refactor(cnn): isolate CNN v2 to cnn_v2/ subdirectory

Move all CNN v2 files to dedicated cnn_v2/ directory to prepare for CNN v3 development. Zero functional changes.

Structure:
- cnn_v2/src/ - C++ effect implementation
- cnn_v2/shaders/ - WGSL shaders (6 files)
- cnn_v2/weights/ - Binary weights (3 files)
- cnn_v2/training/ - Python training scripts (4 files)
- cnn_v2/scripts/ - Shell scripts (train_cnn_v2_full.sh)
- cnn_v2/tools/ - Validation tools (HTML)
- cnn_v2/docs/ - Documentation (4 markdown files)

Changes:
- Update CMake source list to cnn_v2/src/cnn_v2_effect.cc
- Update assets.txt with relative paths to cnn_v2/
- Update includes to ../../cnn_v2/src/cnn_v2_effect.h
- Add PROJECT_ROOT resolution to Python/shell scripts
- Update doc references in HOWTO.md, TODO.md
- Add cnn_v2/README.md

Verification: 34/34 tests passing, demo runs correctly.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

1 files changed, 16 insertions, 16 deletions

diff --git a/doc/HOWTO.md b/doc/HOWTO.md
index 0dc9ec7..a309b27 100644
--- a/doc/HOWTO.md
+++ b/doc/HOWTO.md
@@ -145,31 +145,31 @@ Enhanced CNN with parametric static features (7D input: RGBD + UV + sin encoding
 **Complete Pipeline** (recommended):
 ```bash
 # Train → Export → Build → Validate (default config)
-./scripts/train_cnn_v2_full.sh
+./cnn_v2/scripts/train_cnn_v2_full.sh
 
 # Rapid debug (1 layer, 3×3, 5 epochs)
-./scripts/train_cnn_v2_full.sh --num-layers 1 --kernel-sizes 3 --epochs 5 --output-weights test.bin
+./cnn_v2/scripts/train_cnn_v2_full.sh --num-layers 1 --kernel-sizes 3 --epochs 5 --output-weights test.bin
 
 # Custom training parameters
-./scripts/train_cnn_v2_full.sh --epochs 500 --batch-size 32 --checkpoint-every 100
+./cnn_v2/scripts/train_cnn_v2_full.sh --epochs 500 --batch-size 32 --checkpoint-every 100
 
 # Custom architecture
-./scripts/train_cnn_v2_full.sh --kernel-sizes 3,5,3 --num-layers 3 --mip-level 1
+./cnn_v2/scripts/train_cnn_v2_full.sh --kernel-sizes 3,5,3 --num-layers 3 --mip-level 1
 
 # Custom output path
-./scripts/train_cnn_v2_full.sh --output-weights workspaces/test/cnn_weights.bin
+./cnn_v2/scripts/train_cnn_v2_full.sh --output-weights workspaces/test/cnn_weights.bin
 
 # Grayscale loss (compute loss on luminance instead of RGBA)
-./scripts/train_cnn_v2_full.sh --grayscale-loss
+./cnn_v2/scripts/train_cnn_v2_full.sh --grayscale-loss
 
 # Custom directories
-./scripts/train_cnn_v2_full.sh --input training/input --target training/target_2
+./cnn_v2/scripts/train_cnn_v2_full.sh --input training/input --target training/target_2
 
 # Full-image mode (instead of patch-based)
-./scripts/train_cnn_v2_full.sh --full-image --image-size 256
+./cnn_v2/scripts/train_cnn_v2_full.sh --full-image --image-size 256
 
 # See all options
-./scripts/train_cnn_v2_full.sh --help
+./cnn_v2/scripts/train_cnn_v2_full.sh --help
 ```
 
 **Defaults:** 200 epochs, 3×3 kernels, 8→4→4 channels, batch-size 16, patch-based (8×8, harris detector).
@@ -184,33 +184,33 @@ Enhanced CNN with parametric static features (7D input: RGBD + UV + sin encoding
 **Validation Only** (skip training):
 ```bash
 # Use latest checkpoint
-./scripts/train_cnn_v2_full.sh --validate
+./cnn_v2/scripts/train_cnn_v2_full.sh --validate
 
 # Use specific checkpoint
-./scripts/train_cnn_v2_full.sh --validate checkpoints/checkpoint_epoch_50.pth
+./cnn_v2/scripts/train_cnn_v2_full.sh --validate checkpoints/checkpoint_epoch_50.pth
 ```
 
 **Manual Training:**
 ```bash
 # Default config
-./training/train_cnn_v2.py \
+./cnn_v2/training/train_cnn_v2.py \
   --input training/input/ --target training/target_2/ \
   --epochs 100 --batch-size 16 --checkpoint-every 5
 
 # Custom architecture (per-layer kernel sizes)
-./training/train_cnn_v2.py \
+./cnn_v2/training/train_cnn_v2.py \
   --input training/input/ --target training/target_2/ \
   --kernel-sizes 1,3,5 \
   --epochs 5000 --batch-size 16
 
 # Mip-level for p0-p3 features (0=original, 1=half, 2=quarter, 3=eighth)
-./training/train_cnn_v2.py \
+./cnn_v2/training/train_cnn_v2.py \
   --input training/input/ --target training/target_2/ \
   --mip-level 1 \
   --epochs 100 --batch-size 16
 
 # Grayscale loss (compute loss on luminance Y = 0.299*R + 0.587*G + 0.114*B)
-./training/train_cnn_v2.py \
+./cnn_v2/training/train_cnn_v2.py \
   --input training/input/ --target training/target_2/ \
   --grayscale-loss \
   --epochs 100 --batch-size 16
@@ -236,7 +236,7 @@ Use `--quiet` for streamlined output in scripts (used automatically by train_cnn
 
 ```
 
-**Validation:** Use HTML tool (`tools/cnn_v2_test/index.html`) for CNN v2 validation. See `doc/CNN_V2_WEB_TOOL.md`.
+**Validation:** Use HTML tool (`cnn_v2/tools/cnn_v2_test/index.html`) for CNN v2 validation. See `cnn_v2/docs/CNN_V2_WEB_TOOL.md`.
 
 ---