passedArgs = {}
extractArgs = {}
if args.embedding_path is not None:
passedArgs['embedding_path'] = args.embedding_path
extractArgs['embedding_path'] = args.embedding_path
if args.recognizer_path is not None:
passedArgs['recognizer_path'] = args.recognizer_path
if args.le_path is not None:
passedArgs['le_path'] = args.le_path
if args.train:
trainer.train_model(**passedArgs)
else:
passedArgs['width'] = args.width
passedArgs['min_conf'] = args.conf
recognizer = Recognizer(**passedArgs)
if args.training_images_path is not None:
extractArgs['training_images_path'] = args.training_images_path
if args.extract:
recognizer.extractor.extract_and_write_embeddings(
**extractArgs)
else:
if 'embedding_path' in extractArgs:
del extractArgs['embedding_path']
recognizer.extract_and_train(**extractArgs)
