zsychn / disco-diffusion-wrapper

Implementation of disco-diffusion-wrapper that could run on your own GPU with batch text input.

disco-diffusion-wrapper

My implementation of disco diffusion wrapper that could run your own GPU with a batch of input text.

What this repo did

1.Separate the model loading and model inference parts of the initial code. Now you can use it like:

# init and load pretrain model.
disco = DiscoDiffusion()
# infer
disco.draw(text, ...)

2.Use deepL to preprocess the text, so that you can use any language you like to draw. The default language pair is from Chinese->English(ZH->EN-US)，you can change it in run.py or run_batch.py

def translate(text, source_lang="ZH", target_lang="EN-US"):
    res = translator.translate_text(text, source_lang="ZH", target_lang="EN-US")
    return res

3.Batch generating & saving. As the loading part and the inferring part is seperated, you do not need to load pretrain model again for a new sentence. This reduces a bunch of time.

cd disco-diffusion-wrapper/wrapper
# create and fill the sentence.list
python run_batch.py

The output images is saved by the name of the origin text, so you can easily find it even after a deepL.

Usage

git clone [e-mail]:mazzzystar/disco-diffusion-wrapper.git
cd disco-diffusion-wrapper

# download pretrain model
python wrapper/utils.py

cd wrapper

# generated image by one sentence
python run.py "一行白鹭上青天"

# batch generation
touch sentence.list
# fill your text in, one by a line.
python batch_run.py

Samples

Below are some samples generated using this repo.

半亩方塘一鉴开，天光云影共徘徊，水墨画

雪山，平原，幽鬼军队在夜里打着荧光绿色的火把前行，抽象画，Trending on artstation

躺在废墟中的玻璃鲸鱼，抽象画

明月松间照，清泉石上流，**画

Elf Castle

山随平野尽，江入大荒流，Trending on artstation

You can download all our Chinese poem generating results from here.

If you use this project and produced some interesting results, submissions are welcomed.

Problems

As it's for fun, I did not look much into the details, and deleted many features(such as VR/3D/Video ...) to make me faster and more clear on the project resonctruction. It's awesome if you're interested in restoring the original function, PR is wellcomed.