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| from diffusers import StableDiffusionImg2ImgPipeline, DDIMScheduler | |
| from PIL import Image | |
| import gradio as gr | |
| import torch | |
| stable_model_list = [ | |
| "runwayml/stable-diffusion-v1-5", | |
| "stabilityai/stable-diffusion-2", | |
| "stabilityai/stable-diffusion-2-base", | |
| "stabilityai/stable-diffusion-2-1", | |
| "stabilityai/stable-diffusion-2-1-base" | |
| ] | |
| 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_img2img( | |
| model_path:str, | |
| image_path:str, | |
| prompt:str, | |
| negative_prompt:str, | |
| guidance_scale:int, | |
| num_inference_step:int, | |
| ): | |
| image = Image.open(image_path) | |
| pipe = StableDiffusionImg2ImgPipeline.from_pretrained( | |
| model_path, | |
| safety_checker=None, | |
| 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, | |
| negative_prompt = negative_prompt, | |
| num_inference_steps = num_inference_step, | |
| guidance_scale = guidance_scale, | |
| ).images | |
| return output[0] | |
| def stable_diffusion_img2img_app(): | |
| with gr.Tab('Image2Image'): | |
| image2image2_image_file = gr.Image( | |
| type='filepath', | |
| label='Image' | |
| ) | |
| image2image_model_path = gr.Dropdown( | |
| choices=stable_model_list, | |
| value=stable_model_list[0], | |
| label='Image-Image Model Id' | |
| ) | |
| image2image_prompt = gr.Textbox( | |
| lines=1, | |
| value=stable_prompt_list[0], | |
| label='Prompt' | |
| ) | |
| image2image_negative_prompt = gr.Textbox( | |
| lines=1, | |
| value=stable_negative_prompt_list[0], | |
| label='Negative Prompt' | |
| ) | |
| with gr.Accordion("Advanced Options", open=False): | |
| image2image_guidance_scale = gr.Slider( | |
| minimum=0.1, | |
| maximum=15, | |
| step=0.1, | |
| value=7.5, | |
| label='Guidance Scale' | |
| ) | |
| image2image_num_inference_step = gr.Slider( | |
| minimum=1, | |
| maximum=100, | |
| step=1, | |
| value=50, | |
| label='Num Inference Step' | |
| ) | |
| image2image_predict = gr.Button(value='Generator') | |
| variables = { | |
| 'image_path': image2image2_image_file, | |
| 'model_path': image2image_model_path, | |
| 'prompt': image2image_prompt, | |
| 'negative_prompt': image2image_negative_prompt, | |
| 'guidance_scale': image2image_guidance_scale, | |
| 'num_inference_step': image2image_num_inference_step, | |
| 'predict': image2image_predict | |
| } | |
| return variables |