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comparison python/cvutils.py @ 726:43ae3a1af290

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added functionality to display matchings between ground truth and tracked objects
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 07 Aug 2015 13:07:53 -0400
parents 35bc5e30a53f
children 6022350f8173
comparison
equal deleted inserted replaced
725:35bc5e30a53f 726:43ae3a1af290
23 23
24 24
25 cvRed = (0,0,255) 25 cvRed = (0,0,255)
26 cvGreen = (0,255,0) 26 cvGreen = (0,255,0)
27 cvBlue = (255,0,0) 27 cvBlue = (255,0,0)
28 cvCyan = (255, 255, 0)
29 cvYellow = (0, 255, 255)
30 cvMagenta = (255, 0, 255)
31 cvWhite = (255, 255, 255)
32 cvBlack = (0,0,0)
33 cvColors3 = utils.PlottingPropertyValues([cvRed,
34 cvGreen,
35 cvBlue])
28 cvColors = utils.PlottingPropertyValues([cvRed, 36 cvColors = utils.PlottingPropertyValues([cvRed,
29 cvGreen, 37 cvGreen,
30 cvBlue]) 38 cvBlue,
39 cvCyan,
40 cvYellow,
41 cvMagenta,
42 cvWhite,
43 cvBlack])
31 44
32 def quitKey(key): 45 def quitKey(key):
33 return chr(key&255)== 'q' or chr(key&255) == 'Q' 46 return chr(key&255)== 'q' or chr(key&255) == 'Q'
34 47
35 def saveKey(key): 48 def saveKey(key):
55 #draw.line([p1.x, p1.y, p2.x, p2.y], pen) 68 #draw.line([p1.x, p1.y, p2.x, p2.y], pen)
56 del draw 69 del draw
57 70
58 #out = utils.openCheck(resultFilename) 71 #out = utils.openCheck(resultFilename)
59 img.save(resultFilename) 72 img.save(resultFilename)
73
74 def rgb2gray(rgb):
75 return dot(rgb[...,:3], [0.299, 0.587, 0.144])
60 76
61 def matlab2PointCorrespondences(filename): 77 def matlab2PointCorrespondences(filename):
62 '''Loads and converts the point correspondences saved 78 '''Loads and converts the point correspondences saved
63 by the matlab camera calibration tool''' 79 by the matlab camera calibration tool'''
64 from numpy.lib.io import loadtxt, savetxt 80 from numpy.lib.io import loadtxt, savetxt
96 for j in range(cvmat.cols): 112 for j in range(cvmat.cols):
97 cvmat[i,j] = a[i,j] 113 cvmat[i,j] = a[i,j]
98 return cvmat 114 return cvmat
99 115
100 def cvPlot(img, positions, color, lastCoordinate = None, **kwargs): 116 def cvPlot(img, positions, color, lastCoordinate = None, **kwargs):
101 last = lastCoordinate+1 117 if lastCoordinate is None:
102 if lastCoordinate is not None and lastCoordinate >=0: 118 last = positions.length()-1
119 elif lastCoordinate >=0:
103 last = min(positions.length()-1, lastCoordinate) 120 last = min(positions.length()-1, lastCoordinate)
104 for i in range(0, last-1): 121 for i in range(0, last):
105 cv2.line(img, positions[i].asint().astuple(), positions[i+1].asint().astuple(), color, **kwargs) 122 cv2.line(img, positions[i].asint().astuple(), positions[i+1].asint().astuple(), color, **kwargs)
106 123
107 def cvImshow(windowName, img, rescale = 1.0): 124 def cvImshow(windowName, img, rescale = 1.0):
108 'Rescales the image (in particular if too large)' 125 'Rescales the image (in particular if too large)'
109 from cv2 import resize 126 from cv2 import resize
262 else: 279 else:
263 croppedImg = None 280 croppedImg = None
264 return croppedImg, yCropMin, yCropMax, xCropMin, xCropMax 281 return croppedImg, yCropMin, yCropMax, xCropMin, xCropMax
265 282
266 283
267 def displayTrajectories(videoFilename, objects, boundingBoxes = {}, homography = None, firstFrameNum = 0, lastFrameNumArg = None, printFrames = True, rescale = 1., nFramesStep = 1, saveAllImages = False, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1.): 284 def displayTrajectories(videoFilename, objects, boundingBoxes = {}, homography = None, firstFrameNum = 0, lastFrameNumArg = None, printFrames = True, rescale = 1., nFramesStep = 1, saveAllImages = False, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1., annotations = [], gtMatches = {}, toMatches = {}):
268 '''Displays the objects overlaid frame by frame over the video ''' 285 '''Displays the objects overlaid frame by frame over the video '''
269 from moving import userTypeNames 286 from moving import userTypeNames
270 from math import ceil, log10 287 from math import ceil, log10
