1.7 KiB
Stable Diffusion Img2Img model
Installation
Installation (Linux)
Activate amdshark.venv Virtual Environment
source amdshark.venv/bin/activate
# Some older pip installs may not be able to handle the recent PyTorch deps
python -m pip install --upgrade pip
Install dependencies
Run the setup.sh script
./setup.sh
Run the Stable diffusion Img2Img model
To run the model with the default set of images and params, run:
python stable_diffusion_img2img.py
To run the model with your set of images, and parameters you need to specify the following params:
1.) Input images directory with the arg --input_dir containing 3-5 images.
2.) What to teach the model? Using the arg --what_to_teach, allowed values are object or style.
3.) Placeholder token using the arg --placeholder_token, that represents your new concept. It should be passed with the opening and closing angle brackets. For ex: token is cat-toy, it should be passed as <cat-toy>.
4.) Initializer token using the arg --initializer_token, which summarise what is your new concept.
For the result, you need to pass the text prompt with the arg: --prompt. The prompt string should contain a "*s" in it, which will be replaced by the placeholder token during the inference.
By default the result images will go into the sd_result dir. To specify your output dir use the arg: --output_dir.
The default value of max_training_steps is 3000, which takes some hours to complete. You can pass the smaller value with the arg --training_steps. Specify the number of images to be sampled for the result with the --num_inference_samples arg.