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/pytorch-auto-drive-master/main_semseg.py

@@ -0,0 +1,64 @@
+import torch
+import argparse
+try:
+    from utils.common import warnings
+except ImportError:
+    import warnings
+
+from utils.args import parse_arg_cfg, read_config, map_states, add_shortcuts, cmd_dict
+from utils.runners import SegTrainer, SegTester
+
+
+if __name__ == '__main__':
+    # Settings (user input > config > argparse defaults)
+    parser = argparse.ArgumentParser(description='PytorchAutoDrive Semantic Segmentation', conflict_handler='resolve')
+    add_shortcuts(parser)
+
+    # Required args
+    parser.add_argument('--config', type=str, help='Path to config file', required=True)
+    group = parser.add_mutually_exclusive_group(required=True)
+    group.add_argument('--train', action='store_true')
+    group.add_argument('--val', action='store_true')  # There is no test labels available for these datasets
+    group.add_argument('--state', type=int,
+                       help='[Deprecated] validation set testing(1)/training(0)')
+
+    # Optional args/to overwrite configs
+    group2 = parser.add_mutually_exclusive_group()
+    group2.add_argument('--continue-from', type=str,
+                        help='[Deprecated] Continue training from a previous checkpoint')
+    group2.add_argument('--checkpoint', type=str,
+                        help='Continue/Load from a previous checkpoint')
+
+    # Optional args/to overwrite configs
+    group2 = parser.add_mutually_exclusive_group()
+    group2.add_argument('--continue-from', type=str,
+                        help='[Deprecated] Continue training from a previous checkpoint')
+    group2.add_argument('--checkpoint', type=str,
+                        help='Continue/Load from a previous checkpoint')
+
+    parser.add_argument('--mixed-precision', action='store_true',
+                        help='Enable mixed precision training')
+    parser.add_argument('--cfg-options', type=cmd_dict,
+                        help='Override config options with \"x1=y1 x2=y2 xn=yn\"')
+
+    states = ['train', 'val']
+    retain_args = ['state', 'mixed_precision']
+
+    args = parser.parse_args()
+    if args.state is not None:
+        warnings.warn('--state={} is deprecated, it is recommended to specify with --{}'.format(
+            args.state, states[args.state]))
+    args.state = map_states(args, states)
+    if args.mixed_precision and torch.__version__ < '1.6.0':
+        warnings.warn('PyTorch version too low, mixed precision training is not available.')
+
+    # Parse configs and execute runner
+    cfg = read_config(args.config)
+    cfg_runner_key = 'train' if args.state == 0 else 'test'
+    Runner = SegTrainer if args.state == 0 else SegTester
+    args, cfg = parse_arg_cfg(args, cfg)
+    for k in retain_args:
+        cfg[cfg_runner_key][k] = vars(args)[k]
+    runner = Runner(cfg=cfg)
+    runner.run()
+    runner.clean()