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• # 请问这段代码中line.x1 ()*r 这里的*r后得到的结果有什么具体含义吗？

• ``````ROIS = [ # [ROI, weight]
(0, 0, 80, 120, 0.5), # You'll need to tweak the weights for you app
(80, 0, 80, 120, 0.5) # depending on how your robot is setup.
]
weight_sum = 0 #权值和初始化
#for r in ROIS: weight_sum += r # r is the roi weight.A
#计算权值和。遍历上面的三个矩形，r即每个矩形的权值。
# This is called the fast linear regression because we use the least-squares
# method to fit the line. However, this method is NOT GOOD FOR ANY images that
# have a lot (or really any) outlier points which corrupt the line fit...

#设置阈值，（0，100）检测黑色线
THRESHOLD = (0, 100) # Grayscale threshold for dark things...

#设置是否使用img.binary()函数进行图像分割
BINARY_VISIBLE = True # Does binary first so you can see what the linear regression
# is being run on... might lower FPS though.

import sensor, image, time
import json
from pyb import UART
uart = UART(3, 9600)
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

while(True):
clock.tick()
img = sensor.snapshot().binary([THRESHOLD]) if BINARY_VISIBLE else sensor.snapshot()
centroid_sum = 0
for r in ROIS:
blobs = img.find_blobs(THRESHOLD , roi=r[0:2], merge=True)
# Returns a line object similar to line objects returned by find_lines() and
# find_line_segments(). You have x1(), y1(), x2(), y2(), length(),
# theta() (rotation in degrees), rho(), and magnitude().
#
# magnitude() represents how well the linear regression worked. It goes from
# (0, INF] where 0 is returned for a circle. The more linear the
# scene is the higher the magnitude.
#函数返回回归后的线段对象line，有x1(), y1(), x2(), y2(), length(), theta(), rho(), magnitude()参数。
#x1 y1 x2 y2分别代表线段的两个顶点坐标，length是线段长度，theta是线段的角度。
#magnitude表示线性回归的效果，它是（0，+∞）范围内的一个数字，其中0代表一个圆。如果场景线性回归的越好，这个值越大。
line = img.get_regression([(255,255) if BINARY_VISIBLE else THRESHOLD])
if (line): img.draw_line(line.line(), color = 127)
arveage_x1 += line.x1 ()*r
arveage_x2 += line.x2 ()*r
arveage_y1 += line.y1 ()*r
arveage_y2 += line.y2 ()*r
arveage_theta += line.theta()*r
img.draw_line(arveage_x1,arveage_y1,arveage_x2,arveage_y2, color = 80)
print("FPS %f, mag = %s" % (clock.fps(), str(line.magnitude()) if (line) else "N/A"))

#
# A [theta+0:-rho] tuple is the same as [theta+180:+rho].
data_out = str(line.theta())
uart.write(data_out )
time.sleep(100)
print("OUT",data_out)
``````

• 注释r中说r为每个矩形的权值，但我仍然不理解坐标乘以权值能得到什么，或者说有什么含义？

• 这个代码是什么地方的？