160x120
    sensor.skip_frames(10)                # 跳过10帧，使以上设置生效
    sensor.set_auto_whitebal(False)       # 关闭白平衡
    clock = time.clock()                  # 创建时钟对象

# 主函数
def main():
    while 1:
        clock.tick()                      # 更新FPS帧率时钟
        img = sensor.snapshot()           # 拍一张照片并返回图像

        blobs = img.find_blobs([target_threshold])  # 找到图像中的目标区域
        if len(blobs) == 1:
            b = blobs[0]
            img.draw_rectangle(b[0:4])    # 将目标区域框出来
            img.draw_cross(b[5], b[6])    # 在目标中心位置画十字
            Lm = (b[2]+b[3])/2            # 获取像素点
            w = K * b[2]                  # 通过比例系数K和像素值得到物体实际宽度
            h = K * b[3]                  # 通过比例系数K和像素值得到物体实际高度
            print('物体实际宽度为 %s cm' % w)  # 打印物体实际宽度值
            print('物体实际高度为 %s cm' % h)  # 打印物体实际高度值
            #print(Lm)                     # 打印像素点数，在你对一个新的物体进行测大小时，需要将该物体放在求比例系数K时的那个距离处，此处我们使用的是10cm处
        #print(clock.fps())              # 打印帧率，注:实际FPS更高，流FB使它更慢。

# 程序入口
if __name__ == '__main__':
    init_setup()  # 执行初始化函数
    try:
        main()    # 执行主函数
    except:
        pass