Add 3 segmentation classes for UAV_VisLoc: bare soil, rooftop, sports field

Analysis of scene 01 showed 29% background pixels, mainly caused by:
- Plowed/bare fields (no crop match) → add "bare soil and plowed field"
- Dark/textured roofs missed by "building" → add "roof and rooftop"
- Sports fields/playgrounds → add "sports field and playground"

Total: 11 → 14 classes. Palette extended with 3 new colors.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

scripts/run_uav_visloc.py

@@ -74,9 +74,20 @@ def main() -> None:
 
     input_conf = InputConfig(image_size=256)
     seg_conf = SegConfig(prompts=[
-        "background", "building", "road", "vegetation", "water",
+        "background",                   # 0
-        "sand and gravel ground", "rocky terrain", "farmland",
+        "building",                     # 1
-        "railway", "parking lot", "sidewalk",
+        "road",                         # 2
+        "vegetation",                   # 3
+        "water",                        # 4
+        "sand and gravel ground",       # 5
+        "rocky terrain",                # 6
+        "farmland",                     # 7
+        "railway",                      # 8
+        "parking lot",                  # 9
+        "sidewalk",                     # 10
+        "bare soil and plowed field",   # 11
+        "roof and rooftop",             # 12
+        "sports field and playground",  # 13
     ])
     models_conf = ModelsConfig(weights_dir=str(_PROJECT_ROOT / "in" / "weights"))
 

src/augmentor/io_utils.py

@@ -94,6 +94,9 @@ _FIXED_PALETTE = np.array([
     [100,  60, 120],  # 8:  railway      — purple
     [255, 165,   0],  # 9:  parking lot  — orange
     [200, 200, 200],  # 10: sidewalk     — light gray
+    [140, 100,  50],  # 11: bare soil    — dark tan
+    [180,  60,  60],  # 12: rooftop      — dark red
+    [50,  200, 150],  # 13: sports field — teal
 ], dtype=np.uint8)