how to train a face-recognizer with new additional pictures?

recognizer= cv2.face.createLBPHFaceRecognizer()
if os.path.exists("recognizer\\trainingData_LBPHF.yml"):
    recognizer.load("recognizer\\trainingData_LBPHF.yml")
IDs,faces=retrainer(directory)
recognizer.train(faces,IDs)

While I run this code my recognizer retrain on new pictures but lose everything that had been done before. Is there a way to retrain my recognizer on new additional pictures without retraining on the old ones in order to accelerate the processing?

Solution

You need to call update:

recognizer.update(faces, IDs)

This method updates a (probably trained) FaceRecognizer, but only if the algorithm supports it. The Local Binary Patterns Histograms (LBPH) recognizer (see createLBPHFaceRecognizer) can be updated.