feat: initial HSAP platform

Huaxu Sentinel Active Safety Platform with embedded algorithm code,
Docker Compose setup, and vendored dataset scaffolds for clone-and-run.

Co-authored-by: Cursor <cursoragent@cursor.com>

algorithms/lane_ufld/code/CLRNet-main/clrnet/models/nets/__init__.py

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+from .detector import Detector 

algorithms/lane_ufld/code/CLRNet-main/clrnet/models/nets/detector.py

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+import torch.nn as nn
+import torch
+
+from clrnet.models.registry import NETS
+from ..registry import build_backbones, build_aggregator, build_heads, build_necks
+
+
+@NETS.register_module
+class Detector(nn.Module):
+    def __init__(self, cfg):
+        super(Detector, self).__init__()
+        self.cfg = cfg
+        self.backbone = build_backbones(cfg)
+        self.aggregator = build_aggregator(cfg) if cfg.haskey('aggregator') else None
+        self.neck = build_necks(cfg) if cfg.haskey('neck') else None
+        self.heads = build_heads(cfg)
+    
+    def get_lanes(self):
+        return self.heads.get_lanes(output)
+
+    def forward(self, batch):
+        output = {}
+        fea = self.backbone(batch['img'] if isinstance(batch, dict) else batch)
+
+        if self.aggregator:
+            fea[-1] = self.aggregator(fea[-1])
+
+        if self.neck:
+            fea = self.neck(fea)
+
+        if self.training:
+            output = self.heads(fea, batch=batch)
+        else:
+            output = self.heads(fea)
+
+        return output