feat: 导入 IRSTD 研究代码与文档（小目标检测）

- 新增 irstd 核心包、scripts、tests、configs
- 新增研究文档：literature_review / mathematical_analysis / novelty_matrix / experiment_plan / research_decision / research_log / manuscript_outline
- 新增 evidence、results 数据与审计产物
- 新增 pyproject.toml、requirements、.gitignore

scripts/predict.py

@@ -0,0 +1,20 @@
+import argparse,json
+from pathlib import Path
+import numpy as np
+import torch
+from irstd.models import TinyUNet
+from irstd.data import read_manifest,read_pair,sha
+
+def main():
+ p=argparse.ArgumentParser();p.add_argument('--manifest',required=True);p.add_argument('--checkpoint',required=True)
+ p.add_argument('--out',required=True);p.add_argument('--device',default='cuda');a=p.parse_args()
+ ck=torch.load(a.checkpoint,map_location='cpu',weights_only=True)
+ model=TinyUNet().to(a.device);model.load_state_dict(ck['state_dict']);model.eval()
+ out=Path(a.out);out.mkdir(parents=True,exist_ok=False)
+ with torch.no_grad():
+  for r in read_manifest(a.manifest):
+   x,_=read_pair(r)
+   prob=model(torch.from_numpy(x)[None,None].to(a.device)).sigmoid()[0,0].cpu().numpy()
+   np.save(out/(r['id']+'.npy'),prob)
+ (out/'provenance.json').write_text(json.dumps(dict(checkpoint_sha256=sha(a.checkpoint),manifest_sha256=sha(a.manifest)),indent=2))
+if __name__=='__main__':main()