From 3e4fece8fce11b368b4c7bab284242bf18e6a0b1 Mon Sep 17 00:00:00 2001
From: skal <pascal.massimino@gmail.com>
Date: Wed, 25 Mar 2026 08:27:39 +0100
Subject: feat(cnn_v3/training): add --single-sample option + doc fixes
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- train_cnn_v3.py: --single-sample <dir> implies --full-image + --batch-size 1
- cnn_v3_utils.py: CNNv3Dataset accepts single_sample= kwarg (explicit override)
- HOWTO.md: document --single-sample workflow, fix pack_photo_sample.py usage (--target required)
- HOW_TO_CNN.md: fix GBufferEffect seq input (prev_cnn→source), fix binary name (demo→demo64k), add --resume to flag table, remove stale "pack without target" block

handoff(Gemini): --single-sample <dir> added to train_cnn_v3.py; docs audited and corrected
---
 cnn_v3/docs/HOWTO.md | 28 +++++++++++++++++++++++++---
 1 file changed, 25 insertions(+), 3 deletions(-)

(limited to 'cnn_v3/docs/HOWTO.md')

diff --git a/cnn_v3/docs/HOWTO.md b/cnn_v3/docs/HOWTO.md
index 58f09ed..1aead68 100644
--- a/cnn_v3/docs/HOWTO.md
+++ b/cnn_v3/docs/HOWTO.md
@@ -233,12 +233,13 @@ channel-dropout training.
 
 ```bash
 python3 cnn_v3/training/pack_photo_sample.py \
-    --photo cnn_v3/training/input/photo1.jpg \
+    --photo  input/photo1.jpg \
+    --target target/photo1_styled.png \
     --output dataset/photos/sample_001/
 ```
 
-The output `target.png` defaults to the input photo (no style). Copy in
-your stylized version as `target.png` before training.
+`--target` is required and must be a stylized ground-truth image at the same
+resolution as the photo. The script writes it as `target.png` in the sample dir.
 
 ### Dataset layout
 
@@ -285,10 +286,31 @@ python3 train_cnn_v3.py \
     --patch-size 32 --detector random
 ```
 
+### Single-sample training
+
+Use `--single-sample <dir>` to train on one specific sample directory.
+Implies `--full-image` and `--batch-size 1` automatically.
+
+```bash
+# Pack input/target pair into a sample directory first
+python3 pack_photo_sample.py \
+    --photo  input/photo1.png \
+    --target target/photo1_styled.png \
+    --output dataset/simple/sample_001/
+
+# Train on that sample only
+python3 train_cnn_v3.py \
+    --single-sample dataset/simple/sample_001/ \
+    --epochs 500
+```
+
+All other flags (`--epochs`, `--lr`, `--checkpoint-dir`, `--enc-channels`, etc.) work normally.
+
 ### Key flags
 
 | Flag | Default | Notes |
 |------|---------|-------|
+| `--single-sample DIR` | — | Train on one sample dir; implies `--full-image`, `--batch-size 1` |
 | `--input DIR` | `training/dataset` | Root with `full/` or `simple/` subdirs |
 | `--input-mode` | `simple` | `simple`=photos, `full`=Blender G-buffer |
 | `--patch-size N` | `64` | Patch crop size |
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