feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation

Major changes:
- New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind
- 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理
- Data catalog with charts (DMS/ADAS/Lane 3-tab view)
- Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance
- Audit enhancements: batch operations, rejection categories, Feishu notifications
- Operation audit log (操作日志)
- World model simulation studio (仿真工坊)
- Dataset version management with snapshots and diff
- ADAS 7-class dataset integration (138K images organized + compressed)
- User management with Feishu integration and pagination
- CRUD/search/filter on all pages, card layout redesign
- PIL-optimized image overlay rendering
- Auto-snapshot on build, in_review workflow stage
- Removed embedded algorithm code (now in workspace)

algorithms/dms_yolo/code.embedded.bak/ultralytics/models/fastsam/utils.py

@@ -0,0 +1,23 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+
+def adjust_bboxes_to_image_border(boxes, image_shape, threshold=20):
+    """Adjust bounding boxes to stick to image border if they are within a certain threshold.
+
+    Args:
+        boxes (torch.Tensor): Bounding boxes with shape (N, 4) in xyxy format.
+        image_shape (tuple): Image dimensions as (height, width).
+        threshold (int): Pixel threshold for considering a box close to the border.
+
+    Returns:
+        (torch.Tensor): Adjusted bounding boxes with shape (N, 4).
+    """
+    # Image dimensions
+    h, w = image_shape
+
+    # Adjust boxes that are close to image borders
+    boxes[boxes[:, 0] < threshold, 0] = 0  # x1
+    boxes[boxes[:, 1] < threshold, 1] = 0  # y1
+    boxes[boxes[:, 2] > w - threshold, 2] = w  # x2
+    boxes[boxes[:, 3] > h - threshold, 3] = h  # y2
+    return boxes