From 161a59fa50bb92e3664c389fa03b95aefe349b3f Mon Sep 17 00:00:00 2001 From: skal Date: Sun, 15 Feb 2026 18:44:17 +0100 Subject: 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 --- doc/HOWTO.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) (limited to 'doc/HOWTO.md') 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`. --- -- cgit v1.2.3