mirror of
https://github.com/huggingface/diffusers.git
synced 2025-12-11 23:14:37 +08:00
57 lines
2.9 KiB
Plaintext
57 lines
2.9 KiB
Plaintext
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
|
|
the License. You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
|
|
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
|
specific language governing permissions and limitations under the License.
|
|
-->
|
|
|
|
# Text-Guided Image-Inpainting
|
|
|
|
The [`StableDiffusionInpaintPipeline`] lets you edit specific parts of an image by providing a mask and a text prompt. It uses a version of Stable Diffusion specifically trained for in-painting tasks.
|
|
|
|
```python
|
|
import PIL
|
|
import requests
|
|
import torch
|
|
from io import BytesIO
|
|
|
|
from diffusers import StableDiffusionInpaintPipeline
|
|
|
|
|
|
def download_image(url):
|
|
response = requests.get(url)
|
|
return PIL.Image.open(BytesIO(response.content)).convert("RGB")
|
|
|
|
|
|
img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
|
|
mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
|
|
|
|
init_image = download_image(img_url).resize((512, 512))
|
|
mask_image = download_image(mask_url).resize((512, 512))
|
|
|
|
pipe = StableDiffusionInpaintPipeline.from_pretrained(
|
|
"runwayml/stable-diffusion-inpainting",
|
|
torch_dtype=torch.float16,
|
|
)
|
|
pipe = pipe.to("cuda")
|
|
|
|
prompt = "Face of a yellow cat, high resolution, sitting on a park bench"
|
|
image = pipe(prompt=prompt, image=init_image, mask_image=mask_image).images[0]
|
|
```
|
|
|
|
`image` | `mask_image` | `prompt` | **Output** |
|
|
:-------------------------:|:-------------------------:|:-------------------------:|-------------------------:|
|
|
<img src="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png" alt="drawing" width="250"/> | <img src="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png" alt="drawing" width="250"/> | ***Face of a yellow cat, high resolution, sitting on a park bench*** | <img src="https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/test.png" alt="drawing" width="250"/> |
|
|
|
|
|
|
You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb)
|
|
|
|
<Tip warning={true}>
|
|
A previous experimental implementation of in-painting used a different, lower-quality process. To ensure backwards compatibility, loading a pretrained pipeline that doesn't contain the new model will still apply the old in-painting method.
|
|
</Tip>
|