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annotate python/cvutils.py @ 251:4978b5baf8f1
Win32 version for traffic intelligence. Use the README-Win32.txt to know how to
fetch the dependencies. A batch file is included to automate most of the process
author | Jeep-Tour@Jeep-Tour-PC |
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date | Mon, 23 Jul 2012 12:27:50 -0400 |
parents | 571ba5ed22e2 |
children | aba9711b3149 |
rev | line source |
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28 | 1 #! /usr/bin/env python |
2 '''Image/Video utilities''' | |
3 | |
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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12 |
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13 import utils |
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14 |
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15 #import aggdraw # agg on top of PIL (antialiased drawing) |
28 | 16 #import utils |
17 | |
18 __metaclass__ = type | |
19 | |
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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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26 |
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27 cvKeyNumbers = {'a':1048673, |
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28 'n': 1048686, |
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29 'y': 1048697} |
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30 |
28 | 31 def drawLines(filename, origins, destinations, w = 1, resultFilename='image.png'): |
32 '''Draws lines over the image ''' | |
33 | |
34 img = Image.open(filename) | |
35 | |
36 draw = ImageDraw.Draw(img) | |
37 #draw = aggdraw.Draw(img) | |
38 #pen = aggdraw.Pen("red", width) | |
39 for p1, p2 in zip(origins, destinations): | |
40 draw.line([p1.x, p1.y, p2.x, p2.y], width = w, fill = (256,0,0)) | |
41 #draw.line([p1.x, p1.y, p2.x, p2.y], pen) | |
42 del draw | |
43 | |
44 #out = utils.openCheck(resultFilename) | |
45 img.save(resultFilename) | |
46 | |
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47 def matlab2PointCorrespondences(filename): |
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48 '''Loads and converts the point correspondences saved |
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49 by the matlab camera calibration tool''' |
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50 from numpy.lib.io import loadtxt, savetxt |
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51 from numpy.lib.function_base import append |
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52 points = loadtxt(filename, delimiter=',') |
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53 savetxt(utils.removeExtension(filename)+'-point-correspondences.txt',append(points[:,:2].T, points[:,3:].T, axis=0)) |
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54 |
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55 def loadPointCorrespondences(filename): |
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56 '''Loads and returns the corresponding points in world (first 2 lines) and image spaces (last 2 lines)''' |
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57 from numpy.lib.npyio import loadtxt |
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58 from numpy import float32 |
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59 points = loadtxt(filename, dtype=float32) |
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60 return (points[:2,:].T, points[2:,:].T) # (world points, image points) |
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61 |
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62 def computeHomography(srcPoints, dstPoints, method=0, ransacReprojThreshold=0.0): |
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63 '''Returns the homography matrix mapping from srcPoints to dstPoints (dimension Nx2)''' |
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64 #cvSrcPoints = arrayToCvMat(srcPoints); |
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65 #cvDstPoints = arrayToCvMat(dstPoints); |
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66 #H = cv.CreateMat(3, 3, cv.CV_64FC1) |
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67 H, mask = cv2.findHomography(srcPoints, dstPoints, method, ransacReprojThreshold) |
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68 return H |
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69 |
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70 def cvMatToArray(cvmat): |
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71 '''Converts an OpenCV CvMat to numpy array.''' |
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72 from numpy.core.multiarray import zeros |
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73 a = zeros((cvmat.rows, cvmat.cols))#array([[0.0]*cvmat.width]*cvmat.height) |
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74 for i in xrange(cvmat.rows): |
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75 for j in xrange(cvmat.cols): |
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76 a[i,j] = cvmat[i,j] |
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77 return a |
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78 |
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79 if opencvExists: |
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80 def arrayToCvMat(a, t = cv2.cv.CV_64FC1): |
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81 '''Converts a numpy array to an OpenCV CvMat, with default type CV_64FC1.''' |
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82 cvmat = cv2.cv.CreateMat(a.shape[0], a.shape[1], t) |
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83 for i in range(cvmat.rows): |
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84 for j in range(cvmat.cols): |
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85 cvmat[i,j] = a[i,j] |
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86 return cvmat |
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87 |
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88 def draw(img, positions, color, lastCoordinate = None): |
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89 last = lastCoordinate+1 |
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90 if lastCoordinate != None and lastCoordinate >=0: |
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91 last = min(positions.length()-1, lastCoordinate) |
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92 for i in range(0, last-1): |
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93 cv2.line(img, positions[i].asint().astuple(), positions[i+1].asint().astuple(), color) |
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94 |
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95 def playVideo(filename, firstFrameNum = 0): |
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96 '''Plays the video''' |
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97 capture = cv2.VideoCapture(filename) |
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98 if capture.isOpened(): |
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99 key = -1 |
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100 ret = True |
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101 frameNum = firstFrameNum |
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102 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, firstFrameNum) |
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103 while ret and key!= 113: # 'q' |
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104 ret, img = capture.read() |
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105 if ret: |
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106 print('frame {0}'.format(frameNum)) |
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107 frameNum+=1 |
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108 cv2.imshow('frame', img) |
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109 key = cv2.waitKey(5) |
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110 |
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111 def getImagesFromVideo(filename, nImages = 1, saveImage = False): |
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112 '''Returns nImages images from the video sequence''' |
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113 images = [] |
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114 capture = cv2.VideoCapture(filename) |
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115 if capture.isOpened(): |
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116 ret = False |
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117 numImg = 0 |
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118 while numImg<nImages: |
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119 ret, img = capture.read() |
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120 i = 0 |
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121 while not ret and i<10: |
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122 ret, img = capture.read() |
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123 i += 1 |
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124 if img.size>0: |
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125 numImg +=1 |
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126 if saveImage: |
