From 7a0d9970c9b283b957f8b8df0b940813afb28ec2 Mon Sep 17 00:00:00 2001 From: skal Date: Fri, 13 Feb 2026 16:41:35 +0100 Subject: CNN v2: Add --mip-level option for parametric features Add mip level control for p0-p3 features (0=original, 1=half, 2=quarter, 3=eighth). Uses pyrDown/pyrUp for proper Gaussian filtering during mip generation. Changes: - compute_static_features(): Accept mip_level param, generate mip via cv2 pyramid - PatchDataset/ImagePairDataset: Pass mip_level to feature computation - CLI: Add --mip-level arg with choices [0,1,2,3] - Save mip_level in checkpoint config for tracking - Doc updates: HOWTO.md and CNN_V2.md Co-Authored-By: Claude Sonnet 4.5 --- doc/HOWTO.md | 6 ++++++ 1 file changed, 6 insertions(+) (limited to 'doc/HOWTO.md') diff --git a/doc/HOWTO.md b/doc/HOWTO.md index 9c67106..9003fe1 100644 --- a/doc/HOWTO.md +++ b/doc/HOWTO.md @@ -166,6 +166,12 @@ Config: 100 epochs, 3×3 kernels, 8→4→4 channels, patch-based (harris detect --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 \ + --input training/input/ --target training/target_2/ \ + --mip-level 1 \ + --epochs 100 --batch-size 16 ``` **Export Binary Weights:** -- cgit v1.2.3