Mercurial Hosting > traffic-intelligence
annotate python/cvutils.py @ 396:167f6ec44ec5
cleaned function to save images
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Sun, 28 Jul 2013 16:30:11 -0400 |
parents | eaf7765221d9 |
children | 3399bd48cb40 |
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 opencvAvailable = 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 opencvAvailable = False |
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11 try: |
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12 import skimage |
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13 skimageAvailable = True |
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14 except ImportError: |
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15 print('Scikit-image library could not be loaded') |
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16 skimageAvailable = False |
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17 |
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18 from sys import stdout |
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19 |
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20 import utils |
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21 |
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22 #import aggdraw # agg on top of PIL (antialiased drawing) |
28 | 23 #import utils |
24 | |
25 __metaclass__ = type | |
26 | |
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27 cvRed = (0,0,255) |
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28 cvGreen = (0,255,0) |
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29 cvBlue = (255,0,0) |
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30 cvColors = utils.PlottingPropertyValues([cvRed, |
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31 cvGreen, |
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32 cvBlue]) |
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33 |
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34 def quitKey(key): |
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35 return chr(key&255)== 'q' or chr(key&255) == 'Q' |
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36 |
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37 def saveKey(key): |
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38 return chr(key&255) == 's' |
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39 |
28 | 40 def drawLines(filename, origins, destinations, w = 1, resultFilename='image.png'): |
41 '''Draws lines over the image ''' | |
42 | |
43 img = Image.open(filename) | |
44 | |
45 draw = ImageDraw.Draw(img) | |
46 #draw = aggdraw.Draw(img) | |
47 #pen = aggdraw.Pen("red", width) | |
48 for p1, p2 in zip(origins, destinations): | |
49 draw.line([p1.x, p1.y, p2.x, p2.y], width = w, fill = (256,0,0)) | |
50 #draw.line([p1.x, p1.y, p2.x, p2.y], pen) | |
51 del draw | |
52 | |
53 #out = utils.openCheck(resultFilename) | |
54 img.save(resultFilename) | |
55 | |
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56 def matlab2PointCorrespondences(filename): |
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57 '''Loads and converts the point correspondences saved |
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58 by the matlab camera calibration tool''' |
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59 from numpy.lib.io import loadtxt, savetxt |
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60 from numpy.lib.function_base import append |
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61 points = loadtxt(filename, delimiter=',') |
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62 savetxt(utils.removeExtension(filename)+'-point-correspondences.txt',append(points[:,:2].T, points[:,3:].T, axis=0)) |
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63 |
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64 def loadPointCorrespondences(filename): |
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65 '''Loads and returns the corresponding points in world (first 2 lines) and image spaces (last 2 lines)''' |
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66 from numpy.lib.npyio import loadtxt |
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67 from numpy import float32 |
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68 points = loadtxt(filename, dtype=float32) |
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69 return (points[:2,:].T, points[2:,:].T) # (world points, image points) |
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70 |
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71 def cvMatToArray(cvmat): |
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72 '''Converts an OpenCV CvMat to numpy array.''' |
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73 print('Deprecated, use new interface') |
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74 from numpy.core.multiarray import zeros |
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75 a = zeros((cvmat.rows, cvmat.cols))#array([[0.0]*cvmat.width]*cvmat.height) |
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76 for i in xrange(cvmat.rows): |
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77 for j in xrange(cvmat.cols): |
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78 a[i,j] = cvmat[i,j] |
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79 return a |
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80 |
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81 if opencvAvailable: |
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82 def computeHomography(srcPoints, dstPoints, method=0, ransacReprojThreshold=0.0): |
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83 '''Returns the homography matrix mapping from srcPoints to dstPoints (dimension Nx2)''' |
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84 H, mask = cv2.findHomography(srcPoints, dstPoints, method, ransacReprojThreshold) |
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85 return H |
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86 |
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87 def arrayToCvMat(a, t = cv2.cv.CV_64FC1): |
112
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88 '''Converts a numpy array to an OpenCV CvMat, with default type CV_64FC1.''' |
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89 print('Deprecated, use new interface') |
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90 cvmat = cv2.cv.CreateMat(a.shape[0], a.shape[1], t) |
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91 for i in range(cvmat.rows): |
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92 for j in range(cvmat.cols): |
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93 cvmat[i,j] = a[i,j] |
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94 return cvmat |
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95 |
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96 def draw(img, positions, color, lastCoordinate = None): |
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97 last = lastCoordinate+1 |
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98 if lastCoordinate != None and lastCoordinate >=0: |
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99 last = min(positions.length()-1, lastCoordinate) |
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100 for i in range(0, last-1): |
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101 cv2.line(img, positions[i].asint().astuple(), positions[i+1].asint().astuple(), color) |
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102 |
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103 def cvImshow(windowName, img, rescale = 1.0): |
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104 'Rescales the image (in particular if too large)' |
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105 from cv2 import resize |
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106 if rescale != 1.: |
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107 size = (int(round(img.shape[1]*rescale)), int(round(img.shape[0]*rescale))) |
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108 resizedImg = resize(img, size) |
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109 cv2.imshow(windowName, resizedImg) |
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110 else: |
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111 cv2.imshow(windowName, img) |
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112 |
