demo.git/cnn_v3/training/input, branch main

add more samples + tool html

2026-03-24T22:14:57Z

feat(cnn_v3): gen_sample tool + 7 simple training samples

2026-03-22T06:51:28Z

- pack_photo_sample.py: --target now required (no albedo fallback) - gen_sample.py: bash wrapper with positional args (input target output_dir) - input/photo7.jpg: copy of photo2 (second style target) - target_1: photo2_1_out→photo2_out, photo2_2_out→photo7_out - dataset/simple/sample_001..007: 7 packed photo/target pairs handoff(Gemini): training data ready; next step is train_cnn_v3.py run

feat(cnn_v3): gen_sample tool + 7 simple training samples

2026-03-22T06:33:28Z

- pack_photo_sample.py: --target now required (no albedo fallback) - gen_sample: bash wrapper with positional args (input target output_dir) - input/photo7.jpg: copy of photo2 (second style target) - target_1: photo2_1_out→photo2_out, photo2_2_out→photo7_out - dataset/simple/sample_001..007: 7 packed photo/target pairs handoff(Gemini): training data ready; next step is train_cnn_v3.py run

add training photos

2026-03-05T08:37:52Z

remove old files, add new training set

2026-02-27T22:59:49Z

feat(cnn): add CNN v3 directory structure with training data

2026-02-15T18:12:58Z

Initialize CNN v3 subdirectory with training pipeline layout: - docs/, scripts/, shaders/, src/, tools/, weights/ for organization - training/input/ with sample images - training/target_1/, target_2/ for multi-style training - README.md documenting structure Training images tracked in repo for easy collaboration. Co-Authored-By: Claude Sonnet 4.5