CNN v2 training: Expose all parameters as CLI options

Expose all hardcoded parameters in train_cnn_v2_full.sh:
- Training: epochs, batch-size, checkpoint-every, kernel-sizes, num-layers, mip-level
- Patches: patch-size, patches-per-image, detector, full-image, image-size
- Directories: input, target, checkpoint-dir, validation-dir

Update --help with organized sections (modes, training, patches, directories).
Update doc/HOWTO.md with usage examples.

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

1 files changed, 17 insertions, 5 deletions

diff --git a/doc/HOWTO.md b/doc/HOWTO.md
index f89d375..2290aa8 100644
--- a/doc/HOWTO.md
+++ b/doc/HOWTO.md
@@ -136,18 +136,30 @@ Enhanced CNN with parametric static features (7D input: RGBD + UV + sin encoding
 
 **Complete Pipeline** (recommended):
 ```bash
-# Train → Export → Build → Validate
+# Train → Export → Build → Validate (default config)
 ./scripts/train_cnn_v2_full.sh
 
-# With custom mip level for p0-p3 features
-./scripts/train_cnn_v2_full.sh --mip-level 1
+# Custom training parameters
+./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
+
+# Custom directories
+./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
+
+# See all options
+./scripts/train_cnn_v2_full.sh --help
 ```
 
-Config: 100 epochs, 3×3 kernels, 8→4→4 channels, patch-based (harris detector).
+**Defaults:** 200 epochs, 3×3 kernels, 8→4→4 channels, batch-size 16, patch-based (8×8, harris detector).
 - Live progress with single-line update
 - Validates all input images on final epoch
 - Exports binary weights (storage buffer architecture)
-- Mip level: 0 (default, original resolution)
+- All parameters configurable via command-line
 
 **Validation Only** (skip training):
 ```bash