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