def val_dataloader(self): return DataLoader( FaceDetectionDataset( label_path=self.hparams["val_annotation_path"], image_path=self.hparams["val_image_path"], transform=from_dict(self.hparams["val_aug"]), preproc=self.preproc, ), batch_size=self.hparams["val_parameters"]["batch_size"], num_workers=self.hparams["num_workers"], shuffle=False, pin_memory=True, drop_last=True, collate_fn=detection_collate, )
def val_dataloader(self) -> DataLoader: result = DataLoader( FaceDetectionDataset( label_path=VAL_LABEL_PATH, image_path=VAL_IMAGE_PATH, transform=from_dict(self.config.val_aug), preproc=self.preproc, rotate90=self.config.val_parameters.rotate90, ), batch_size=self.config.val_parameters.batch_size, num_workers=self.config.num_workers, shuffle=False, pin_memory=True, drop_last=True, collate_fn=detection_collate, ) return result
def train_dataloader(self): result = DataLoader( FaceDetectionDataset( label_path=TRAIN_LABEL_PATH, image_path=TRAIN_IMAGE_PATH, transform=from_dict(self.config.train_aug), preproc=self.preproc, rotate90=self.config.train_parameters.rotate90, ), batch_size=self.config.train_parameters.batch_size, num_workers=self.config.num_workers, shuffle=True, pin_memory=True, drop_last=False, collate_fn=detection_collate, ) print("Len train dataloader = ", len(result)) return result