def build_transform(cfg):
tfs = []
for icfg in cfg:
if TRANSFORMS.get(icfg.get('type')) is not None:
tf = build_from_cfg(icfg, TRANSFORMS)
elif hasattr(alb, icfg.get('type')):
if icfg.get('interpolation') and icfg.get(
'interpolation') in CV2_MODE:
icfg['interpolation'] = CV2_MODE[icfg.get('interpolation')]
if icfg.get('border_mode') and icfg.get(
'border_mode') in CV2_BORDER_MODE:
icfg['border_mode'] = CV2_BORDER_MODE[icfg.get('border_mode')]
tf = build_from_cfg(icfg, alb, mode='module')
else:
raise AttributeError(f"Invalid class {icfg.get('type')}")
tfs.append(tf)
aug = alb.Compose(
transforms=tfs,
p=1,
keypoint_params=alb.KeypointParams(format='xy',
remove_invisible=False),
)
return aug
def build_datasets(cfg, default_args=None):
datasets = []
for icfg in cfg:
ds = build_from_cfg(icfg, DATASETS, default_args)
datasets.append(ds)
return datasets
def build_criterion(cfgs):
criterion_list = []
for cfg in cfgs:
criterion = build_from_cfg(cfg, CRITERIA, mode='registry')
criterion_list.append(criterion)
return criterion_list
def build_brick(cfg, default_args=None):
brick = build_from_cfg(cfg, BRICKS, default_args)
return brick
def build_lr_scheduler(cfg, default_args=None):
scheduler = build_from_cfg(cfg, LR_SCHEDULERS, default_args, 'registry')
return scheduler
def build_enhance(cfg, default_args=None):
decoder = build_from_cfg(cfg, ENHANCE, default_args)
return decoder
def build_backbone(cfg, default_args=None):
backbone = build_from_cfg(cfg, BACKBONES, default_args)
return backbone
def build_collate_fn(cfg, default_args=None):
collate_fn = build_from_cfg(cfg, COLLATE_FN, default_args)
return collate_fn
def build_dataloader(cfg, default_args=None):
dataloader = build_from_cfg(cfg, DATALOADERS, default_args)
return dataloader
def build_enhance_module(cfg, default_args=None):
enhance_module = build_from_cfg(cfg, ENHANCE_MODULES, default_args)
return enhance_module
def build_optimizer(cfg, default_args=None):
optim = build_from_cfg(cfg, torch_optim, default_args, 'module')
return optim
def build_head(cfg, default_args=None):
heads = build_from_cfg(cfg, HEADS, default_args)
return heads
def build_module(cfg, default_args=None):
util = build_from_cfg(cfg, UTILS, default_args)
return util
def build_torch_nn(cfg, default_args=None):
module = build_from_cfg(cfg, nn, default_args, 'module')
return module