Mercurial > hg > nsaunier > traffic-intelligence

comparison python/cvutils.py @ 1015:cf9d29de3dbf

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merge With Pr Saunier's code
author Wendlasida
date Mon, 04 Jun 2018 11:25:49 -0400
parents a5f2309bb1ff
children 16932cefabc1
comparison
equal deleted inserted replaced
1014:026f6b3b122c 1015:cf9d29de3dbf
16 print('Scikit-image library could not be loaded (HoG-based classification methods will not be available)') 16 print('Scikit-image library could not be loaded (HoG-based classification methods will not be available)')
17 skimageAvailable = False 17 skimageAvailable = False
18 18
19 from sys import stdout 19 from sys import stdout
20 from os import listdir 20 from os import listdir
21 from subprocess import check_call 21 from subprocess import run
22 from math import floor, log10, ceil 22 from math import floor, log10, ceil
23 23
24 from numpy import dot, array, append, float32, loadtxt, savetxt, append, zeros, ones, identity, abs as npabs, logical_and, unravel_index, sum as npsum, isnan, mgrid, median, floor as npfloor, ceil as npceil 24 from numpy import dot, array, append, float32, loadtxt, savetxt, append, zeros, ones, identity, abs as npabs, logical_and, unravel_index, sum as npsum, isnan, mgrid, median, floor as npfloor, ceil as npceil
25 from numpy.linalg import inv 25 from numpy.linalg import inv
26 from matplotlib.mlab import find 26 from matplotlib.mlab import find
280 if yCropMax != yCropMin and xCropMax != xCropMin and (yCropMax - yCropMin) * (xCropMax - xCropMin) > minNPixels: 280 if yCropMax != yCropMin and xCropMax != xCropMin and (yCropMax - yCropMin) * (xCropMax - xCropMin) > minNPixels:
281 return img[yCropMin : yCropMax, xCropMin : xCropMax] 281 return img[yCropMin : yCropMax, xCropMin : xCropMax]
282 else: 282 else:
283 return None 283 return None
284 284
285 def tracking(configFilename, grouping, videoFilename = None, dbFilename = None, homographyFilename = None, maskFilename = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None): 285 def tracking(configFilename, grouping, videoFilename = None, dbFilename = None, homographyFilename = None, maskFilename = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, dryRun = False):
286 '''Runs the tracker in a subprocess 286 '''Runs the tracker in a subprocess
287 if grouping is True, it is feature grouping 287 if grouping is True, it is feature grouping
288 otherwise it is feature tracking''' 288 otherwise it is feature tracking'''
289 if grouping: 289 if grouping:
290 trackingMode = '--gf' 290 trackingMode = '--gf'
301 if maskFilename is not None: 301 if maskFilename is not None:
302 cmd += ['--mask-filename', maskFilename] 302 cmd += ['--mask-filename', maskFilename]
303 if undistort: 303 if undistort:
304 cmd += ['--undistort', 'true'] 304 cmd += ['--undistort', 'true']
305 if intrinsicCameraMatrix is not None: # we currently have to save a file 305 if intrinsicCameraMatrix is not None: # we currently have to save a file
306 pass#from time import time 306 from time import time
307 #savetxt 307 intrinsicCameraFilename = '/tmp/intrinsic-{}.txt'.format(time())
308 #cmd += [] 308 savetxt(intrinsicCameraFilename, intrinsicCameraMatrix)
309 cmd += ['--intrinsic-camera-filename', intrinsicCameraFilename]
309 if distortionCoefficients is not None: 310 if distortionCoefficients is not None:
310 cmd += ['--distortion-coefficients', ' '.join([str(x) for x in distortionCoefficients])] 311 cmd += ['--distortion-coefficients '+' '.join([str(x) for x in distortionCoefficients])]
311 312 if dryRun:
312 #check_call([trackerExe, configFilename, trackingMode]) # , stderr = out, shell = True 313 print(cmd)
313 print(cmd) # , stderr = out, shell = True 314 else:
315 run(cmd)
314 316
315 def displayTrajectories(videoFilename, objects, boundingBoxes = {}, homography = None, firstFrameNum = 0, lastFrameNumArg = None, printFrames = True, rescale = 1., nFramesStep = 1, saveAllImages = False, nZerosFilenameArg = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1., annotations = [], gtMatches = {}, toMatches = {}, colorBlind = False): 317 def displayTrajectories(videoFilename, objects, boundingBoxes = {}, homography = None, firstFrameNum = 0, lastFrameNumArg = None, printFrames = True, rescale = 1., nFramesStep = 1, saveAllImages = False, nZerosFilenameArg = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1., annotations = [], gtMatches = {}, toMatches = {}, colorBlind = False):
316 '''Displays the objects overlaid frame by frame over the video ''' 318 '''Displays the objects overlaid frame by frame over the video '''
317 if colorBlind: 319 if colorBlind:
318 colorType = 'colorblind' 320 colorType = 'colorblind'