Spaces:
Runtime error
Runtime error
import PIL.Image | |
import cv2 | |
import numpy as np | |
import torch | |
from iopaint.const import KANDINSKY22_NAME | |
from .base import DiffusionInpaintModel | |
from iopaint.schema import InpaintRequest | |
from .utils import get_torch_dtype, enable_low_mem, is_local_files_only | |
class Kandinsky(DiffusionInpaintModel): | |
pad_mod = 64 | |
min_size = 512 | |
def init_model(self, device: torch.device, **kwargs): | |
from diffusers import AutoPipelineForInpainting | |
use_gpu, torch_dtype = get_torch_dtype(device, kwargs.get("no_half", False)) | |
model_kwargs = { | |
"torch_dtype": torch_dtype, | |
"local_files_only": is_local_files_only(**kwargs), | |
} | |
self.model = AutoPipelineForInpainting.from_pretrained( | |
self.name, **model_kwargs | |
).to(device) | |
enable_low_mem(self.model, kwargs.get("low_mem", False)) | |
self.callback = kwargs.pop("callback", None) | |
def forward(self, image, mask, config: InpaintRequest): | |
"""Input image and output image have same size | |
image: [H, W, C] RGB | |
mask: [H, W, 1] 255 means area to repaint | |
return: BGR IMAGE | |
""" | |
self.set_scheduler(config) | |
generator = torch.manual_seed(config.sd_seed) | |
mask = mask.astype(np.float32) / 255 | |
img_h, img_w = image.shape[:2] | |
# kandinsky 没有 strength | |
output = self.model( | |
prompt=config.prompt, | |
negative_prompt=config.negative_prompt, | |
image=PIL.Image.fromarray(image), | |
mask_image=mask[:, :, 0], | |
height=img_h, | |
width=img_w, | |
num_inference_steps=config.sd_steps, | |
guidance_scale=config.sd_guidance_scale, | |
output_type="np", | |
callback_on_step_end=self.callback, | |
generator=generator, | |
).images[0] | |
output = (output * 255).round().astype("uint8") | |
output = cv2.cvtColor(output, cv2.COLOR_RGB2BGR) | |
return output | |
class Kandinsky22(Kandinsky): | |
name = KANDINSKY22_NAME | |