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Open Source Computer Vision Library
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94 lines
2.3 KiB
94 lines
2.3 KiB
#!/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 cv.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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import numpy as np |
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import cv2 as cv |
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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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cur_func_name = next(dist_func_names) |
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def update(_=None): |
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noise = cv.getTrackbarPos('noise', 'fit line') |
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n = cv.getTrackbarPos('point n', 'fit line') |
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r = cv.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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cv.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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cv.circle(img, toint(p), 2, (255, 255, 255), -1) |
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for p in outliers: |
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cv.circle(img, toint(p), 2, (64, 64, 255), -1) |
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func = getattr(cv, cur_func_name) |
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vx, vy, cx, cy = cv.fitLine(np.float32(points), func, 0, 0.01, 0.01) |
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cv.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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cv.imshow('fit line', img) |
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def main(): |
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cv.namedWindow('fit line') |
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cv.createTrackbar('noise', 'fit line', 3, 50, update) |
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cv.createTrackbar('point n', 'fit line', 100, 500, update) |
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cv.createTrackbar('outlier %', 'fit line', 30, 100, update) |
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while True: |
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update() |
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ch = cv.waitKey(0) |
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if ch == ord('f'): |
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global cur_func_name |
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cur_func_name = next(dist_func_names) |
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if ch == 27: |
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break |
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print('Done') |
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if __name__ == '__main__': |
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print(__doc__) |
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main() |
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cv.destroyAllWindows()
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