Paint-with-Words, Implemented with Stable diffusion

"realistic photo of a dog, cat, tree, with beautiful sky, on sandy ground"

"A digital painting of a half-frozen lake near mountains under a full moon and aurora. A boat is in the middle of the lake. Highly detailed."

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Very recently, researchers from NVIDIA proposed eDiffi. In the paper, they suggested method that allows "painting with word". Basically, this is like make-a-scene, but with just using adjusted cross-attention score. You can see the results and detailed method in the paper.

Unfortunately, their paper and their method was not open-sourced. Yet, paint-with-words can be implemented with Stable Diffusion since they share common Cross Attention module. So, I implemented it with Stable Diffusion.

Installation

pip install git+https://github.com/cloneofsimo/paint-with-words-sd.git

Basic Usage

Before running, fill in the variable HF_TOKEN in .env file with Huggingface token for Stable Diffusion, and load_dotenv().

Prepare segmentation map, and map-color : tag label such as below. keys are (R, G, B) format, and values are tag label.

{
    (0, 0, 0): "cat,1.0",
    (255, 255, 255): "dog,1.0",
    (13, 255, 0): "tree,1.5",
    (90, 206, 255): "sky,0.2",
    (74, 18, 1): "ground,0.2",
}

You neeed to have them so that they are in format "{label},{strength}", where strength is additional weight of the attention score you will give during generation, i.e., it will have more effect.

import dotenv
from PIL import Image

from paint_with_words import paint_with_words

settings = {
    "color_context": {
        (0, 0, 0): "cat,1.0",
        (255, 255, 255): "dog,1.0",
        (13, 255, 0): "tree,1.5",
        (90, 206, 255): "sky,0.2",
        (74, 18, 1): "ground,0.2",
    },
    "color_map_img_path": "contents/example_input.png",
    "input_prompt": "realistic photo of a dog, cat, tree, with beautiful sky, on sandy ground",
    "output_img_path": "contents/output_cat_dog.png",
}


dotenv.load_dotenv()

color_map_image = Image.open(settings["color_map_img_path"]).convert("RGB")
color_context = settings["color_context"]
input_prompt = settings["input_prompt"]

img = paint_with_words(
    color_context=color_context,
    color_map_image=color_map_image,
    input_prompt=input_prompt,
    num_inference_steps=30,
    guidance_scale=7.5,
    device="cuda:0",
)

img.save(settings["output_img_path"])

There is minimal working example in runner.py that is self contained. Plase have a look!