Add 80/20 random split (replaces cross-area 46/54 split)

- scripts/make_split.py: merges cross-area train+test (33,708 pairs),
  shuffles with seed=42, splits 80/20
- meta/train_80.json (26,966) + meta/test_20.json (6,742)
- After seg filter: 24,891 train / 6,252 test
- Default paths in train_gtauav.py updated to use new split

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

README.md

@@ -29,7 +29,7 @@ Loss:    InfoNCE(query, gallery)
 - Captions: `/home/servml/Документы/datasets/GTA-UAV-LR-captions/` (40K JSON, 3-paragraph VLM)
 - Segmentation: `/home/servml/Документы/datasets/GTA-UAV-LR-aug/` (17 classes)
 - Seg filter: 37,498 passed / 10,905 excluded (>=90% background+water)
-- Train: 15,693 pairs, Test: 18,015 pairs (cross-area split)
+- Split: 80/20 random (26,966 train / 6,742 test → 24,891/6,252 after seg filter)
 
 ### V2 — UAV-GeoLoc + GeoRSCLIP (legacy)
 
@@ -89,9 +89,10 @@ numpy
 
 ## Workflow (V3 — GTA-UAV)
 
-### 1. Filter segmentation (exclude uninformative images)
+### 1. Create 80/20 split and filter segmentation
 
 ```bash
+python -m scripts.make_split --output-dir meta
 python -m scripts.filter_segmentation --output meta/seg_filter.json
 ```