def main(doTubeFormat, inFileName, outTrajIDfileName, featPath, nrTrajThresh4Tube=0):
tube2trajIDs.check()
outPath = os.path.dirname(outTrajIDfileName)
if not os.path.exists( outPath ):
os.makedirs(outPath)
# read trajectory positions
print '\tGet trajectory positions;',
geoFeat = denseTraj.getFeatFromFileByName(featPath, 'geo')
# if proposals are stored as Tubes already, read them
if doTubeFormat:
tubeProposals = TubeList()
tubeProposals.readHDF5(inFileName)
# initialize with a single name
inHDF5fileClusts = ['tubes']
else:
print '\tGet video dimensions;',
vidInfo = denseTraj.getFeatFromFileByName(featPath, 'vidinfo')
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File( inFileName, 'r')
# go over all features
totNrProposals = 0
for featName in inHDF5fileClusts:
if not doTubeFormat:
# get the clustered proposals for this feature type in SLINK pointer-representation
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(mergedTracks, geoFeat, nrTrajThresh4Tube, xmax, ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s", number of proposals: %d;' % (featName,nrProposals)
# if ok
if nrProposals > 0:
# write as traj IDs
if totNrProposals==0:
outHDF5file = h5py.File( outTrajIDfileName, 'w', compression="gzip", compression_opts=9)
for j in range(nrProposals):
trajIDs = tubeProposals[j].tube2trajIDs(geoFeat)
outHDF5file.create_dataset(str(totNrProposals), data=trajIDs)
totNrProposals += 1
print '\tWrite trajectory IDs to', outTrajIDfileName
outHDF5file.close()
def main(inFileName, featPath, nrTrajThresh4Tube, outFileName):
#print inFileName, featPath, nrTrajThresh4Tube, outFileName
#sys.exit()
outPath = os.path.dirname(outFileName)
if not os.path.exists(outPath):
os.makedirs(outPath)
# output file
print '\tWrite tubes to: %s' % (outFileName)
outHDF5fileTubes = h5py.File(outFileName, 'w')
# get the trajectory locations
geoFeat = denseTraj.getFeatFromFileByName(featPath, 'geo')
# get vid info (length, width, height)
vidInfo = denseTraj.getFeatFromFileByName(featPath, 'vidinfo')
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File(inFileName, 'r')
propOutstartID = 0
for featName in inHDF5fileClusts:
# get the clustered proposals for this feature type in SLINK pointer-representation
#featName = featNames[featNameID]
#fnameSS = os.path.join(inPath, featName + suffixIn + '.npy')
#mergedTracks = np.load( fnameSS )
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals and write to disk
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(mergedTracks, geoFeat,
nrTrajThresh4Tube, xmax,
ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s"; Number of proposals: %d' % (featName,
nrProposals),
# if OK
if nrProposals > 0:
# write to file
#print '; writing proposals:', outPath
tubeProposals.writeHDF5(outHDF5fileTubes, propOutstartID)
propOutstartID += nrProposals
print 'tot:', propOutstartID
# close the file
outHDF5fileTubes.close()
def main(inFileName, featPath, nrTrajThresh4Tube, outFileName):
# print inFileName, featPath, nrTrajThresh4Tube, outFileName
# sys.exit()
outPath = os.path.dirname(outFileName)
if not os.path.exists(outPath):
os.makedirs(outPath)
# output file
print "\tWrite tubes to: %s" % (outFileName)
outHDF5fileTubes = h5py.File(outFileName, "w")
# get the trajectory locations
geoFeat = denseTraj.getFeatFromFileByName(featPath, "geo")
# get vid info (length, width, height)
vidInfo = denseTraj.getFeatFromFileByName(featPath, "vidinfo")
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File(inFileName, "r")
propOutstartID = 0
for featName in inHDF5fileClusts:
# get the clustered proposals for this feature type in SLINK pointer-representation
# featName = featNames[featNameID]
# fnameSS = os.path.join(inPath, featName + suffixIn + '.npy')
# mergedTracks = np.load( fnameSS )
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals and write to disk
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(mergedTracks, geoFeat, nrTrajThresh4Tube, xmax, ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s"; Number of proposals: %d' % (featName, nrProposals),
# if OK
if nrProposals > 0:
# write to file
# print '; writing proposals:', outPath
tubeProposals.writeHDF5(outHDF5fileTubes, propOutstartID)
propOutstartID += nrProposals
print "tot:", propOutstartID
# close the file
outHDF5fileTubes.close()
def main(doTubeFormat, inFileName, outIoUfile, gtPath, nrTrajThresh4Tube=-1, featPath=''):
# check if cython is used
tubeIoU.check()
# read ground truth tubes
print '\tRead ground truth;',
gtTubes = TubeList()
gtTubes.readHDF5(gtPath)
outPath = os.path.dirname(outIoUfile)
if not os.path.exists( outPath ):
os.makedirs(outPath)
# if proposals are stored as Tubes already, read them
if doTubeFormat:
tubeProposals = TubeList()
tubeProposals.readHDF5(inFileName)
# initialize with a single name
inHDF5fileClusts = ['tubes']
else:
# otherwise, read trajectory positions and vidinfo to generate proposals later
print '\tGet trajectory positions;',
