archive(cnn): move CNN v1 to cnn_v1/ subdirectory

Consolidate CNN v1 (CNNEffect) into dedicated directory:
- C++ effect: src/effects → cnn_v1/src/
- Shaders: workspaces/main/shaders/cnn → cnn_v1/shaders/
- Training: training/train_cnn.py → cnn_v1/training/
- Docs: doc/CNN*.md → cnn_v1/docs/

Updated all references:
- CMake source list
- C++ includes (relative paths: ../../cnn_v1/src/)
- Asset paths (../../cnn_v1/shaders/)
- Documentation cross-references

CNN v1 remains active in timeline. For new work, use CNN v2 with
enhanced features (7D static, storage buffer, sigmoid activation).

Tests: 34/34 passing (100%)

18 files changed, 64 insertions, 0 deletions

diff --git a/cnn_v1/README.md b/cnn_v1/README.md
new file mode 100644
index 0000000..ad9b8f3
--- /dev/null
+++ b/cnn_v1/README.md
@@ -0,0 +1,64 @@
+# CNN v1: Original Post-Processing Neural Network
+
+**Architecture:** 3-layer convolution, generated shader weights
+**Status:** Active (used in timeline), legacy architecture
+
+## Overview
+
+Original CNN implementation with per-layer WGSL shaders. Supports multiple kernel sizes (1×1, 3×3, 5×5, 7×7) with generated weight arrays.
+
+**For new work, use CNN v2** (`cnn_v2/`) which provides:
+- Storage buffer architecture (~3.2 KB vs generated WGSL)
+- 7D static features (RGBD + UV + sin + bias)
+- Sigmoid activation with stable training
+- Dynamic layer configuration
+
+## Quick Reference
+
+**Training:**
+```bash
+./cnn_v1/training/train_cnn.py --input training/input --target training/output \
+  --layers 3 --kernel_sizes 3,5,3 --epochs 5000
+```
+
+**Integration:**
+- **C++:** `cnn_v1/src/cnn_effect.{h,cc}`
+- **Assets:** `workspaces/main/assets.txt` (lines 40-46)
+- **Timeline:** `workspaces/main/timeline.seq` (CNNEffect)
+
+## Documentation
+
+- [CNN.md](docs/CNN.md) - Architecture overview
+- [CNN_EFFECT.md](docs/CNN_EFFECT.md) - Implementation details
+- [CNN_TEST_TOOL.md](docs/CNN_TEST_TOOL.md) - Testing guide
+- [CNN_DEBUG.md](docs/CNN_DEBUG.md) - Debugging notes
+
+## Directory Structure
+
+```
+cnn_v1/
+├── README.md              # This file
+├── src/
+│   ├── cnn_effect.h       # Effect header
+│   └── cnn_effect.cc      # Effect implementation
+├── shaders/               # WGSL shaders (7 files)
+├── training/              # Python training script
+└── docs/                  # Documentation (7 markdown files)
+```
+
+## Differences from CNN v2
+
+| Feature | CNN v1 | CNN v2 |
+|---------|--------|--------|
+| Architecture | Generated WGSL weights | Storage buffer weights |
+| Input Features | 4D (RGBA/prev layer) | 12D (4D + 8D static) |
+| Activation | ReLU | Sigmoid + ReLU |
+| Size | ~Variable (WGSL gen) | ~3.2 KB (binary) |
+| Training | Full-image | Patch-based (default) |
+| Layer Config | Compile-time | Runtime (dynamic) |
+
+## Migration Notes
+
+CNN v1 remains in the timeline for historical validation. For new effects or experiments, use CNN v2's enhanced feature set and compact binary format.
+
+See `cnn_v2/docs/CNN_V2.md` for CNN v2 architecture details.
diff --git a/doc/CNN.md b/cnn_v1/docs/CNN.md
