87 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
			
		
		
	
	
			87 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
| #!/usr/bin/env python
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| 
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| '''
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| Robust line fitting.
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| ==================
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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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| 
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| Usage
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| -----
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| fitline.py
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| 
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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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| 
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| Keys
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| ----
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| SPACE - generaty random points
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| f     - change distance function
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| ESC   - exit
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| '''
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| 
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| import numpy as np
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| import cv2
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| 
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| # built-in modules
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| import itertools as it
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| 
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| # local modules
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| from common import draw_str
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| 
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| 
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| w, h = 512, 256
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| 
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| def toint(p):
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|     return tuple(map(int, p))
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| 
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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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| 
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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 = dist_func_names.next()
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| if __name__ == '__main__':
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|     print __doc__
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| 
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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)
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|         if ch == ord('f'):
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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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