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from diffsynth import ModelManager, SDImagePipeline, download_models |
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import torch |
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download_models(["AingDiffusion_v12", "IP-Adapter-SD", "TextualInversion_VeryBadImageNegative_v1.3"]) |
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model_manager = ModelManager(torch_dtype=torch.float16, device="cuda") |
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model_manager.load_models([ |
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"models/stable_diffusion/aingdiffusion_v12.safetensors", |
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"models/IpAdapter/stable_diffusion/image_encoder/model.safetensors", |
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"models/IpAdapter/stable_diffusion/ip-adapter_sd15.bin" |
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]) |
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pipe = SDImagePipeline.from_model_manager(model_manager) |
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pipe.prompter.load_textual_inversions(["models/textual_inversion/verybadimagenegative_v1.3.pt"]) |
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torch.manual_seed(1) |
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style_image = pipe( |
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prompt="masterpiece, best quality, a car", |
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negative_prompt="verybadimagenegative_v1.3", |
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cfg_scale=7, clip_skip=2, |
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height=512, width=512, num_inference_steps=50, |
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) |
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style_image.save("car.jpg") |
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image = pipe( |
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prompt="masterpiece, best quality, a car running on the road", |
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negative_prompt="verybadimagenegative_v1.3", |
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cfg_scale=7, clip_skip=2, |
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height=512, width=512, num_inference_steps=50, |
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ipadapter_images=[style_image], ipadapter_scale=1.0 |
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) |
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image.save("car_on_the_road.jpg") |
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