models/inpainting.py

import torch
from diffusers import AutoPipelineForInpainting
from torchvision.transforms.functional import to_pil_image
from PIL import Image

class InpaintingModel:
    def __init__(self) -> None:
        pass
    def generate(self, image: torch.Tensor, mask_image: torch.Tensor, prompt: str) -> Image.Image:
        pass

class KandingskyInpaintingModel(InpaintingModel):
    def __init__(
        self,
        device = torch.device("cpu"),
    ) -> None:
        super().__init__()
        self.device = device
        self.model = AutoPipelineForInpainting.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch.float16)
        self.model.enable_model_cpu_offload()
        self.negative_prompt = "deformed, ugly, disfigured"

    def generate(self, image: Image.Image, mask_image: Image.Image, prompt: str) -> Image.Image:
        output = self.model(prompt=prompt, negative_prompt=self.negative_prompt, image=image, mask_image=mask_image)
        return output.images[0]