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| from diffusers import StableDiffusionControlNetPipeline, ControlNetModel | |
| from diffusers import UniPCMultistepScheduler | |
| import gradio as gr | |
| import torch | |
| from gradio.components import Markdown | |
| # Models | |
| controlnet_pose = ControlNetModel.from_pretrained( | |
| "lllyasviel/sd-controlnet-openpose", torch_dtype=torch.float16 | |
| ) | |
| controlnet_canny = ControlNetModel.from_pretrained( | |
| "lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16 | |
| ) | |
| pipe = StableDiffusionControlNetPipeline.from_pretrained( | |
| "dreamlike-art/dreamlike-anime-1.0", | |
| controlnet=[controlnet_pose, controlnet_canny], | |
| safety_checker=None, torch_dtype=torch.float16 | |
| ).to('cuda') | |
| pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config) | |
| # This command loads the individual model components on GPU on-demand. So, we don't | |
| # need to explicitly call pipe.to("cuda"). | |
| #pipe.enable_model_cpu_offload() | |
| # xformers | |
| pipe.enable_xformers_memory_efficient_attention() | |
| # Generator seed, | |
| generator = torch.manual_seed(1) | |
| negative_prompt = ("worst quality, low quality, lowres, bad anatomy, bad hands, " | |
| "missing fingers, extra digit, fewer digits") | |
| markdown = """ | |
| ## Generate controlled outputs with Mult-ControlNet and Stable Diffusion using 🤗Diffusers | |
| This Space uses pose lines and canny edged image as the additional conditioning. Please refer to the "Examples" for what kind of images are appropriate. | |
| The Followings are tools available to create such images. In this example, tool 1 is being used. | |
| 1. [Character bones that look like Openpose for blender Ver4.7 Depth+Canny](https://toyxyz.gumroad.com/l/ciojz) | |
| 2. [open-pose-editor](https://github.com/ZhUyU1997/open-pose-editor) | |
| """ | |
| # **This space using these models**: | |
| # - ControlNet Model (canny): [lllyasviel/sd-controlnet-canny](https://hf.co/lllyasviel/sd-controlnet-canny) | |
| # - ControlNet Model (openpose): [lllyasviel/sd-controlnet-openpose](https://hf.co/lllyasviel/sd-controlnet-openpose) | |
| # - SD Base Model: [dreamlike-art/dreamlike-anime-1.0](https://hf.co/dreamlike-art/dreamlike-anime-1.0) | |
| def generate_images(pose_image, canny_image, prompt): | |
| output = pipe( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| image=[pose_image, canny_image], | |
| generator=generator, | |
| num_images_per_prompt=2, | |
| num_inference_steps=20, | |
| ) | |
| all_outputs = [] | |
| all_outputs.append(pose_image) | |
| all_outputs.append(canny_image) | |
| for image in output.images: | |
| all_outputs.append(image) | |
| return all_outputs | |
| gr.Interface( | |
| generate_images, | |
| inputs=[ | |
| gr.Image(type="pil"), | |
| gr.Image(type="pil"), | |
| gr.Textbox( | |
| label="Enter your prompt", | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| ), | |
| ], | |
| outputs=gr.Gallery().style(grid=[2], height="auto"), | |
| description=markdown, | |
| examples=[ | |
| ["p11_clip.png", | |
| "c11_clip.png", | |
| "masterpiece, a professional portrait of woman wearing white shirts, smile, heart hand sign" | |
| ], | |
| # ["p13_clip.png", | |
| # "c13_clip.png", | |
| # "masterpiece, a professional portrait of woman wearing white shirts, smile" | |
| # ], | |
| ["p12_clip.png", | |
| "c12_clip.png", | |
| "masterpiece, a professional portrait of woman wearing white shirts, smile" | |
| ], | |
| ], | |
| allow_flagging=False, | |
| ).launch(enable_queue=True) | |