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| from contextlib import nullcontext | |
| import gradio as gr | |
| import torch | |
| from torch import autocast | |
| from diffusers import SemanticStableDiffusionPipeline | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pipe = SemanticStableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5") | |
| pipe = pipe.to(device) | |
| gen = torch.Generator(device=device) | |
| # Sometimes the nsfw checker is confused by the Pokémon images, you can disable | |
| # it at your own risk here | |
| disable_safety = False | |
| if disable_safety: | |
| def null_safety(images, **kwargs): | |
| return images, False | |
| pipe.safety_checker = null_safety | |
| def infer(prompt, steps, scale, seed, editing_prompt_1 = None, reverse_editing_direction_1 = False, edit_warmup_steps_1=10, edit_guidance_scale_1=5, edit_threshold_1=0.95, | |
| editing_prompt_2 = None, reverse_editing_direction_2 = False, edit_warmup_steps_2=10, edit_guidance_scale_2=5, edit_threshold_2=0.95, | |
| edit_momentum_scale=0.5, edit_mom_beta=0.6): | |
| gen.manual_seed(seed) | |
| images = pipe(prompt, guidance_scale=scale, num_inference_steps=steps, generator=gen).images | |
| editing_prompt = [editing_prompt_1, editing_prompt_2] | |
| reverse_editing_direction = [reverse_editing_direction_1, reverse_editing_direction_2] | |
| edit_warmup_steps = [edit_warmup_steps_1, edit_warmup_steps_2] | |
| edit_guidance_scale = [edit_guidance_scale_1, edit_guidance_scale_2] | |
| edit_threshold = [edit_threshold_1, edit_threshold_2] | |
| indices = [ind for ind, val in enumerate(editing_prompt) if val is None or len(val) <= 1] | |
| for index in sorted(indices, reverse=True): | |
| del editing_prompt[index] | |
| del reverse_editing_direction[index] | |
| del edit_warmup_steps[index] | |
| del edit_guidance_scale[index] | |
| del edit_threshold[index] | |
| gen.manual_seed(seed) | |
| images.extend(pipe(prompt, guidance_scale=scale, num_inference_steps=steps, generator=gen, | |
| editing_prompt=editing_prompt, reverse_editing_direction=reverse_editing_direction, edit_warmup_steps=edit_warmup_steps, edit_guidance_scale=edit_guidance_scale, | |
| edit_momentum_scale=edit_momentum_scale, edit_mom_beta=edit_mom_beta | |
| ).images) | |
| return images | |
| css = """ | |
| a { | |
| color: inherit; | |
| text-decoration: underline; | |
| } | |
| .gradio-container { | |
| font-family: 'IBM Plex Sans', sans-serif; | |
| } | |
| .gr-button { | |
| color: white; | |
| border-color: #9d66e5; | |
| background: #9d66e5; | |
| } | |
| input[type='range'] { | |
| accent-color: #9d66e5; | |
| } | |
| .dark input[type='range'] { | |
| accent-color: #dfdfdf; | |
| } | |
| .container { | |
| max-width: 730px; | |
| margin: auto; | |
| padding-top: 1.5rem; | |
| } | |
| #gallery { | |
| min-height: 22rem; | |
| margin-bottom: 15px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| border-bottom-right-radius: .5rem !important; | |
| border-bottom-left-radius: .5rem !important; | |
| } | |
| #gallery>div>.h-full { | |
| min-height: 20rem; | |
| } | |
| .details:hover { | |
| text-decoration: underline; | |
| } | |
| .gr-button { | |
| white-space: nowrap; | |
| } | |
| .gr-button:focus { | |
| border-color: rgb(147 197 253 / var(--tw-border-opacity)); | |
| outline: none; | |
| box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); | |
| --tw-border-opacity: 1; | |
| --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); | |
| --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); | |
| --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); | |
| --tw-ring-opacity: .5; | |
| } | |
| #advanced-options { | |
| margin-bottom: 20px; | |
| } | |
| .footer { | |
| margin-bottom: 45px; | |
| margin-top: 35px; | |
| text-align: center; | |
| border-bottom: 1px solid #e5e5e5; | |
| } | |
| .footer>p { | |
| font-size: .8rem; | |
| display: inline-block; | |
| padding: 0 10px; | |
| transform: translateY(10px); | |
| background: white; | |
| } | |
| .dark .footer { | |
| border-color: #303030; | |
| } | |
| .dark .footer>p { | |
| background: #0b0f19; | |
| } | |
| .acknowledgments h4{ | |
| margin: 1.25em 0 .25em 0; | |
| font-weight: bold; | |
| font-size: 115%; | |
| } | |
| """ | |
| block = gr.Blocks(css=css) | |
| examples = [ | |
| [ | |
| 'a photo of a cat', | |
| 50, | |
| 7, | |
| 3, | |
| 'sunglasses', | |
| False, | |
| 10, | |
| 6, | |
| 0.95, | |
| '', | |
| False, | |
| 10, | |
| 5, | |
| 0.95 | |
| ], | |
| [ | |
| 'an image of a crowded boulevard, realistic, 4k', | |
| 50, | |
| 7, | |
| 9, | |
| 'crowd, crowded, people', | |
| True, | |
| 10, | |
| 8.3, | |
| 0.9, | |
| '', | |
| False, | |
| 10, | |
| 5, | |
| 0.95 | |
| ], | |
| [ | |
| 'a castle next to a river', | |
| 50, | |
| 7, | |
| 48, | |
| 'boat on a river', | |
| False, | |
| 15, | |
| 6, | |
| 0.9, | |
| 'monet, impression, sunrise', | |
