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| import gradio as gr | |
| import torch | |
| from diffusers import DDIMScheduler, DiffusionPipeline | |
| stable_inpiant_model_list = [ | |
| "stabilityai/stable-diffusion-2-inpainting", | |
| "runwayml/stable-diffusion-inpainting", | |
| ] | |
| stable_prompt_list = ["a photo of a man.", "a photo of a girl."] | |
| stable_negative_prompt_list = ["bad, ugly", "deformed"] | |
| def stable_diffusion_inpaint( | |
| dict: str, | |
| model_path: str, | |
| prompt: str, | |
| negative_prompt: str, | |
| guidance_scale: int, | |
| num_inference_step: int, | |
| ): | |
| image = dict["image"].convert("RGB").resize((512, 512)) | |
| mask_image = dict["mask"].convert("RGB").resize((512, 512)) | |
| pipe = DiffusionPipeline.from_pretrained( | |
| model_path, | |
| revision="fp16", | |
| torch_dtype=torch.float16, | |
| ) | |
| pipe.to("cuda") | |
| pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) | |
| pipe.enable_xformers_memory_efficient_attention() | |
| output = pipe( | |
| prompt=prompt, | |
| image=image, | |
| mask_image=mask_image, | |
| negative_prompt=negative_prompt, | |
| num_inference_steps=num_inference_step, | |
| guidance_scale=guidance_scale, | |
| ).images | |
| return output[0] | |
| def stable_diffusion_inpaint_app(): | |
| with gr.Blocks(): | |
| with gr.Row(): | |
| with gr.Column(): | |
| inpaint_image_file = gr.Image( | |
| source="upload", | |
| tool="sketch", | |
| elem_id="image_upload", | |
| type="pil", | |
| label="Upload", | |
| ) | |
| inpaint_model_id = gr.Dropdown( | |
| choices=stable_inpiant_model_list, | |
| value=stable_inpiant_model_list[0], | |
| label="Inpaint Model Id", | |
| ) | |
| inpaint_prompt = gr.Textbox( | |
| lines=1, value=stable_prompt_list[0], label="Prompt" | |
| ) | |
| inpaint_negative_prompt = gr.Textbox( | |
| lines=1, | |
| value=stable_negative_prompt_list[0], | |
| label="Negative Prompt", | |
| ) | |
| with gr.Accordion("Advanced Options", open=False): | |
| inpaint_guidance_scale = gr.Slider( | |
| minimum=0.1, | |
| maximum=15, | |
| step=0.1, | |
| value=7.5, | |
| label="Guidance Scale", | |
| ) | |
| inpaint_num_inference_step = gr.Slider( | |
| minimum=1, | |
| maximum=100, | |
| step=1, | |
| value=50, | |
| label="Num Inference Step", | |
| ) | |
| inpaint_predict = gr.Button(value="Generator") | |
| with gr.Column(): | |
| output_image = gr.Gallery(label="Outputs") | |
| inpaint_predict.click( | |
| fn=stable_diffusion_inpaint, | |
| inputs=[ | |
| inpaint_image_file, | |
| inpaint_model_id, | |
| inpaint_prompt, | |
| inpaint_negative_prompt, | |
| inpaint_guidance_scale, | |
| inpaint_num_inference_step, | |
| ], | |
| outputs=output_image, | |
| ) | |