def build_train_loader(cls, cfg: CfgNode):
data_loader = build_detection_train_loader(cfg, mapper=DatasetMapper(cfg, True))
if not has_inference_based_loaders(cfg):
return data_loader
model = cls.build_model(cfg)
model.to(cfg.BOOTSTRAP_MODEL.DEVICE)
DetectionCheckpointer(model).resume_or_load(cfg.BOOTSTRAP_MODEL.WEIGHTS, resume=False)
inference_based_loaders, ratios = build_inference_based_loaders(cfg, model)
loaders = [data_loader] + inference_based_loaders
ratios = [1.0] + ratios
combined_data_loader = build_combined_loader(cfg, loaders, ratios)
sample_counting_loader = SampleCountingLoader(combined_data_loader)
return sample_counting_loader
def build_test_loader(cls, cfg: CfgNode, dataset_name):
return build_detection_test_loader(cfg,
dataset_name,
mapper=DatasetMapper(cfg, False))
def build_train_loader(cls, cfg: CfgNode):
return build_detection_train_loader(cfg,
mapper=DatasetMapper(cfg, True))