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>
2026-05-25 16:59:59 +08:00
commit 7c43b44c57
1619 changed files with 373355 additions and 0 deletions
--- a/algorithms/lane_ufld/code/UFLD/vis_tusimple_pred.py
+++ b/algorithms/lane_ufld/code/UFLD/vis_tusimple_pred.py
@@ -0,0 +1,66 @@
+"""Visualize TuSimple-format predictions from test.py (tusimple_eval_tmp.0.txt)."""
+
+import argparse
+import json
+import os
+
+import cv2
+
+LANE_COLORS = [(0, 255, 0), (0, 0, 255), (255, 0, 0), (0, 255, 255)]
+
+
+def draw_lanes(img, lanes, h_samples):
+    for lane_idx, xs in enumerate(lanes):
+        color = LANE_COLORS[lane_idx % len(LANE_COLORS)]
+        pts = [(int(x), int(y)) for x, y in zip(xs, h_samples) if x >= 0]
+        for i in range(len(pts) - 1):
+            cv2.line(img, pts[i], pts[i + 1], color, 3)
+        for p in pts:
+            cv2.circle(img, p, 4, color, -1)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--pred',
+        default='tmp/tusimple_eval_tmp.0.txt',
+        help='prediction jsonl from test.py',
+    )
+    parser.add_argument(
+        '--data_root',
+        default='/home/chengfanglu/DATA/lane0_copy/DATASET',
+        help='dataset root (images under data_root/raw_file)',
+    )
+    parser.add_argument(
+        '--out_dir',
+        default='tmp/vis_pred',
+        help='directory to save overlay images',
+    )
+    args = parser.parse_args()
+
+    os.makedirs(args.out_dir, exist_ok=True)
+    n_ok = 0
+    with open(args.pred, 'r') as f:
+        for line in f:
+            item = json.loads(line)
+            rel = item['raw_file']
+            img_path = os.path.join(args.data_root, rel)
+            if not os.path.isfile(img_path):
+                print('skip (missing):', img_path)
+                continue
+            img = cv2.imread(img_path)
+            if img is None:
+                print('skip (read failed):', img_path)
+                continue
+            draw_lanes(img, item['lanes'], item['h_samples'])
+            out_path = os.path.join(args.out_dir, rel)
+            os.makedirs(os.path.dirname(out_path), exist_ok=True)
+            cv2.imwrite(out_path, img)
+            n_ok += 1
+            print('saved', out_path)
+
+    print(f'done: {n_ok} images -> {args.out_dir}')
+
+
+if __name__ == '__main__':
+    main()