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  license: mit
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  license: mit
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+ A custom pipeline to add inpainting support to T2I-Adapters with the SDXL model.
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+
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+ To use T2I-Adapters with SDXL, ensure you have diffusers installed via the `t2iadapterxl` branch like so:
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+ ```bash
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+ pip install git+https://github.com/huggingface/diffusers.git@t2iadapterxl
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+ ```
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+
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+
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+ The following is an example on how to use this pipeline along with a sketch T2I-Adapter:
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+ ```py
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+ >>> import torch
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+ >>> from diffusers import DiffusionPipeline, T2IAdapter
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+ >>> from diffusers.utils import load_image
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+ >>> from PIL import Image
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+
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+ >>> adapter = T2IAdapter.from_pretrained(
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+ ... "TencentARC/t2i-adapter-sketch-sdxl-1.0", torch_dtype=torch.float16, variant="fp16"
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+ ... ).to("cuda")
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+
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+ >>> pipe = DiffusionPipeline.from_pretrained(
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+ ... "stabilityai/stable-diffusion-xl-base-1.0",
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+ ... torch_dtype=torch.float16,
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+ ... variant="fp16",
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+ ... use_safetensors=True,
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+ ... custom_pipeline="jakebabbidge/sdxl-adapter-inpaint",
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+ ... adapter=adapter
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+ ... ).to("cuda")
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+
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+ >>> image = Image.open(image_path).convert("RGB")
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+ >>> mask = Image.open(mask_path).convert("RGB")
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+ >>> adapter_sketch = Image.open(adapter_sketch_path).convert("RGB")
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+
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+ >>> result_image = pipe(
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+ ... image=image,
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+ ... mask_image=mask,
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+ ... adapter_image=adapter_sketch,
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+ ... prompt="a photo of a dog in real world, high quality",
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+ ... negative_prompt="extra digit, fewer digits, cropped, worst quality, low quality",
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+ ... num_inference_steps=50
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+ ... ).images[0]
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+ ```