def create_visda_datasets(self, train_tforms, eval_tforms):
"""
Create visda datasets
:param train_tforms: training transformers
:param eval_tforms: evaluation transformers
:return:
trs_set: training source set
trt_set: training target set
tes_set: testing source set
tet_set: testing target set
"""
# Read config
cfg = load_json(self.args.cfg)
trs = cfg['SRC']['TRAIN']
trt = cfg['TGT']['TRAIN']
tes = cfg['SRC']['TRAIN']
tet = cfg['TGT']['TEST']
self.label_dict = cfg['Label']
trs_set = DomainRecDataset(trs,
trt,
tforms=train_tforms,
tformt=train_tforms,
ratio=self.args.ratio)
tes_set = DomainRecDataset(tes, tforms=eval_tforms)
tet_set = DomainRecDataset(tet, tforms=eval_tforms)
return trs_set, tes_set, tet_set
def create_office_datasets(self, train_tforms, eval_tforms):
"""
Create office datasets
:param train_tforms: training transformers
:param eval_tforms: evaluation transformers
:return:
trs_set: training source set
trt_set: training target set
tes_set: testing source set
tet_set: testing target set
"""
cfg = load_json(self.args.cfg)
cfg = split_office_train_test(cfg, 1, self.args.seed)
trs = cfg[self.args.src.upper()]['SRC-TR']
trt = cfg[self.args.tgt.upper()]['TGT-TR']
tes = cfg[self.args.src.upper()]['TGT-TE']
tet = cfg[self.args.tgt.upper()]['TGT-TE']
trs_set = DomainFolderDataset(trs,
trt,
tforms=train_tforms,
tformt=train_tforms,
ratio=self.args.ratio)
tes_set = DomainFolderDataset(tes, tforms=eval_tforms)
tet_set = DomainFolderDataset(tet, tforms=eval_tforms)
return trs_set, tes_set, tet_set
def load_office_cfg(self):
cfg = load_json(self.args.cfg)
cfg = split_office_train_test(cfg, 1, self.args.seed)
trs = cfg[self.args.src.upper()]['SRC-TR']
trt = cfg[self.args.tgt.upper()]['TGT-TR']
tes = cfg[self.args.src.upper()]['TGT-TE']
tet = cfg[self.args.tgt.upper()]['TGT-TE']
return trs, trt, tes, tet
def load_visda_cfg(self):
cfg = load_json(self.args.cfg)
trs = cfg['SRC']['TRAIN']
trt = cfg['TGT']['TRAIN']
tes = cfg['SRC']['TRAIN']
tet = cfg['TGT']['TEST']
self.label_dict = cfg['Label']
return trs, trt, tes, tet
def load_digits_cfg(self):
cfg = load_json(self.args.cfg)
cfg = split_digits_train_test(cfg, self.args.src.upper(),
self.args.tgt.upper(), 1, self.args.seed)
trs = cfg[self.args.src.upper()]['TR']
trt = cfg[self.args.tgt.upper()]['TR']
tes = cfg[self.args.src.upper()]['TE']
tet = cfg[self.args.tgt.upper()]['TE']
return trs, trt, tes, tet