mirror of
https://github.com/opencv/opencv.git
synced 2024-11-26 04:00:30 +08:00
105 lines
2.6 KiB
Python
Executable File
105 lines
2.6 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
'''
|
|
Robust line fitting.
|
|
==================
|
|
|
|
Example of using cv.fitLine function for fitting line
|
|
to points in presence of outliers.
|
|
|
|
Usage
|
|
-----
|
|
fitline.py
|
|
|
|
Switch through different M-estimator functions and see,
|
|
how well the robust functions fit the line even
|
|
in case of ~50% of outliers.
|
|
|
|
Keys
|
|
----
|
|
SPACE - generate random points
|
|
f - change distance function
|
|
ESC - exit
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
import sys
|
|
PY3 = sys.version_info[0] == 3
|
|
|
|
import numpy as np
|
|
import cv2 as cv
|
|
|
|
# built-in modules
|
|
import itertools as it
|
|
|
|
# local modules
|
|
from common import draw_str
|
|
|
|
|
|
w, h = 512, 256
|
|
|
|
def toint(p):
|
|
return tuple(map(int, p))
|
|
|
|
def sample_line(p1, p2, n, noise=0.0):
|
|
p1 = np.float32(p1)
|
|
t = np.random.rand(n,1)
|
|
return p1 + (p2-p1)*t + np.random.normal(size=(n, 2))*noise
|
|
|
|
dist_func_names = it.cycle('DIST_L2 DIST_L1 DIST_L12 DIST_FAIR DIST_WELSCH DIST_HUBER'.split())
|
|
|
|
if PY3:
|
|
cur_func_name = next(dist_func_names)
|
|
else:
|
|
cur_func_name = dist_func_names.next()
|
|
|
|
def update(_=None):
|
|
noise = cv.getTrackbarPos('noise', 'fit line')
|
|
n = cv.getTrackbarPos('point n', 'fit line')
|
|
r = cv.getTrackbarPos('outlier %', 'fit line') / 100.0
|
|
outn = int(n*r)
|
|
|
|
p0, p1 = (90, 80), (w-90, h-80)
|
|
img = np.zeros((h, w, 3), np.uint8)
|
|
cv.line(img, toint(p0), toint(p1), (0, 255, 0))
|
|
|
|
if n > 0:
|
|
line_points = sample_line(p0, p1, n-outn, noise)
|
|
outliers = np.random.rand(outn, 2) * (w, h)
|
|
points = np.vstack([line_points, outliers])
|
|
for p in line_points:
|
|
cv.circle(img, toint(p), 2, (255, 255, 255), -1)
|
|
for p in outliers:
|
|
cv.circle(img, toint(p), 2, (64, 64, 255), -1)
|
|
func = getattr(cv, cur_func_name)
|
|
vx, vy, cx, cy = cv.fitLine(np.float32(points), func, 0, 0.01, 0.01)
|
|
cv.line(img, (int(cx-vx*w), int(cy-vy*w)), (int(cx+vx*w), int(cy+vy*w)), (0, 0, 255))
|
|
|
|
draw_str(img, (20, 20), cur_func_name)
|
|
cv.imshow('fit line', img)
|
|
|
|
def main():
|
|
cv.namedWindow('fit line')
|
|
cv.createTrackbar('noise', 'fit line', 3, 50, update)
|
|
cv.createTrackbar('point n', 'fit line', 100, 500, update)
|
|
cv.createTrackbar('outlier %', 'fit line', 30, 100, update)
|
|
while True:
|
|
update()
|
|
ch = cv.waitKey(0)
|
|
if ch == ord('f'):
|
|
if PY3:
|
|
cur_func_name = next(dist_func_names)
|
|
else:
|
|
cur_func_name = dist_func_names.next()
|
|
if ch == 27:
|
|
break
|
|
|
|
print('Done')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
print(__doc__)
|
|
main()
|
|
cv.destroyAllWindows()
|