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