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22 changes: 19 additions & 3 deletions README.md
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Expand Up @@ -8,8 +8,15 @@ To reduce the VRAM usage, the following opimizations are used:

<h1 align="center">Installation</h1>

Establish a virtual environment and install dependencies as referred to the official [repo](https://github.com/CompVis/stable-diffusion "repo").
The quantized model checkpoint can be downloaded from [Google drive](https://drive.google.com/file/d/1bdsW5Bys70xt3x4DDxNKsbMkRkkKgneJ/view?usp=drive_link)
On Windows:

Establish a virtual environment and install the following dependencies:
- Get the NVIDIA App and download the latest available driver for your hardware [https://www.nvidia.com/de-de/software/nvidia-app/](https://www.nvidia.com/de-de/software/nvidia-app/)
- Get CUDA here [https://developer.nvidia.com/cuda-zone](https://developer.nvidia.com/cuda-zone) and make sure your GPU is supported ([https://en.wikipedia.org/wiki/CUDA#GPUs_supported](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)).
- Get the latest pytorch cuda version via pip ```pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118```
- Install the remaining dependencies as required ```pip install setuptools omegaconf pillow einops pytorch_lightning pandas transformers taming-transformers scipy clip kornia```

The quantized model checkpoint can be downloaded from [Google drive](https://drive.google.com/file/d/1bdsW5Bys70xt3x4DDxNKsbMkRkkKgneJ/view?usp=drive_link). The path to the file can be appended as argument to the command running the txt2img app.

<h1 align="center">Usage</h1>

Expand All @@ -20,10 +27,19 @@ Only txt2img is supported now.

- For example, the following command will generate 10 512x512 images:

`python3 tiny_optimizedSD/tiny_txt2img.py --prompt "A peaceful lakeside cabin with a dock, surrounded by tall pine trees and a clear blue sky" --H 512 --W 512 --seed 27`
`py tiny_optimizedSD/tiny_txt2img.py --prompt "A peaceful lakeside cabin with a dock, surrounded by tall pine trees and a clear blue sky" --H 512 --W 512 --seed 27`

Full example with checkpoint file path specification:

`py tiny_optimizedSD/tiny_txt2img.py --prompt "A peaceful lakeside cabin with a dock, surrounded by tall pine trees and a clear blue sky" --H 512 --W 512 --seed 27 --ckpt "C:\Python\venv\tiny-stable\tiny-stable-diffusion-main\full_int2_sd.pth"`

<h1 align="center">Arguments</h1>

## `--ckpt`

- Specify the file path to the quantized model checkpoint file you downloaded earlier.
- Example `--ckpt "C:\Path\To\full_int2_sd.pth`

## `--seed`

**Seed for image generation**, can be used to reproduce previously generated images. Defaults to a random seed if unspecified.
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