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127 cv2.imwrite('image{0:04d}.png'.format(numImg), img) |
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128 else: |
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129 images.append(img) |
150
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130 return images |
149
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131 |
248
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132 def displayTrajectories(videoFilename, objects, homography = None, firstFrameNum = 0, lastFrameNumArg = None): |
203
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133 '''Displays the objects overlaid frame by frame over the video ''' |
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134 capture = cv2.VideoCapture(videoFilename) |
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135 if capture.isOpened(): |
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136 key = -1 |
227
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137 ret = True |
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138 frameNum = firstFrameNum |
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139 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, firstFrameNum) |
248
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140 if not lastFrameNumArg: |
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141 from sys import maxint |
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142 lastFrameNum = maxint |
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143 else: |
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144 lastFrameNum = lastFrameNumArg |
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145 while ret and key!= 113 and frameNum < lastFrameNum: # 'q' |
203
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146 ret, img = capture.read() |
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147 if ret: |
227
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148 print('frame {0}'.format(frameNum)) |
203
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149 for obj in objects: |
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150 if obj.existsAtInstant(frameNum): |
236
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151 if not hasattr(obj, 'projectedPositions'): |
218
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152 if homography != None: |
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153 obj.projectedPositions = obj.positions.project(homography) |
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154 else: |
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155 obj.projectedPositions = obj.positions |
203
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156 draw(img, obj.projectedPositions, cvRed, frameNum-obj.getFirstInstant()) |
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157 cv2.putText(img, '{0}'.format(obj.num), obj.projectedPositions[frameNum-obj.getFirstInstant()].asint().astuple(), cv2.FONT_HERSHEY_PLAIN, 1, cvRed) |
203
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158 cv2.imshow('frame', img) |
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159 key = cv2.waitKey(50) |
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160 frameNum += 1 |
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161 |
99
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162 def printCvMat(cvmat, out = stdout): |
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163 '''Prints the cvmat to out''' |
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164 for i in xrange(cvmat.rows): |
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165 for j in xrange(cvmat.cols): |
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166 out.write('{0} '.format(cvmat[i,j])) |
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167 out.write('\n') |
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168 |
98
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169 def projectArray(homography, points): |
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170 '''Returns the coordinates of the projected points (format 2xN points) |
28 | 171 through homography''' |
172 from numpy.core._dotblas import dot | |
173 from numpy.core.multiarray import array | |
98
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174 from numpy.lib.function_base import append |
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175 |
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176 if points.shape[0] != 2: |
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177 raise Exception('points of dimension {0} {1}'.format(points.shape[0], points.shape[1])) |
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178 |
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179 if (homography!=None) and homography.size>0: |
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180 augmentedPoints = append(points,[[1]*points.shape[1]], 0) |
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181 prod = dot(homography, augmentedPoints) |
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182 return prod[0:2]/prod[2] |
28 | 183 else: |
184 return p | |
185 | |
98
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186 def project(homography, p): |
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187 '''Returns the coordinates of the projection of the point p |
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188 through homography''' |
243
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189 from numpy import array |
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190 return projectArray(homography, array([[p[0]],[p[1]]])) |
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191 |
28 | 192 def projectTrajectory(homography, trajectory): |
193 '''Projects a series of points in the format | |
194 [[x1, x2, ...], | |
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195 [y1, y2, ...]]''' |
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196 from numpy.core.multiarray import array |
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197 return projectArray(homography, array(trajectory)) |
28 | 198 |
48
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199 def invertHomography(homography): |
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200 'Returns an inverted homography' |
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201 from numpy.linalg.linalg import inv |
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202 invH = inv(homography) |
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203 invH /= invH[2,2] |
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204 return invH |
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205 |
112
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206 if opencvExists: |
154
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207 def computeTranslation(img1, img2, img1Points, maxTranslation2, minNMatches, windowSize = (5,5), level = 5, criteria = (cv2.TERM_CRITERIA_EPS, 0, 0.01)): |
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208 '''Computes the translation of img2 with respect to img1 |
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209 (loaded using OpenCV as numpy arrays) |
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210 img1Points are used to compute the translation |
100
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211 |
154
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212 TODO add diagnostic if data is all over the place, and it most likely is not a translation (eg zoom, other non linear distortion)''' |
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213 from numpy.core.multiarray import array |
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214 from numpy.lib.function_base import median |
154
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215 from numpy.core.fromnumeric import sum |
100
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216 |
154
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217 nextPoints = array([]) |
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218 (img2Points, status, track_error) = cv2.calcOpticalFlowPyrLK(img1, img2, img1Points, nextPoints, winSize=windowSize, maxLevel=level, criteria=criteria) |
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219 # calcOpticalFlowPyrLK(prevImg, nextImg, prevPts[, nextPts[, status[, err[, winSize[, maxLevel[, criteria[, derivLambda[, flags]]]]]]]]) -> nextPts, status, err |
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220 delta = [] |
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221 for (k, (p1,p2)) in enumerate(zip(img1Points, img2Points)): |
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222 if status[k] == 1: |
154
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223 dp = p2-p1 |
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224 d = sum(dp**2) |
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225 if d < maxTranslation2: |
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226 delta.append(dp) |
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227 if len(delta) >= minNMatches: |
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228 return median(delta, axis=0) |
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229 else: |
156
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230 print(dp) |
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231 return None |