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113 def playVideo(filename, firstFrameNum = 0, frameRate = -1, interactive = False, printFrames = True, text = None, rescale = 1.): |
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114 '''Plays the video''' |
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115 wait = 5 |
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116 if frameRate > 0: |
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117 wait = int(round(1000./frameRate)) |
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118 if interactive: |
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119 wait = 0 |
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120 capture = cv2.VideoCapture(filename) |
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121 if capture.isOpened(): |
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122 key = -1 |
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123 ret = True |
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124 frameNum = firstFrameNum |
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125 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, firstFrameNum) |
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126 while ret and not quitKey(key): |
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127 ret, img = capture.read() |
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128 if ret: |
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129 if printFrames: |
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130 print('frame {0}'.format(frameNum)) |
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131 frameNum+=1 |
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132 if text != None: |
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133 cv2.putText(img, text, (10,50), cv2.FONT_HERSHEY_PLAIN, 1, cvRed) |
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134 cvImshow('frame', img, rescale) |
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135 key = cv2.waitKey(wait) |
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136 cv2.destroyAllWindows() |
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137 |
396
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138 def getImagesFromVideo(videoFilename, firstFrameNum = 0, nFrames = 1, saveImage = False, outputPrefix = 'image'): |
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139 '''Returns nFrames images from the video sequence''' |
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140 from math import floor, log10 |
150
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141 images = [] |
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142 capture = cv2.VideoCapture(videoFilename) |
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143 nDigits = int(floor(log10(capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))))+1 |
150
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144 if capture.isOpened(): |
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145 ret = False |
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146 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, firstFrameNum) |
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147 imgNum = 0 |
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148 while imgNum<nFrames: |
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149 ret, img = capture.read() |
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150 i = 0 |
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151 while not ret and i<10: |
150
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152 ret, img = capture.read() |
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153 i += 1 |
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154 if img.size>0: |
216
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155 if saveImage: |
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156 imgNumStr = format(firstFrameNum+imgNum, '0{}d'.format(nDigits)) |
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157 cv2.imwrite(outputPrefix+imgNumStr+'.png', img) |
216
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158 else: |
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159 images.append(img) |
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160 imgNum +=1 |
150
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161 return images |
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162 |
393
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163 def displayTrajectories(videoFilename, objects, boundingBoxes, homography = None, firstFrameNum = 0, lastFrameNumArg = None, printFrames = True, rescale = 1.): |
203
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164 '''Displays the objects overlaid frame by frame over the video ''' |
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165 capture = cv2.VideoCapture(videoFilename) |
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166 if capture.isOpened(): |
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167 key = -1 |
227
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168 ret = True |
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169 frameNum = firstFrameNum |
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170 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, firstFrameNum) |
248
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171 if not lastFrameNumArg: |
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172 from sys import maxint |
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173 lastFrameNum = maxint |
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174 else: |
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175 lastFrameNum = lastFrameNumArg |
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176 while ret and not quitKey(key) and frameNum < lastFrameNum: |
203
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177 ret, img = capture.read() |
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178 if ret: |
381
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179 if printFrames: |
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180 print('frame {0}'.format(frameNum)) |
203
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181 for obj in objects: |
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182 if obj.existsAtInstant(frameNum): |
236
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183 if not hasattr(obj, 'projectedPositions'): |
218
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184 if homography != None: |
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185 obj.projectedPositions = obj.positions.project(homography) |
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186 else: |
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187 obj.projectedPositions = obj.positions |
203
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188 draw(img, obj.projectedPositions, cvRed, frameNum-obj.getFirstInstant()) |
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189 if frameNum in boundingBoxes.keys(): |
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190 for rect in boundingBoxes[frameNum]: |
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191 cv2.rectangle(img, rect[0].asint().astuple(), rect[1].asint().astuple(), cvRed) |
223
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192 cv2.putText(img, '{0}'.format(obj.num), obj.projectedPositions[frameNum-obj.getFirstInstant()].asint().astuple(), cv2.FONT_HERSHEY_PLAIN, 1, cvRed) |
385
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193 cvImshow('frame', img, rescale) |
266
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194 key = cv2.waitKey() |
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195 if saveKey(key): |
266
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196 cv2.imwrite('image.png', img) |
203
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197 frameNum += 1 |
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198 cv2.destroyAllWindows() |
203
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199 |
99
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200 def printCvMat(cvmat, out = stdout): |
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201 '''Prints the cvmat to out''' |
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202 print('Deprecated, use new interface') |
99
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203 for i in xrange(cvmat.rows): |
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204 for j in xrange(cvmat.cols): |
