File size: 1,549 Bytes
ce209f5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | from __future__ import annotations
from pathlib import Path
from wrapper_common import ROOT, main_for
def make_changer_config(dataset_cfg: dict, output_path: str) -> str:
template = ROOT / "model_repos/open-cd/configs/changer/changer_ex_r18_512x512_40k_levircd.py"
out = Path(output_path)
out.parent.mkdir(parents=True, exist_ok=True)
rel_template = template.relative_to(out.parent).as_posix() if template.is_relative_to(out.parent) else str(template)
out.write_text(
"\n".join([
"# Generated by train/train_changer.py",
f"_base_ = [{rel_template!r}]",
f"data_root = {dataset_cfg['data_root']!r}",
f"crop_size = ({int(dataset_cfg.get('img_size', 256))}, {int(dataset_cfg.get('img_size', 256))})",
f"train_dataloader = dict(batch_size={int(dataset_cfg.get('batch_size', 8))}, num_workers={int(dataset_cfg.get('num_workers', 4))}, dataset=dict(data_root=data_root))",
f"val_dataloader = dict(batch_size=1, num_workers={int(dataset_cfg.get('num_workers', 4))}, dataset=dict(data_root=data_root))",
f"test_dataloader = dict(batch_size=1, num_workers={int(dataset_cfg.get('num_workers', 4))}, dataset=dict(data_root=data_root))",
f"data_preprocessor = dict(mean={dataset_cfg.get('mean_a', [0.485, 0.456, 0.406])!r}, std={dataset_cfg.get('std_a', [0.229, 0.224, 0.225])!r})",
"",
]),
encoding="utf-8",
)
return str(out)
if __name__ == "__main__":
raise SystemExit(main_for("changer"))
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