index 2dc3362..2dc3362 100644
--- a/doc/CNN.md
+++ b/cnn_v1/docs/CNN.md
diff --git a/doc/CNN_BIAS_FIX_2026-02.md b/cnn_v1/docs/CNN_BIAS_FIX_2026-02.md
index 26db8eb..26db8eb 100644
--- a/doc/CNN_BIAS_FIX_2026-02.md
+++ b/cnn_v1/docs/CNN_BIAS_FIX_2026-02.md
diff --git a/doc/CNN_DEBUG.md b/cnn_v1/docs/CNN_DEBUG.md
index ba220a0..ba220a0 100644
--- a/doc/CNN_DEBUG.md
+++ b/cnn_v1/docs/CNN_DEBUG.md
diff --git a/doc/CNN_EFFECT.md b/cnn_v1/docs/CNN_EFFECT.md
index 40f095e..40f095e 100644
--- a/doc/CNN_EFFECT.md
+++ b/cnn_v1/docs/CNN_EFFECT.md
diff --git a/doc/CNN_FLATTEN_ANALYSIS.md b/cnn_v1/docs/CNN_FLATTEN_ANALYSIS.md
index bf63c5d..bf63c5d 100644
--- a/doc/CNN_FLATTEN_ANALYSIS.md
+++ b/cnn_v1/docs/CNN_FLATTEN_ANALYSIS.md
diff --git a/doc/CNN_RGBD_GRAYSCALE_SUMMARY.md b/cnn_v1/docs/CNN_RGBD_GRAYSCALE_SUMMARY.md
index 3439f2c..3439f2c 100644
--- a/doc/CNN_RGBD_GRAYSCALE_SUMMARY.md
+++ b/cnn_v1/docs/CNN_RGBD_GRAYSCALE_SUMMARY.md
diff --git a/doc/CNN_TEST_TOOL.md b/cnn_v1/docs/CNN_TEST_TOOL.md
index 4307894..4307894 100644
--- a/doc/CNN_TEST_TOOL.md
+++ b/cnn_v1/docs/CNN_TEST_TOOL.md
diff --git a/workspaces/main/shaders/cnn/cnn_activation.wgsl b/cnn_v1/shaders/cnn_activation.wgsl
index 4fe771e..4fe771e 100644
--- a/workspaces/main/shaders/cnn/cnn_activation.wgsl
+++ b/cnn_v1/shaders/cnn_activation.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_conv1x1.wgsl b/cnn_v1/shaders/cnn_conv1x1.wgsl
index f77cfa8..f77cfa8 100644
--- a/workspaces/main/shaders/cnn/cnn_conv1x1.wgsl
+++ b/cnn_v1/shaders/cnn_conv1x1.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl b/cnn_v1/shaders/cnn_conv3x3.wgsl
index f7d11b1..f7d11b1 100644
--- a/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl
+++ b/cnn_v1/shaders/cnn_conv3x3.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_conv5x5.wgsl b/cnn_v1/shaders/cnn_conv5x5.wgsl
index 9328d75..9328d75 100644
--- a/workspaces/main/shaders/cnn/cnn_conv5x5.wgsl
+++ b/cnn_v1/shaders/cnn_conv5x5.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_conv7x7.wgsl b/cnn_v1/shaders/cnn_conv7x7.wgsl
index e68d644..e68d644 100644
--- a/workspaces/main/shaders/cnn/cnn_conv7x7.wgsl
+++ b/cnn_v1/shaders/cnn_conv7x7.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_layer.wgsl b/cnn_v1/shaders/cnn_layer.wgsl
index cbd1686..cbd1686 100644
--- a/workspaces/main/shaders/cnn/cnn_layer.wgsl
+++ b/cnn_v1/shaders/cnn_layer.wgsl
diff --git a/workspaces/main/shaders/cnn/cnn_weights_generated.wgsl b/cnn_v1/shaders/cnn_weights_generated.wgsl
index 510f86f..510f86f 100644
--- a/workspaces/main/shaders/cnn/cnn_weights_generated.wgsl
+++ b/cnn_v1/shaders/cnn_weights_generated.wgsl
diff --git a/src/effects/cnn_effect.cc b/cnn_v1/src/cnn_effect.cc
index 49c5239..49c5239 100644
--- a/src/effects/cnn_effect.cc
+++ b/cnn_v1/src/cnn_effect.cc
diff --git a/src/effects/cnn_effect.h b/cnn_v1/src/cnn_effect.h
index cdcd656..cdcd656 100644
--- a/src/effects/cnn_effect.h
+++ b/cnn_v1/src/cnn_effect.h
diff --git a/training/train_cnn.py b/cnn_v1/training/train_cnn.py
index 4171dcb..4171dcb 100755
--- a/training/train_cnn.py
+++ b/cnn_v1/training/train_cnn.py