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| from diffusers import StableDiffusionXLPipeline, DDIMScheduler | |
| import torch | |
| import gradio as gr | |
| import inversion | |
| import numpy as np | |
| from PIL import Image | |
| import sa_handler | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False) | |
| pipeline = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, scheduler=scheduler).to(device) | |
| def run(image, src_style, src_prompt, prompts, shared_score_shift, shared_score_scale, guidance_scale, num_inference_steps, seed, large=True): | |
| prompts = prompts.splitlines() | |
| dim, d = (1024, 128) if large else (512, 64) | |
| image = image.resize((dim, dim)) | |
| x0 = np.array(image) | |
| zts = inversion.ddim_inversion(pipeline, x0, src_prompt, num_inference_steps, 2) | |
| offset = min(5, len(zts) - 1) | |
| prompts.insert(0, src_prompt) | |
| shared_score_shift = np.log(shared_score_shift) | |
| handler = sa_handler.Handler(pipeline) | |
| sa_args = sa_handler.StyleAlignedArgs( | |
| share_group_norm=True, share_layer_norm=True, share_attention=True, | |
| adain_queries=True, adain_keys=True, adain_values=False, | |
| shared_score_shift=shared_score_shift, shared_score_scale=shared_score_scale,) | |
| handler.register(sa_args) | |
| for i in range(1, len(prompts)): | |
| prompts[i] = f'{prompts[i]}, {src_style}.' | |
| zT, inversion_callback = inversion.make_inversion_callback(zts, offset=offset) | |
| g_cpu = torch.Generator(device='cpu') | |
| if seed > 0: | |
| g_cpu.manual_seed(seed) | |
| latents = torch.randn(len(prompts), 4, d, d, device='cpu', generator=g_cpu, dtype=pipeline.unet.dtype,).to(device) | |
| latents[0] = zT | |
| images_a = pipeline(prompts, latents=latents, callback_on_step_end=inversion_callback, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale).images | |
| handler.remove() | |
| torch.cuda.empty_cache() | |
| return images_a | |
| with gr.Blocks() as demo: | |
| gr.Markdown("""# Welcome to🌟Tonic's🤵🏻Style📐Align | |
| Here you can generate images with a style from a reference image using [transfer style from sdxl](https://huggingface.co/docs/diffusers/main/en/using-diffusers/sdxl). Add a reference picture, describe the style and add prompts to generate images in that style. It's the most interesting with your own art! You can also use [stabilityai/stable-diffusion-xl-base-1.0] by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/TonicsStyleAlign?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> | |
| Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/nXx5wbX9) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha) | |
| """) | |
| with gr.Row(): | |
| image_input = gr.Image(label="Reference image", type="pil") | |
| with gr.Row(): | |
| style_input = gr.Textbox(label="Describe the reference style") | |
| image_desc_input = gr.Textbox(label="Describe the reference image") | |
| prompts_input = gr.Textbox(label="Prompts to generate images (separate with new lines)", lines=5) | |
| with gr.Accordion(label="Advanced Settings"): | |
| with gr.Row(): | |
| shared_score_shift_input = gr.Slider(value=1.5, label="shared_score_shift", minimum=1.0, maximum=2.0, step=0.05) | |
| shared_score_scale_input = gr.Slider(value=0.5, label="shared_score_scale", minimum=0.0, maximum=1.0, step=0.05) | |
| guidance_scale_input = gr.Slider(value=10.0, label="guidance_scale", minimum=5.0, maximum=20.0, step=1) | |
| num_inference_steps_input = gr.Slider(value=12, label="num_inference_steps", minimum=12, maximum=300, step=1) | |
| seed_input = gr.Slider(value=0, label="seed", minimum=0, maximum=1000000, step=42) | |
| with gr.Row(): | |
| run_button = gr.Button("Generate Images") | |
| with gr.Row(): | |
| output_gallery = gr.Gallery() | |
| run_button.click( | |
| run, | |
| inputs=[image_input, style_input, image_desc_input, prompts_input, shared_score_shift_input, shared_score_scale_input, guidance_scale_input, num_inference_steps_input, seed_input], | |
| outputs=output_gallery | |
| ) | |
| examples = [ | |
| ["./download%20(8).jpg", "picasso blue period", "a portrait of a man playing guitar", | |
| "an astronaut holding a cocktail glass\nan astronaut in space holding a laptop\nan astronaut in space with an explosion of iridescent powder", | |
| 1.7, 0.7, 20, 144, False, 245112] | |
| ] | |
| examples_component = gr.Examples( | |
| examples=examples, | |
| inputs=[image_input, style_input, image_desc_input, prompts_input, shared_score_shift_input, shared_score_scale_input, guidance_scale_input, num_inference_steps_input, seed_input, large_input], # Corrected the variable names and order | |
| outputs=output_gallery, | |
| fn=run, | |
| cache_examples=True | |
| ) | |
| demo.add_component(examples_component) | |
| demo.launch() |