newdes = des
if NANs.any() > 0:
print 'There is NAN case', np.shape(des)
newdes = des[not NANs]
print 'sahpe after', np.shape(newdes)
return newdes
if __name__ == '__main__':
# main()
# Path which contains sample files in .zip format
datapaths = ['../TestData/']
# Keep an copy the the sample files We delete what is not required
# _depth.mp4 _video.mp4 _user.mp4 and sampleXXXXX.zip files will be deteted
mytools.UnzipAllfiles(datapaths[0])
kk = 0
isAll = False
Single = True
for datapath in datapaths:
# Get the list of training samples
fileList = os.listdir(datapath)
print datapath
# Filter input files (only ZIP files)
samplelist = [
files for files in fileList if files.startswith("Sample")
]
for sample in samplelist:
#print("\t Processing file " + sample)
