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annotate python/cvutils.py @ 151:4af774bb186d

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wrote a simple script to compute homography from point correspondences and display the reprojection for visual verification
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 06 Sep 2011 17:55:06 -0400
parents 404f3cade05f
children 74b1fc68d4df
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1 #! /usr/bin/env python
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2 '''Image/Video utilities'''
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3
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4 import Image, ImageDraw # PIL
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5 try:
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6 import cv2
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7 opencvExists = True
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8 except ImportError:
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9 print('OpenCV library could not be loaded')
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10 opencvExists = False
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11 from sys import stdout
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13 import utils
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15 #import aggdraw # agg on top of PIL (antialiased drawing)
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16 #import utils
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17
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18 __metaclass__ = type
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20 cvRed = (0,0,255)
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21 cvGreen = (0,255,0)
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22 cvBlue = (255,0,0)
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23 cvColors = utils.PlottingPropertyValues([cvRed,
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24 cvGreen,
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25 cvBlue])
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27 def drawLines(filename, origins, destinations, w = 1, resultFilename='image.png'):
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28 '''Draws lines over the image '''
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30 img = Image.open(filename)
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31
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32 draw = ImageDraw.Draw(img)
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33 #draw = aggdraw.Draw(img)
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34 #pen = aggdraw.Pen("red", width)
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35 for p1, p2 in zip(origins, destinations):
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36 draw.line([p1.x, p1.y, p2.x, p2.y], width = w, fill = (256,0,0))
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37 #draw.line([p1.x, p1.y, p2.x, p2.y], pen)
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38 del draw
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39
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40 #out = utils.openCheck(resultFilename)
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41 img.save(resultFilename)
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42
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43 def computeHomography(srcPoints, dstPoints, method=0, ransacReprojThreshold=0.0):
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44 '''Returns the homography matrix mapping from srcPoints to dstPoints (dimension Nx2)'''
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45 #cvSrcPoints = arrayToCvMat(srcPoints);
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46 #cvDstPoints = arrayToCvMat(dstPoints);
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47 #H = cv.CreateMat(3, 3, cv.CV_64FC1)
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48 H, mask = cv2.findHomography(srcPoints, dstPoints, method, ransacReprojThreshold)
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49 return H
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51 def cvMatToArray(cvmat):
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52 '''Converts an OpenCV CvMat to numpy array.'''
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53 from numpy.core.multiarray import zeros
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54 a = zeros((cvmat.rows, cvmat.cols))#array([[0.0]*cvmat.width]*cvmat.height)
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55 for i in xrange(cvmat.rows):
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56 for j in xrange(cvmat.cols):
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57 a[i,j] = cvmat[i,j]
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58 return a
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60 if opencvExists:
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61 def arrayToCvMat(a, t = cv.CV_64FC1):
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62 '''Converts a numpy array to an OpenCV CvMat, with default type CV_64FC1.'''
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63 cvmat = cv.CreateMat(a.shape[0], a.shape[1], t)
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64 for i in range(cvmat.rows):
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65 for j in range(cvmat.cols):
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66 cvmat[i,j] = a[i,j]
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67 return cvmat
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69 def playVideo(filename):
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70 '''Plays the video'''
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71 capture = cv2.VideoCapture(filename)
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72 if capture.isOpened():
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73 key = -1
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74 while key!= 1048689: # 'q'
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75 ret, img = capture.read()
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76 if ret:
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77 cv2.imshow('frame', img)
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78 key = cv2.waitKey(5)
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79
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80 def getImagesFromVideo(filename, nImages = 1):
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81 '''Returns nImages images from the video sequence'''
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82 images = []
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83 capture = cv2.VideoCapture(filename)
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84 if capture.isOpened():
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85 ret = False
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86 while len(images)<nImages:
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87 while not ret:
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88 ret, img = capture.read()
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89 if img.size>0:
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90 images.append(img)
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91 return images
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93 def printCvMat(cvmat, out = stdout):
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94 '''Prints the cvmat to out'''
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95 for i in xrange(cvmat.rows):
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96 for j in xrange(cvmat.cols):
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97 out.write('{0} '.format(cvmat[i,j]))
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98 out.write('\n')
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100 def projectArray(homography, points):
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101 '''Returns the coordinates of the projected points (format 2xN points)
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102 through homography'''
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103 from numpy.core._dotblas import dot
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104 from numpy.core.multiarray import array
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105 from numpy.lib.function_base import append
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106
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107 if points.shape[0] != 2:
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108 raise Exception('points of dimension {0} {1}'.format(points.shape[0], points.shape[1]))
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109
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110 if (homography!=None) and homography.size>0:
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111 augmentedPoints = append(points,[[1]*points.shape[1]], 0)
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112 prod = dot(homography, augmentedPoints)
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113 return prod[0:2]/prod[2]
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114 else:
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115 return p
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116
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117 def project(homography, p):
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118 '''Returns the coordinates of the projection of the point p
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119 through homography'''
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120 from numpy.core.multiarray import array
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121 return projectArray(homography, array([[p[0]],p[1]]))
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122
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123 def projectTrajectory(homography, trajectory):
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124 '''Projects a series of points in the format
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125 [[x1, x2, ...],
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126 [y1, y2, ...]]'''
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127 from numpy.core.multiarray import array
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128 return projectArray(homography, array(trajectory))
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129
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130 def invertHomography(homography):
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131 'Returns an inverted homography'
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132 from numpy.linalg.linalg import inv
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133 invH = inv(homography)
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134 invH /= invH[2,2]
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135 return invH
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136
112
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137 if opencvExists:
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138 def computeTranslation(img1, img2, img1Points, maxTranslation, minNMatches, windowSize = (5,5), level = 5, criteria = (cv.CV_TERMCRIT_EPS, 0, 0.01)):
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139 '''Computes the translation between of img2 with respect to img1
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140 (loaded using OpenCV)
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141 img1Points are used to compute the translation
100
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142
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143 TODO add diagnostic if data is all over the place, and it most likely is not a translation (eg zoom)'''
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144 from numpy.core.multiarray import zeros
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145 from numpy.lib.function_base import median
100
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146
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147 (img2Points, status, track_error) = cv.CalcOpticalFlowPyrLK(img1, img2, zeros((img1.rows,img1.cols+8)), zeros((img1.rows,img1.cols+8)), img1Points, windowSize, level, criteria, 0)
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148
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149 deltaX = []
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150 deltaY = []
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151 for (k, (p1,p2)) in enumerate(zip(img1Points, img2Points)):
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152 if status[k] == 1:
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153 dx = p2[0]-p1[0]
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154 dy = p2[1]-p1[1]
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155 d = dx**2 + dy**2
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156 if d < maxTranslation:
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157 deltaX.append(dx)
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158 deltaY.append(dy)
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159 if len(deltaX) >= 10:
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160 return [median(deltaX), median(deltaY)]
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161 else:
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162 return None