Correct split documentation: by_class is an unseen-class split, not a class-balanced one

README.md

@@ -116,15 +116,34 @@ That is what gives 222.
 
 ## Splits
 
-Two protocols. Each covers all 4,111 sequences; they are **alternatives, not nested** — say which
-one you used.
+Two protocols, each covering all 4,111 sequences. They answer different questions — **report which
+one you used.**
 
-| Protocol | Files | Train | Test |
-|---|---|---|---|
-| Sequence-level | `splits/train_t-IoU.txt` / `test_t-IoU.txt` | 3,289 | 822 |
-| Class-balanced | `splits/train_t-IoU_by_class.txt` / `test_t-IoU_by_class.txt` | 3,301 | 810 |
+### 1. Standard split — use this one by default
 
-Both are also columns (`split_tiou`, `split_by_class`) in `metadata.csv`.
+`splits/train_t-IoU.txt` (3,289) / `splits/test_t-IoU.txt` (822) · column `split_tiou`
+
+**This is the split the paper evaluates on**, and the one to use for comparable numbers. Classes
+overlap between train and test, so it measures ordinary in-distribution performance.
+
+Coverage is near-total but not exact: test covers 217 of 222 classes and train 221 of 222. The
+five classes with no test sequence are `aquatic_animal-urchin`, `human-rider`, `human-skydiver`,
+`human-swimmer`, `mammal-pig`; `sport_equipment-ice_hockey` has no train sequence. Most of these
+are classes with very few sequences overall (urchin, swimmer and ice_hockey have exactly one).
+
+### 2. Unseen-class split — for zero-shot / generalization
+
+`splits/train_t-IoU_by_class.txt` (3,301) / `splits/test_t-IoU_by_class.txt` (810) ·
+column `split_by_class`
+
+Split **along class boundaries**: 180 classes in train, 42 in test, with **zero overlap**. No test
+category is ever seen during training, so this measures generalization to novel object categories
+rather than in-distribution accuracy. Numbers from this split are not comparable with the standard
+split — they are a harder, different task.
+
+The 42 held-out classes span 14 supercategories (aircraft, aquatic_animal, bird,
+clothing_accessory, electronic, food, insect, kitchenware, mammal, personal_care, reptile,
+sport_equipment, vehicle, watercraft).
 
 ## Categories
 

scripts/download.py

@@ -48,7 +48,8 @@ def main():
     p.add_argument("--out", default="VQS-4K", help="destination directory")
     p.add_argument("--split", default="all", choices=["train", "test", "all"])
     p.add_argument("--protocol", default="tiou", choices=["tiou", "by_class"],
-                   help="which official split protocol --split refers to")
+                   help="tiou = the standard split the paper reports on (default); "
+                        "by_class = the unseen-class split, train and test share no categories")
     p.add_argument("--categories", nargs="+", metavar="NAME",
                    help="limit to these category_id or supercategory values")
     p.add_argument("--masks-only", action="store_true",