271 288
272 capture = cv2.VideoCapture(videoFilename) 289 capture = cv2.VideoCapture(videoFilename)
299 if printFrames: 316 if printFrames:
300 print('frame {0}'.format(frameNum)) 317 print('frame {0}'.format(frameNum))
301 if len(objectToDeleteIds) > 0: 318 if len(objectToDeleteIds) > 0:
302 objects = [o for o in objects if o.getNum() not in objectToDeleteIds] 319 objects = [o for o in objects if o.getNum() not in objectToDeleteIds]
303 objectToDeleteIds = [] 320 objectToDeleteIds = []
321 # plot objects
304 for obj in objects: 322 for obj in objects:
305 if obj.existsAtInstant(frameNum): 323 if obj.existsAtInstant(frameNum):
306 if obj.getLastInstant() == frameNum: 324 if obj.getLastInstant() == frameNum:
307 objectToDeleteIds.append(obj.getNum()) 325 objectToDeleteIds.append(obj.getNum())
308 if not hasattr(obj, 'projectedPositions'): 326 if not hasattr(obj, 'projectedPositions'):
309 if homography is not None: 327 if homography is not None:
310 obj.projectedPositions = obj.positions.project(homography) 328 obj.projectedPositions = obj.positions.project(homography)
311 else: 329 else:
312 obj.projectedPositions = obj.positions 330 obj.projectedPositions = obj.positions
313 cvPlot(img, obj.projectedPositions, cvRed, frameNum-obj.getFirstInstant()) 331 cvPlot(img, obj.projectedPositions, cvColors[obj.getNum()], frameNum-obj.getFirstInstant())
314 if frameNum not in boundingBoxes.keys() and obj.hasFeatures(): 332 if frameNum not in boundingBoxes.keys() and obj.hasFeatures():
315 imgcrop, yCropMin, yCropMax, xCropMin, xCropMax = imageBox(img, obj, frameNum, homography, width, height) 333 imgcrop, yCropMin, yCropMax, xCropMin, xCropMax = imageBox(img, obj, frameNum, homography, width, height)
316 cv2.rectangle(img, (xCropMin, yCropMin), (xCropMax, yCropMax), cvBlue, 1) 334 cv2.rectangle(img, (xCropMin, yCropMin), (xCropMax, yCropMax), cvBlue, 1)
317 objDescription = '{} '.format(obj.num) 335 objDescription = '{} '.format(obj.num)
318 if userTypeNames[obj.userType] != 'unknown': 336 if userTypeNames[obj.userType] != 'unknown':
319 objDescription += userTypeNames[obj.userType][0].upper() 337 objDescription += userTypeNames[obj.userType][0].upper()
320 cv2.putText(img, objDescription, obj.projectedPositions[frameNum-obj.getFirstInstant()].asint().astuple(), cv2.cv.CV_FONT_HERSHEY_PLAIN, 1, cvRed) 338 if len(annotations) > 0: # if we loaded annotations, but there is no match
339 if frameNum not in toMatches[obj.getNum()]:
340 objDescription += " FA"
341 cv2.putText(img, objDescription, obj.projectedPositions[frameNum-obj.getFirstInstant()].asint().astuple(), cv2.cv.CV_FONT_HERSHEY_PLAIN, 1, cvColors[obj.getNum()])
321 # plot object bounding boxes 342 # plot object bounding boxes
322 if frameNum in boundingBoxes.keys(): 343 if frameNum in boundingBoxes.keys():
323 for rect in boundingBoxes[frameNum]: 344 for rect in boundingBoxes[frameNum]:
324 cv2.rectangle(img, rect[0].asint().astuple(), rect[1].asint().astuple(), cvRed) 345 cv2.rectangle(img, rect[0].asint().astuple(), rect[1].asint().astuple(), cvColors[obj.getNum()])
346 # plot ground truth
347 if len(annotations) > 0:
348 for gt in annotations:
349 if gt.existsAtInstant(frameNum):
350 if frameNum in gtMatches[gt.getNum()]:
351 color = cvColors[gtMatches[gt.getNum()][frameNum]] # same color as object
352 else:
353 color = cvRed
354 cv2.putText(img, 'Miss', gt.topLeftPositions[frameNum-gt.getFirstInstant()].asint().astuple(), cv2.cv.CV_FONT_HERSHEY_PLAIN, 1, cvRed)
355 cv2.rectangle(img, gt.topLeftPositions[frameNum-gt.getFirstInstant()].asint().astuple(), gt.bottomRightPositions[frameNum-gt.getFirstInstant()].asint().astuple(), color)
356 # saving images and going to next
325 if not saveAllImages: 357 if not saveAllImages:
326 cvImshow(windowName, img, rescale) 358 cvImshow(windowName, img, rescale)
327 key = cv2.waitKey() 359 key = cv2.waitKey()
328 if saveAllImages or saveKey(key): 360 if saveAllImages or saveKey(key):
329 cv2.imwrite('image-{{:0{}}}.png'.format(nZerosFilename).format(frameNum), img) 361 cv2.imwrite('image-{{:0{}}}.png'.format(nZerosFilename).format(frameNum), img)