---
library_name: diffusers
license: openrail++
datasets:
- ShinoharaHare/Danbooru-2024-Filtered-1M
language:
- en
base_model:
- ShinoharaHare/Waifu-Inpaint-XL
pipeline_tag: image-to-image
tags:
- anime
- art
- colorize
- colorizing
- stable-diffusion
- stable-diffusion-xl
---


# Waifu-Colorize-XL

![image/png](https://cdn-uploads.huggingface.co/production/uploads/630ed69a31970d1cd4fd575d/zcTHuxbQKODbjI9lG9-tq.png)

**Waifu-Colorize-XL** is an SDXL-based model specifically designed for colorizing anime-themed images.

|    Task    |                                                               Model                                                               |
|:----------:|:---------------------------------------------------------------------------------------------------------------------------------:|
| Generation | [WAI-NSFW-illustrious-SDXL-V14.0-V-Prediction](https://huggingface.co/ShinoharaHare/WAI-NSFW-illustrious-SDXL-V14.0-V-Prediction) |
| Inpainting |                             [Waifu-Inpaint-XL](https://huggingface.co/ShinoharaHare/Waifu-Inpaint-XL)                             |
| Colorizing |                            [Waifu-Colorize-XL](https://huggingface.co/ShinoharaHare/Waifu-Colorize-XL)                            |

## Overview

**Waifu-Colorize-XL** is further trained from [Waifu-Inpaint-XL](https://huggingface.co/ShinoharaHare/Waifu-Inpaint-XL ), enabling it to colorize grayscale or binarized images.

## Model Details

- **Developed by:** ShinoharaHare
- **Model type:** Diffusion based image-to-image generative model for colorizing
- **Language(s) (NLP):** English
- **License:** [CreativeML Open RAIL++-M](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md)
- **Finetuned from:** [Waifu-Inpaint-XL](https://huggingface.co/ShinoharaHare/Waifu-Inpaint-XL)

## 🧨 Diffusers

<style>
  .image-viewer {
    position: relative;
    width: 100%;
    margin: 0 auto;
    display: flex;
    flex-flow: wrap;
    align-items: center;
    justify-content: center;
  }
  
  .image-viewer input[type="radio"] {
    display: none;
  }
  
 .image-viewer label {
    width: 120px;
    border-radius: 12px;
    margin: 8px;
    padding: 20px;
    cursor: pointer;
    text-align: center;
    border: 2px solid transparent;
  }

  .image-viewer label:hover {
    border: 2px solid var(--color-blue-400);
  }

  .image-viewer input[type="radio"]:checked + label {
    background-color: var(--color-blue-400);
    color: white;
  }

  .image-container {
    position: relative;
    width: 100%;
    height: 50vh;
  }

  .inner-container {
    position: absolute;
    width: 100%;
    height: 100%;
    display: flex;
    align-items: center;
    justify-content: center;
  }

  .inner-container img {
    border-radius: 10px;
    max-height: 100%;
    max-width: 100%;
    height: 0;
    width: 0;
    opacity: 0;
    margin: 0;
    transition: opacity 0.5s ease, height 0.25s ease, width 0.25s ease;
  }

  #image1:checked ~ .image-container img:nth-child(1),
  #image2:checked ~ .image-container img:nth-child(2) {
    height: auto;
    width: auto;
    opacity: 1.0;
  }
</style>

<div class="image-viewer">
  <input type="radio" id="image1" name="image-switcher" checked>
  <label for="image1" id="image1l">Grayscale</label>
  <input type="radio" id="image2" name="image-switcher">
  <label for="image2" id="image2l">Colorized</label>
  <div class="image-container">
    <div class="inner-container">
      <img src="https://cdn-uploads.huggingface.co/production/uploads/630ed69a31970d1cd4fd575d/ZusF3zcH-auhPgSxY0LKs.png" alt="image1" />
      <img src="https://cdn-uploads.huggingface.co/production/uploads/630ed69a31970d1cd4fd575d/MZsrL3ShppDLLuwHZZpVi.png" alt="image2" />
    </div>
  </div>
</div>

```python
import torch
from diffusers import StableDiffusionXLInpaintPipeline
from diffusers.utils import load_image

pipeline = StableDiffusionXLInpaintPipeline.from_pretrained(
  'ShinoharaHare/Waifu-Colorize-XL',
  custom_pipeline='ShinoharaHare/Waifu-Colorize-XL',
  torch_dtype=torch.half
)
pipeline.to('cuda')

grayscale_image = load_image('https://cdn-uploads.huggingface.co/production/uploads/630ed69a31970d1cd4fd575d/ZusF3zcH-auhPgSxY0LKs.png')
prompt = '' # Write you own prompt if you want.

colorized_image = pipeline(
  prompt=prompt,
  image=grayscale_image,
  num_inference_steps=28,
  guidance_scale=5.0 if prompt else 0.0,
  height=grayscale_image.height,
  width=grayscale_image.width
).images[0]

colorized_image.show()
```