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modified: ppdiffusers/examples/controlnet/README.md modified: ppdiffusers/examples/controlnet/gradio_ip2p2image.py modified: ppdiffusers/examples/controlnet/gradio_mlsd2image.py
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ppdiffusers/examples/controlnet/README.md

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```
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![image](https://user-images.githubusercontent.com/31800336/236171830-f9254b66-9fbd-46d3-a3bc-e905c87d0ec3.jpg)
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## Pix2Pix to Image
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(ControlNet V1.1) InstructPix2Pix根据指令修改图像
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```
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python gradio_ip2p2image.py
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```
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![image](https://github.com/Submerge-Gu/Images/raw/main/4.png)
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## MLSD to Image
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(ControlNet V1.1) 在原基础上进行升级,采用HoughLine检测图片作为控制条件
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```
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python gradio_mlsd2image.py
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```
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![image](https://github.com/Submerge-Gu/Images/raw/main/8.png)
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# ControlNet模型训练
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## Fill50K 训练例子
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# 参考资料
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- https://github.com/lllyasviel/ControlNet/edit/main/docs/train.md
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- https://github.com/huggingface/diffusers
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[https://github.com/Submerge-Gu/Images/blob/main/8.png]: https://github.com/Submerge-Gu/Images/raw/main/8.png

ppdiffusers/examples/controlnet/gradio_ip2p2image.py

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from paddlenlp.trainer import set_seed as seed_everything
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from ppdiffusers import ControlNetModel, StableDiffusionControlNetPipeline
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controlnet = ControlNetModel.from_pretrained("F:/Paddle/model/control_v11e_sd15_ip2p")
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controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11e_sd15_ip2p")
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None
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)

ppdiffusers/examples/controlnet/gradio_mlsd2image.py

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apply_mlsd = MLSDdetector()
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controlnet = ControlNetModel.from_pretrained("F:/Paddle/model/control_v11p_sd15_mlsd")
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controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11p_sd15_mlsd")
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None
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)

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