Update docs: CNN v2 weights loading fixed and validated

1 files changed, 9 insertions, 17 deletions

diff --git a/TODO.md b/TODO.md
index a1ee9a2..3734ec6 100644
--- a/TODO.md
+++ b/TODO.md
@@ -31,26 +31,18 @@ Enhanced CNN post-processing with multi-dimensional feature inputs.
 **Design:** `doc/CNN_V2.md`
 
 **Status:**
-- ✅ Phase 1-5: All implementation phases complete
-- ✅ Storage buffer architecture (dynamic layer count support)
-- ✅ Binary weight format (header + layer info + f16 weights)
-- ✅ Training pipeline with live progress display
-- ✅ Complete validation tooling (`train_cnn_v2_full.sh --validate`)
+- ✅ Full implementation complete and validated
+- ✅ Binary weight loading fixed (FATAL_CHECK inversion bug)
+- ✅ Training pipeline: 100 epochs, 3×3 kernels, patch-based
 - ✅ All tests passing (36/36)
 
-**Features:**
-- 7D static feature input (RGBD + UV + sin encoding + bias)
-- Storage buffer weights (~3.2 KB for 3-layer, 8→4→4 config)
-- Dynamic layer count (not hardcoded)
-- Single compute shader with per-layer params
-- Patch-based training (harris detector, 32×32 patches)
-- Fast training config: 100 epochs, 3×3 kernels
+**Specs:**
+- 7D static features (RGBD + UV + sin + bias)
+- Storage buffer weights (~3.2 KB, 8→4→4 channels)
+- Dynamic layer count, per-layer params
+- <10 KB target achieved
 
-**Performance:**
-- Storage buffer overhead: ~10-20% vs constants (negligible @ 60fps)
-- Target achieved: <10 KB for 64k demo constraint
-
-**TODO:** 8-bit quantization for 2× size reduction (~1.6 KB). Requires QAT.
+**TODO:** 8-bit quantization (2× reduction, needs QAT).
 
 ---