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README.md

@@ -25,22 +25,28 @@ OpenVid-1M ships as 12.4 TB of ~50 GB zip parts, so selecting clips by
 caption cannot reduce what you *fetch* -- only what you keep. This is
 that selection done once: the filter below applied, every clip decoded
 to a fixed geometry, and the result packed into a flat memmap that a
-training job reads directly. Built from 16 of 186 parts.
+training job reads directly. Built from 20 of 186 parts.
 
 ## Contents
 
 | directory | clips | GOPs | filter |
 |---|---:|---:|---|
-| `openvid-head/` | 10060 | 29689 | static, low motion, >= 1 s, **and** a talking-head caption |
-| `openvid-nonperson/` | 38281 | 78593 | static, low motion, >= 1 s, and **no person mentioned at all** |
-
-They are disjoint, and a large middle is **dropped rather than
-assigned**: clips whose caption mentions a person but does not describe
-a talking head go into neither split. That is what makes the contrast
-real. An earlier version of this dataset had only "head" and
-"everything else", and "everything else" was 86% people -- 61% of it
-mentioning `wearing`, 26% `hair`, 19% `face` -- so a sweep across the
-two ran from roughly 86% head to 100% head rather than 0% to 100%.
+| `openvid-head/` | 10544 | 31051 | static, low motion, >= 1 s, **and** a talking-head caption |
+| `openvid-diverse/` | 28991 | 72831 | static, >= 1 s, quota-balanced over nine caption categories |
+
+`openvid-diverse/` is quota-balanced across animal, food, vehicle,
+text-graphic, urban, nature, interior, object and people-other, each
+assigned by first match in priority order so every clip has exactly one
+label. 85% of each quota is low motion (score < 5) and 15% is
+5-15, deliberately: a corpus with no motion in it is its own kind of
+narrow.
+
+The balance is computed over the clips **actually reachable in the
+fetched parts**, not corpus-wide, because a build fetches a handful of
+~45 GB parts and a corpus-wide quota would leave the published balance
+as whatever those parts happened to hold. That is how an earlier
+version of this dataset ended up with a "non-person" split that was
+almost entirely stock landscape footage.
 
 Talking-head captions match: