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) fs[-1].draw()