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Training

We provide a framework for training and validation.

The scripts below are just for illustration purposes. To achieve better results, you can modify the corresponding parameters as needed.

Start Training

There are different ways to start a training:

  • calling scepter/tools/run_train.py:
# calling at SCEPTER root:
PYTHONPATH=./ python scepter/tools/run_train.py --cfg [path-to-your-yaml]

# calling scepter library:
pip install scepter
python -m scepter.tools.run_train --cfg [path-to-your-yaml]
  • calling your own script:
# calling at SCEPTER root:
PYTHONPATH=./ python [path-to-your-script] --cfg [path-to-your-yaml]

# calling scepter library:
pip install scepter
python [path-to-your-script] --cfg [path-to-your-yaml]

your scepter should be like:

from scepter.tools.run_train import run

if __name__ == '__main__':
    run()

Popular Tasks

Text-to-Image Generation

  • SCEdit
python scepter/tools/run_train.py --cfg scepter/methods/scedit/t2i/sd15_512_sce_t2i.yaml  # SD v1.5
python scepter/tools/run_train.py --cfg scepter/methods/scedit/t2i/sd21_768_sce_t2i.yaml  # SD v2.1
python scepter/tools/run_train.py --cfg scepter/methods/scedit/t2i/sdxl_1024_sce_t2i.yaml  # SD XL
  • Existing Tuning Strategies
python scepter/tools/run_train.py --cfg scepter/methods/examples/generation/stable_diffusion_1.5_512.yaml  # fully-tuning on SD v1.5
python scepter/tools/run_train.py --cfg scepter/methods/examples/generation/stable_diffusion_2.1_768_lora.yaml  # lora-tuning on SD v2.1
  • Data Text Format
# Download the 3D_example_txt.zip as previously mentioned
python scepter/tools/run_train.py --cfg scepter/methods/scedit/t2i/sdxl_1024_sce_t2i_datatxt.yaml

Controllable Image Synthesis

  • SCEdit

The YAML configuration can be modified to combine different base models and conditions. The following is provided as an example.

python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sd15_512_sce_ctr_hed.yaml  # SD v1.5 + hed
python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml  # SD v2.1 + canny
python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml  # SD v2.1 + pose
python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_depth.yaml  # SD XL + depth
python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_color.yaml  # SD XL + color
  • Data Text Format
# Download the 3D_example_txt.zip as previously mentioned
python scepter/tools/run_train.py --cfg scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_color_datatxt.yaml

Customize Modules

You can register your own Modules like DATASET, SAMPLERS, TRANSFORMS, MODELS, SOVLERS, HOOKS, OPTIMIZERS into SCEPTER. Refer to example/, build the modules of your task in example/{task}.

cd example/classifier
python run.py --cfg classifier.yaml