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# Stable Diffusion 3 Inpaint Pipeline
| input image | input mask image | output |
|:-------------------------:|:-------------------------:|:-------------------------:|
|<img src="./overture-creations-5sI6fQgYIuo.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_mask.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_output.jpg" width = "400" /> |
|<img src="./overture-creations-5sI6fQgYIuo.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_mask.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_tiger.jpg" width = "400" /> |
|<img src="./overture-creations-5sI6fQgYIuo.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_mask.png" width = "400" /> | <img src="./overture-creations-5sI6fQgYIuo_panda.jpg" width = "400" /> |
**Please ensure that the version of diffusers >= 0.29.1**
# Demo
```python
import torch
from torchvision import transforms
from pipeline_stable_diffusion_3_inpaint import StableDiffusion3InpaintPipeline
from diffusers.utils import load_image
def preprocess_image(image):
image = image.convert("RGB")
image = transforms.CenterCrop((image.size[1] // 64 * 64, image.size[0] // 64 * 64))(image)
image = transforms.ToTensor()(image)
image = image * 2 - 1
image = image.unsqueeze(0).to("cuda")
return image
def preprocess_mask(mask):
mask = mask.convert("L")
mask = transforms.CenterCrop((mask.size[1] // 64 * 64, mask.size[0] // 64 * 64))(mask)
mask = transforms.ToTensor()(mask)
mask = mask.to("cuda")
return mask
pipe = StableDiffusion3InpaintPipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium-diffusers",
torch_dtype=torch.float16,
).to("cuda")
prompt = "Face of a yellow cat, high resolution, sitting on a park bench"
source_image = load_image(
"./overture-creations-5sI6fQgYIuo.png"
)
source = preprocess_image(source_image)
mask = preprocess_mask(
load_image(
"./overture-creations-5sI6fQgYIuo_mask.png"
)
)
image = pipe(
prompt=prompt,
image=source,
mask_image=1-mask,
height=1024,
width=1024,
num_inference_steps=28,
guidance_scale=7.0,
strength=0.6,
).images[0]
image.save("output.png")
```
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