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205 out.write('{0} '.format(cvmat[i,j])) |
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206 out.write('\n') |
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207 |
98
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208 def projectArray(homography, points): |
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209 '''Returns the coordinates of the projected points through homography |
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210 (format: array 2xN points)''' |
315
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211 from numpy.core import dot |
28 | 212 from numpy.core.multiarray import array |
98
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213 from numpy.lib.function_base import append |
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214 |
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215 if points.shape[0] != 2: |
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216 raise Exception('points of dimension {0} {1}'.format(points.shape[0], points.shape[1])) |
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217 |
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218 if (homography!=None) and homography.size>0: |
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219 augmentedPoints = append(points,[[1]*points.shape[1]], 0) |
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220 prod = dot(homography, augmentedPoints) |
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221 return prod[0:2]/prod[2] |
28 | 222 else: |
223 return p | |
224 | |
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225 def project(homography, p): |
319 | 226 '''Returns the coordinates of the projection of the point p with coordinates p[0], p[1] |
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227 through homography''' |
243
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228 from numpy import array |
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229 return projectArray(homography, array([[p[0]],[p[1]]])) |
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230 |
28 | 231 def projectTrajectory(homography, trajectory): |
232 '''Projects a series of points in the format | |
233 [[x1, x2, ...], | |
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234 [y1, y2, ...]]''' |
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235 from numpy.core.multiarray import array |
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236 return projectArray(homography, array(trajectory)) |
28 | 237 |
48
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238 def invertHomography(homography): |
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239 '''Returns an inverted homography |
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240 Unnecessary for reprojection over camera image''' |
48
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241 from numpy.linalg.linalg import inv |
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242 invH = inv(homography) |
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243 invH /= invH[2,2] |
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244 return invH |
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245 |
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246 if opencvAvailable: |
154
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247 def computeTranslation(img1, img2, img1Points, maxTranslation2, minNMatches, windowSize = (5,5), level = 5, criteria = (cv2.TERM_CRITERIA_EPS, 0, 0.01)): |
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248 '''Computes the translation of img2 with respect to img1 |
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249 (loaded using OpenCV as numpy arrays) |
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250 img1Points are used to compute the translation |
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251 |
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252 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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253 from numpy.core.multiarray import array |
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254 from numpy.lib.function_base import median |
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255 from numpy.core.fromnumeric import sum |
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256 |
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257 nextPoints = array([]) |
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258 (img2Points, status, track_error) = cv2.calcOpticalFlowPyrLK(img1, img2, img1Points, nextPoints, winSize=windowSize, maxLevel=level, criteria=criteria) |
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259 # calcOpticalFlowPyrLK(prevImg, nextImg, prevPts[, nextPts[, status[, err[, winSize[, maxLevel[, criteria[, derivLambda[, flags]]]]]]]]) -> nextPts, status, err |
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260 delta = [] |
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261 for (k, (p1,p2)) in enumerate(zip(img1Points, img2Points)): |
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262 if status[k] == 1: |
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263 dp = p2-p1 |
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264 d = sum(dp**2) |
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265 if d < maxTranslation2: |
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266 delta.append(dp) |
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267 if len(delta) >= minNMatches: |
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268 return median(delta, axis=0) |
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269 else: |
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270 print(dp) |
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271 return None |
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272 |
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273 if skimageAvailable: |
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274 def createHOGTrainingSet(imageDirectory, classLabel, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8, 8), cellsPerBlock=(3, 3), visualize=False, normalize=False): |
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275 from os import listdir |
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276 from matplotlib.pyplot import imread, imshow, figure, subplot |
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277 from skimage.feature import hog |
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278 from skimage import color, transform |
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279 from numpy import array, float32 |
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280 |
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281 inputData = [] |
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282 for filename in listdir(imageDirectory): |
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283 img = imread(imageDirectory+filename) |
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284 bwImg = color.rgb2gray(img) |
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285 inputImg = transform.resize(bwImg, rescaleSize) |
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286 features = hog(inputImg, orientations, pixelsPerCell, cellsPerBlock, visualize, normalize) |
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287 if visualize: |
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288 hogViz = features[1] |
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289 features = features[0] |
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290 figure() |
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291 subplot(1,2,1) |
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292 imshow(img) |
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293 subplot(1,2,2) |
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294 imshow(hogViz) |
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295 inputData.append(features) |
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296 |
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297 nImages = len(inputData) |
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298 return array(inputData, dtype = float32), array([classLabel]*nImages, dtype = float32) |
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299 |
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300 |