Spaces:
Runtime error
Runtime error
File size: 2,322 Bytes
370d4c1 b854139 370d4c1 4e83b84 923adf8 370d4c1 65034b6 370d4c1 65034b6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
from transformers.tools.base import Tool, get_default_device
from transformers.utils import is_accelerate_available
import torch
from diffusers import StableDiffusionInpaintPipeline
INPAINTING_DESCRIPTION = (
"This is a tool that inpaints some parts of an image StableDiffusionInpaintPipeline according to a prompt."
" It takes three inputs: `image`, which should be the original image which will be inpainted,"
" `mask_image`, which should be used to determine which parts of the original image"
" (stored in the `image` variable) should be inpainted,"
" and `prompt`, which should be the prompt to use to guide the inpainting process. It returns the"
" inpainted image."
)
class InpaintingTool(Tool):
default_checkpoint = "stabilityai/stable-diffusion-2-inpainting"
description = INPAINTING_DESCRIPTION
name = "image_inpainter"
inputs = ['image', 'image', 'text']
outputs = ['image']
def __init__(self, device=None, **hub_kwargs) -> None:
if not is_accelerate_available():
raise ImportError("Accelerate should be installed in order to use tools.")
super().__init__()
self.device = device
self.pipeline = None
self.hub_kwargs = hub_kwargs
def setup(self):
if self.device is None:
self.device = get_default_device()
self.pipeline = StableDiffusionInpaintPipeline.from_pretrained(self.default_checkpoint)
self.pipeline.to(self.device)
if self.device.type == "cuda":
self.pipeline.to(torch_dtype=torch.float16)
self.is_initialized = True
def __call__(self, image, mask_image, prompt):
if not self.is_initialized:
self.setup()
resized_image = image.resize((512, 512))
mask_image = mask_image.resize((512, 512))
# negative_prompt = "low quality, bad quality, deformed, low resolution"
# added_prompt = " , highest quality, highly realistic, very high resolution"
inpainted_image = self.pipeline(
# prompt=prompt + added_prompt,
# negative_prompt=negative_prompt,
prompt=prompt,
image=resized_image,
mask_image=mask_image
).images[0]
return inpainted_image.resize((image.size[0], image.size[1])) |