pass
if( configData == True ):
print "config paths ready"
else:
print "config paths failed"
exit()
print dataPath
print modelPath
print participantList
# Creates a SAMpy object
mySAMpy = SAMDriver_faces(True, imgH = 400, imgW = 400, imgHNew = 200, imgWNew = 200,inputImagePort="/visionDriver/image:o")
# Specification of the experiment number
experiment_number = 45
# Location of face data
#root_data_dir="/home/icub/dataDump/actionFilm"
root_data_dir=dataPath
# Image format
image_suffix=".ppm"
# Array of participants to be recognised
#participant_index=('Andreas','Uriel','Tony','Daniel')
participant_index=participantList
# Poses used during the data collection
pose_index=['Seg']
# Use a subset of the data for training
# Hack: Sometimes the participant list is returned as a list of letters, instead of names.
# Check if this is the case and, if yes, fix.
if participantList.index(","):
participantList = participantList[:].split(',')
print dataPath
print modelPath
print participantList
imgHNew = 200
imgWNew = 200
# Creates a SAMpy object
mySAMpy = SAMDriver_faces(True,
imgH=400,
imgW=400,
imgHNew=imgHNew,
imgWNew=imgWNew,
inputImagePort="/visionDriver/image:o")
# Specification of the experiment number
experiment_number = 1 #45
# Location of face data
#root_data_dir="/home/icub/dataDump/actionFilm"
root_data_dir = dataPath
# Image format
image_suffix = ".ppm"
# Array of participants to be recognised
#participant_index=('Andreas','Uriel','Tony','Daniel')
participant_index = participantList
# Poses used during the data collection