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Diffstat (limited to 'doc/HOWTO.md')
| -rw-r--r-- | doc/HOWTO.md | 44 |
1 files changed, 22 insertions, 22 deletions
diff --git a/doc/HOWTO.md b/doc/HOWTO.md index 0dc9ec7..4cafaa2 100644 --- a/doc/HOWTO.md +++ b/doc/HOWTO.md @@ -100,7 +100,7 @@ make run_util_tests # Utility tests Extracts patches at salient points, trains on center pixels only (matches WGSL sliding window): ```bash # Train with 32×32 patches at detected corners/edges -./training/train_cnn.py \ +./cnn_v1/training/train_cnn.py \ --input training/input/ --target training/output/ \ --patch-size 32 --patches-per-image 64 --detector harris \ --layers 3 --kernel_sizes 3,5,3 --epochs 5000 --batch_size 16 \ @@ -117,7 +117,7 @@ Extracts patches at salient points, trains on center pixels only (matches WGSL s ### Full-Image Processes entire image with sliding window (matches WGSL): ```bash -./training/train_cnn.py \ +./cnn_v1/training/train_cnn.py \ --input training/input/ --target training/output/ \ --layers 3 --kernel_sizes 3,5,3 --epochs 10000 --batch_size 8 \ --checkpoint-every 1000 @@ -126,10 +126,10 @@ Processes entire image with sliding window (matches WGSL): ### Export & Validation ```bash # Generate shaders from checkpoint -./training/train_cnn.py --export-only checkpoints/checkpoint_epoch_5000.pth +./cnn_v1/training/train_cnn.py --export-only checkpoints/checkpoint_epoch_5000.pth # Generate ground truth (sliding window, no tiling) -./training/train_cnn.py --infer input.png \ +./cnn_v1/training/train_cnn.py --infer input.png \ --export-only checkpoints/checkpoint_epoch_5000.pth \ --output ground_truth.png ``` @@ -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`. --- @@ -323,11 +323,11 @@ See `doc/ASSET_SYSTEM.md` and `doc/WORKSPACE_SYSTEM.md`. **Status:** - **CNN v2:** ✅ Fully functional, matches CNNv2Effect -- **CNN v1:** ⚠️ Produces incorrect output, use CNNEffect in demo for validation +- **CNN v1:** ⚠️ Produces incorrect output, use CNNv1Effect in demo for validation **Note:** `--weights` loads layer count and kernel sizes from the binary file, overriding `--layers` and forcing CNN v2. -See `doc/CNN_TEST_TOOL.md` for full documentation. +See `cnn_v1/docs/CNN_TEST_TOOL.md` for full documentation. --- |