def __init__(self, ckpt_path=None, gpu='0'):
print('Classifier_Vietocr. Init')
self.config = Cfg.load_config(cls_base_config_path, cls_config_path)
if ckpt_path is not None:
self.config['weights'] = ckpt_path
self.config['cnn']['pretrained'] = False
if gpu is not None:
self.config['device'] = 'cuda:' + str(gpu)
else:
self.config['device'] = 'cpu'
self.config['predictor']['beamsearch'] = False
self.model = Predictor(self.config)
def __init__(self):
self.yolo = YOLOv4()
self.yolo.classes = './coco.names'
self.yolo.make_model()
self.yolo.load_weights("./model/yolov4-custom_last.weights",
weights_type="yolo")
self.config = Cfg.load_config()
self.config['weights'] = './model/transformerocr.pth'
self.config['predictor']['beamsearch'] = False
self.config['device'] = 'cpu'
self.detector = Predictor(self.config)
self.classes = ['id', 'name', 'dmy', 'add1', 'add2']
self.res = dict.fromkeys(self.classes, '')