| False, | |
| 18, | |
| 6, | |
| 0.8 | |
| ], | |
| [ | |
| 'a portrait of a king, full body shot, 8k', | |
| 50, | |
| 7, | |
| 33, | |
| 'male', | |
| True, | |
| 5, | |
| 5, | |
| 0.9, | |
| 'female', | |
| False, | |
| 5, | |
| 5, | |
| 0.9 | |
| ], | |
| [ | |
| 'a photo of a flowerpot', | |
| 50, | |
| 7, | |
| 2, | |
| 'glasses', | |
| False, | |
| 12, | |
| 5, | |
| 0.975, | |
| '', | |
| False, | |
| 10, | |
| 5, | |
| 0.95 | |
| ], | |
| [ | |
| 'a photo of the face of a woman', | |
| 50, | |
| 7, | |
| 21, | |
| 'smiling, smile', | |
| False, | |
| 15, | |
| 3, | |
| 0.99, | |
| 'curls, wavy hair, curly hair', | |
| False, | |
| 13, | |
| 3, | |
| 0.925 | |
| ], | |
| ] | |
| with block: | |
| gr.HTML( | |
| """ | |
| <div style="text-align: center; max-width: 750px; margin: 0 auto;"> | |
| <div> | |
| <img class="logo" src="https://aeiljuispo.cloudimg.io/v7/https://s3.amazonaws.com/moonup/production/uploads/1666181274838-62fa1d95e8c9c532aa75331c.png" alt="AIML Logo" | |
| style="margin: auto; max-width: 7rem;"> | |
| <h1 style="font-weight: 900; font-size: 3rem;"> | |
| Semantic Guidance for Diffusion | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Interact with semantic concepts during the diffusion process. Details can be found in the paper <a href="https://arxiv.org/abs/2301.12247" style="text-decoration: underline;" target="_blank">SEGA: Instructing Diffusion using Semantic Dimensions</a>. <br/> Simply use the edit prompts to make arbitrary changes to the generation. | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| gr.HTML(""" | |
| <p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. | |
| <br/> | |
| <a href="https://huggingface.co/spaces/AIML-TUDA/semantic-diffusion?duplicate=true"> | |
| <img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> | |
| <p/>""") | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| text = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| btn = gr.Button("Generate image").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| ) | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| edit_1 = gr.Textbox( | |
| label="Edit Prompt 1", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your 1st edit prompt", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| with gr.Group(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| rev_1 = gr.Checkbox( | |
| label='Reverse') | |
| warmup_1 = gr.Slider(label='Warmup', minimum=0, maximum=50, value=10, step=1, interactive=True) | |
| scale_1 = gr.Slider(label='Scale', minimum=1, maximum=10, value=5, step=0.25, interactive=True) | |
| threshold_1 = gr.Slider(label='Threshold', minimum=0.5, maximum=0.99, value=0.95, steps=0.01, interactive=True) | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| edit_2 = gr.Textbox( | |
| label="Edit Prompt 2", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your 2nd edit prompt", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| with gr.Group(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| rev_2 = gr.Checkbox( | |
| label='Reverse') | |
| warmup_2 = gr.Slider(label='Warmup', minimum=0, maximum=50, value=10, step=1, interactive=True) | |
| scale_2 = gr.Slider(label='Scale', minimum=1, maximum=10, value=5, step=0.25, interactive=True) | |
| threshold_2 = gr.Slider(label='Threshold', minimum=0.5, maximum=0.99, value=0.95, steps=0.01, interactive=True) | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery" | |
| ).style(grid=[2], height="auto") | |
| with gr.Row(elem_id="advanced-options"): | |
| scale = gr.Slider(label="Scale", minimum=3, maximum=15, value=7, step=1) | |
| steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=50, step=5, interactive=False) | |
| seed = gr.Slider( | |
| label="Seed", | |
| minimum=0, | |
| maximum=2147483647, | |
| step=1, | |
| #randomize=True, | |
| ) | |
| ex = gr.Examples(examples=examples, fn=infer, inputs=[text, steps, scale, seed, edit_1, rev_1, warmup_1, scale_1, threshold_1, edit_2, rev_2, warmup_2, scale_2, threshold_2], outputs=gallery, cache_examples=False) | |
| ex.dataset.headers = [""] | |
| text.submit(infer, inputs=[text, steps, scale, seed, edit_1, rev_1, warmup_1, scale_1, threshold_1, edit_2, rev_2, warmup_2, scale_2, threshold_2], outputs=gallery) | |
| btn.click(infer, inputs=[text, steps, scale, seed, edit_1, rev_1, warmup_1, scale_1, threshold_1, edit_2, rev_2, warmup_2, scale_2, threshold_2], outputs=gallery) | |
| gr.HTML( | |
| """ | |
| <div class="footer"> | |
| <p> Gradio Demo by AIML@TU Darmstadt and 🤗 Hugging Face | |
| </p> | |
| </div> | |
| <div class="acknowledgments"> | |
| <p>Created by <a href="https://www.aiml.informatik.tu-darmstadt.de/people/mbrack/">Manuel Brack</a> and <a href="justinpinkney.com">Patrick Schramowski</a> at <a href="https://www.aiml.informatik.tu-darmstadt.de">AIML Lab</a>.</p> | |
| </div> | |
| """ | |
| ) | |
| block.launch() |