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