def __init__(self, cfg): super().__init__() self.cfg = cfg self.predictor = make_box_predictor(cfg) self.loss_evaluator = MultiBoxLoss(neg_pos_ratio=cfg.MODEL.NEG_POS_RATIO) self.post_processor = PostProcessor(cfg) self.priors = None
def __init__(self, cfg): super().__init__() self.cfg = cfg self.predictor = make_box_predictor(cfg) self.loss_evaluator = MultiBoxLoss(neg_pos_ratio=cfg.MODEL.NEG_POS_RATIO) self.mask_criterion = Mask_BCELoss(2, 0.5, True, 0, True, 3, 0.5, False) self.post_processor = PostProcessor(cfg) self.priors = None
def __init__(self, cfg): super().__init__() self.cfg = cfg self.predictor = make_box_predictor(cfg) self.loss_evaluator = MultiBoxLoss(neg_pos_ratio=cfg.MODEL.NEG_POS_RATIO,num_classes=cfg.MODEL.NUM_CLASSES, alpha=None,gamma=2 ) self.post_processor = PostProcessor(cfg) self.priors = None
def __init__(self, cfg): super().__init__() self.cfg = cfg self.predictor = make_box_predictor(cfg) # if self.cfg.MODEL.BOX_HEAD.LOSS == 'FocalLoss': self.loss_evaluator = FocalLoss(0.25, 2) else: # By default, we use MultiBoxLoss self.loss_evaluator = MultiBoxLoss( neg_pos_ratio=cfg.MODEL.NEG_POS_RATIO) self.post_processor = PostProcessor(cfg) self.priors = None