74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
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import torch
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from huggingface_hub import hf_hub_download
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from inpaint.const import ANYTEXT_NAME
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from inpaint.model.anytext.anytext_pipeline import AnyTextPipeline
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from inpaint.model.base import DiffusionInpaintModel
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from inpaint.model.utils import get_torch_dtype, is_local_files_only
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from inpaint.schema import InpaintRequest
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class AnyText(DiffusionInpaintModel):
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name = ANYTEXT_NAME
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pad_mod = 64
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is_erase_model = False
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@staticmethod
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def download(local_files_only=False):
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hf_hub_download(
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repo_id=ANYTEXT_NAME,
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filename="model_index.json",
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local_files_only=local_files_only,
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)
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ckpt_path = hf_hub_download(
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repo_id=ANYTEXT_NAME,
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filename="pytorch_model.fp16.safetensors",
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local_files_only=local_files_only,
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)
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font_path = hf_hub_download(
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repo_id=ANYTEXT_NAME,
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filename="SourceHanSansSC-Medium.otf",
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local_files_only=local_files_only,
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)
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return ckpt_path, font_path
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def init_model(self, device, **kwargs):
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local_files_only = is_local_files_only(**kwargs)
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ckpt_path, font_path = self.download(local_files_only)
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use_gpu, torch_dtype = get_torch_dtype(device, kwargs.get("no_half", False))
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self.model = AnyTextPipeline(
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ckpt_path=ckpt_path,
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font_path=font_path,
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device=device,
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use_fp16=torch_dtype == torch.float16,
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)
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self.callback = kwargs.pop("callback", None)
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def forward(self, image, mask, config: InpaintRequest):
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"""Input image and output image have same size
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image: [H, W, C] RGB
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mask: [H, W, 1] 255 means area to inpainting
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return: BGR IMAGE
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"""
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height, width = image.shape[:2]
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mask = mask.astype("float32") / 255.0
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masked_image = image * (1 - mask)
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# list of rgb ndarray
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results, rtn_code, rtn_warning = self.model(
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image=image,
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masked_image=masked_image,
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prompt=config.prompt,
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negative_prompt=config.negative_prompt,
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num_inference_steps=config.sd_steps,
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strength=config.sd_strength,
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guidance_scale=config.sd_guidance_scale,
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height=height,
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width=width,
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seed=config.sd_seed,
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sort_priority="y",
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callback=self.callback
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)
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inpainted_rgb_image = results[0][..., ::-1]
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return inpainted_rgb_image
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