labels = []
imgs = []
# for each person grab a training set of images
# and generate a list of labels.
for name in names:
myStr = "Training for : " + name
iset = get_face_set(cam, myStr)
imgs += iset
labels += [name for i in range(0,len(iset))]
time.sleep(waitTime)
# Create, train, and save the recognizer.
t = Trainer()
t.labels = labels
t.images = imgs
f = t.do_the_train()
# f = FaceRecognizer()
# print f.train(imgs, labels)
# f.save("test.csv")
# show the results
disp = Display((640,480))
while disp.isNotDone():
try:
img = cam.getImage()
fs = img.findHaarFeatures('face.xml')
if fs is not None and fs != []:
fs = fs.sortArea()
face = fs[-1].crop().resize(100,100)
