def setup(self, stage=None):
super().setup(stage=stage)
cfg = self.cfg
if HydraConfig.initialized():
# Current directory changed!
# Update paths with original_cwd
csv_path = to_absolute_path(cfg.data.csv_path)
root_dir = to_absolute_path(cfg.data.root_dir)
else:
# Keep relative paths
csv_path = cfg.data.csv_path
root_dir = cfg.data.root_dir
df = pd.read_csv(csv_path)
df[["x", "y", "x1", "y1"]] = pd.DataFrame(
np.stack(df["box"].apply(ast.literal_eval)).astype(np.float32)
)
train_df = df.loc[df["fold"] != cfg.data.valid_fold].copy()
valid_df = df.loc[df["fold"] == cfg.data.valid_fold].copy()
self.train_dataset = PennFudanDataset(
train_df,
root_dir=root_dir,
transforms=self.train_transforms,
mode="train",
)
self.val_dataset = PennFudanDataset(
valid_df, root_dir=root_dir, transforms=self.val_transforms, mode="val"
)
def get_output_dir(subfolder: Optional[str] = None) -> str:
"""Return an unique output dir based on the configuration overrides"""
path = HydraConfig.get().run.dir
if subfolder is not None:
name = os.path.basename(path)
path = os.path.dirname(path)
path = os.path.join(path, subfolder, name)
if not os.path.exists(path):
os.makedirs(path)
return path
def __init__(self, cfg: DictConfig, train_transforms=None, val_transforms=None):
super().__init__(
train_transforms=train_transforms,
val_transforms=val_transforms,
test_transforms=val_transforms,
)
self.train_transforms = train_transforms
self.val_transforms = val_transforms
self.cfg = cfg
if HydraConfig.initialized():
# Current directory changed!
# Update paths with original_cwd
self.data_csv_path = to_absolute_path(cfg.data.csv_path)
self.root_dir = to_absolute_path(cfg.data.root_dir)
else:
# Keep relative paths
self.data_csv_path = cfg.data.csv_path
self.root_dir = cfg.data.root_dir
def get_sweep_dir() -> str:
return HydraConfig.get().sweep.dir
def get_overrides() -> str:
"""Return the configuration overrides"""
return HydraConfig.get().job.override_dirname
def get_hydra_config() -> DictConfig:
r""" Return the configuration """
return HydraConfig.get()
def get_output_dir() -> str: r""" Return an unique output dir based on the configuration overrides """ return HydraConfig.get().run.dir
def get_output_dir() -> str: r""" Specific output dir based on the override """ return HydraConfig.get().run.dir
def get_overrides() -> str: return HydraConfig.get().job.override_dirname
def get_hydra_config() -> DictConfig: return HydraConfig.get()