geoFeat = denseTraj.getFeatFromFileByName(featPath, 'geo')
print '\tGet video dimensions;',
vidInfo = denseTraj.getFeatFromFileByName(featPath, 'vidinfo')
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File( inFileName, 'r')
aboMax = []
# go over all features
for featName in inHDF5fileClusts:
if not doTubeFormat:
# get the clustered proposals for this feature type in SLINK pointer-representation
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(mergedTracks, geoFeat, nrTrajThresh4Tube, xmax, ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s", number of proposals: %d;' % (featName,nrProposals),
# if ok
if nrProposals > 0:
# get Intersection over Union scores
aboMatCur = tubeProposals.computeTubeOverlap(gtTubes)
# if first feature, write to new file otherwise append to existing file
if aboMax == []:
fileOut = open(outIoUfile, 'w')
else:
fileOut = open(outIoUfile, 'a')
# write scores
for prop in range(aboMatCur.shape[0]):
for score in aboMatCur[prop,:]:
fileOut.write('%f ' % score)
fileOut.write('\n')
fileOut.close()
# keep track of the maximum score
curMax = np.max(aboMatCur, axis=0)
if aboMax == []:
aboMax = curMax
else:
aboMax = np.maximum( aboMax, curMax)
print 'Best IoUs:', curMax, '; Best so far:', aboMax
print '\tWriting IoU scores to', outIoUfile
if not doTubeFormat:
inHDF5fileClusts.close()
def main(doTubeFormat,
inFileName,
outIoUfile,
gtPath,
nrTrajThresh4Tube=-1,
featPath=''):
# check if cython is used
tubeIoU.check()
# read ground truth tubes
print '\tRead ground truth;',
gtTubes = TubeList()
gtTubes.readHDF5(gtPath)
outPath = os.path.dirname(outIoUfile)
if not os.path.exists(outPath):
os.makedirs(outPath)
# if proposals are stored as Tubes already, read them
if doTubeFormat:
tubeProposals = TubeList()
tubeProposals.readHDF5(inFileName)
# initialize with a single name
inHDF5fileClusts = ['tubes']
else:
# otherwise, read trajectory positions and vidinfo to generate proposals later
print '\tGet trajectory positions;',
geoFeat = denseTraj.getFeatFromFileByName(featPath, 'geo')
print '\tGet video dimensions;',
vidInfo = denseTraj.getFeatFromFileByName(featPath, 'vidinfo')
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File(inFileName, 'r')
aboMax = []
# go over all features
for featName in inHDF5fileClusts:
if not doTubeFormat:
# get the clustered proposals for this feature type in SLINK pointer-representation
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(
mergedTracks, geoFeat, nrTrajThresh4Tube, xmax, ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s", number of proposals: %d;' % (featName,
nrProposals),
# if ok
if nrProposals > 0:
# get Intersection over Union scores
aboMatCur = tubeProposals.computeTubeOverlap(gtTubes)
# if first feature, write to new file otherwise append to existing file
if aboMax == []:
fileOut = open(outIoUfile, 'w')
else:
fileOut = open(outIoUfile, 'a')
# write scores
for prop in range(aboMatCur.shape[0]):
for score in aboMatCur[prop, :]:
fileOut.write('%f ' % score)
fileOut.write('\n')
fileOut.close()
# keep track of the maximum score
curMax = np.max(aboMatCur, axis=0)
if aboMax == []:
aboMax = curMax
else:
aboMax = np.maximum(aboMax, curMax)
print 'Best IoUs:', curMax, '; Best so far:', aboMax
print '\tWriting IoU scores to', outIoUfile
if not doTubeFormat:
inHDF5fileClusts.close()
def main(doTubeFormat,
inFileName,
outTrajIDfileName,
featPath,
nrTrajThresh4Tube=0):
tube2trajIDs.check()
outPath = os.path.dirname(outTrajIDfileName)
if not os.path.exists(outPath):
os.makedirs(outPath)
# read trajectory positions
print '\tGet trajectory positions;',
geoFeat = denseTraj.getFeatFromFileByName(featPath, 'geo')
# if proposals are stored as Tubes already, read them
if doTubeFormat:
tubeProposals = TubeList()
tubeProposals.readHDF5(inFileName)
# initialize with a single name
inHDF5fileClusts = ['tubes']
else:
print '\tGet video dimensions;',
vidInfo = denseTraj.getFeatFromFileByName(featPath, 'vidinfo')
xmax = vidInfo[1]
ymax = vidInfo[2]
# input cluster file
inHDF5fileClusts = h5py.File(inFileName, 'r')
# go over all features
totNrProposals = 0
for featName in inHDF5fileClusts:
if not doTubeFormat:
# get the clustered proposals for this feature type in SLINK pointer-representation
dset = inHDF5fileClusts[featName]
mergedTracks = dset[()]
# convert pointer-representation to tube proposals
if len(mergedTracks.shape) > 1 and mergedTracks.shape[0] > 1:
tubeProposals = denseTraj.createProposals(
mergedTracks, geoFeat, nrTrajThresh4Tube, xmax, ymax)
nrProposals = len(tubeProposals)
print '\tFeature: "%s", number of proposals: %d;' % (featName,
nrProposals)
# if ok
if nrProposals > 0:
# write as traj IDs
if totNrProposals == 0:
outHDF5file = h5py.File(outTrajIDfileName,
'w',
compression="gzip",
compression_opts=9)
for j in range(nrProposals):
trajIDs = tubeProposals[j].tube2trajIDs(geoFeat)
outHDF5file.create_dataset(str(totNrProposals), data=trajIDs)
totNrProposals += 1
print '\tWrite trajectory IDs to', outTrajIDfileName
outHDF5file.close()
