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import gradio as gr |
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import torch |
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from diffusers import AutoPipelineForInpainting, UNet2DConditionModel |
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import diffusers |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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unet = UNet2DConditionModel.from_pretrained("valhalla/sdxl-inpaint-ema", torch_dtype=torch.float16, revision="d5593e75323fa2a5285ebe02c1aba504a695bbf7") |
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pipe = AutoPipelineForInpainting.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", unet=unet, torch_dtype=torch.float16, variant="fp16").to("cuda") |
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def read_content(file_path: str) -> str: |
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"""read the content of target file |
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""" |
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with open(file_path, 'r', encoding='utf-8') as f: |
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content = f.read() |
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return content |
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def predict(dict, prompt="", guidance_scale=7.5, steps=20, strength=1.0, scheduler="EulerDiscreteScheduler"): |
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scheduler_class_name = scheduler.split("-")[0] |
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add_kwargs = {} |
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if len(scheduler.split("-")) > 1: |
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add_kwargs["use_karras"] = True |
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if len(scheduler.split("-")) > 2: |
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add_kwargs["algorithm_type"] = "sde-dpmsolver++" |
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scheduler = getattr(diffusers, scheduler_class_name) |
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pipe.scheduler = scheduler.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", subfolder="scheduler", **add_kwargs) |
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init_image = dict["image"].convert("RGB").resize((1024, 1024)) |
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mask = dict["mask"].convert("RGB").resize((1024, 1024)) |
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output = pipe(prompt = prompt, image=init_image, mask_image=mask, guidance_scale=guidance_scale, num_inference_steps=int(steps), strength=strength) |
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return output.images[0], gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) |
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css = ''' |
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.container {max-width: 1150px;margin: auto;padding-top: 1.5rem} |
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#image_upload{min-height:400px} |
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#image_upload [data-testid="image"], #image_upload [data-testid="image"] > div{min-height: 400px} |
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#mask_radio .gr-form{background:transparent; border: none} |
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#word_mask{margin-top: .75em !important} |
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#word_mask textarea:disabled{opacity: 0.3} |
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.footer {margin-bottom: 45px;margin-top: 35px;text-align: center;border-bottom: 1px solid #e5e5e5} |
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.footer>p {font-size: .8rem; display: inline-block; padding: 0 10px;transform: translateY(10px);background: white} |
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.dark .footer {border-color: #303030} |
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.dark .footer>p {background: #0b0f19} |
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.acknowledgments h4{margin: 1.25em 0 .25em 0;font-weight: bold;font-size: 115%} |
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#image_upload .touch-none{display: flex} |
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@keyframes spin { |
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from { |
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transform: rotate(0deg); |
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} |
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to { |
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transform: rotate(360deg); |
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} |
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} |
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#share-btn-container { |
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display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; |
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} |
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#share-btn { |
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all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; |
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} |
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#share-btn * { |
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all: unset; |
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} |
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#share-btn-container div:nth-child(-n+2){ |
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width: auto !important; |
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min-height: 0px !important; |
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} |
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#share-btn-container .wrap { |
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display: none !important; |
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} |
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''' |
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image_blocks = gr.Blocks(css=css) |
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with image_blocks as demo: |
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gr.HTML(read_content("header.html")) |
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with gr.Group(): |
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with gr.Box(): |
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with gr.Row(): |
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with gr.Column(): |
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image = gr.Image(source='upload', tool='sketch', elem_id="image_upload", type="pil", label="Upload").style(height=400) |
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with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): |
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prompt = gr.Textbox(placeholder = 'Your prompt (what you want in place of what is erased)', show_label=False, elem_id="input-text") |
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with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): |
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guidance_scale = gr.Number(value=7.5, minimum=1.0, maximum=20.0, step=0.1, label="guidance_scale") |
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steps = gr.Number(value=20, minimum=10, maximum=50, step=0.1, label="steps") |
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strength = gr.Number(value=1.0, minimum=0.0, maximum=1.0, step=0.05, label="strength") |
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with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): |
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schedulers = ["DEISMultistepScheduler", "HeunDiscreteScheduler", "EulerDiscreteScheduler", "DPMSolverMultistepScheduler", "DPMSolverMultistepScheduler-Karras", "DPMSolverMultistepScheduler-Karras-SDE"] |
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scheduler = gr.Dropdown(choices=schedulers, value="EulerDiscreteScheduler") |
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btn = gr.Button("Inpaint!").style( |
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margin=False, |
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rounded=(False, True, True, False), |
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full_width=False, |
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) |
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with gr.Column(): |
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image_out = gr.Image(label="Output", elem_id="output-img").style(height=400) |
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with gr.Group(elem_id="share-btn-container"): |
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community_icon = gr.HTML(community_icon_html, visible=False) |
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loading_icon = gr.HTML(loading_icon_html, visible=False) |
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share_button = gr.Button("Share to community", elem_id="share-btn", visible=False) |
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btn.click(fn=predict, inputs=[image, prompt, guidance_scale, steps, strength, scheduler], outputs=[image_out, community_icon, loading_icon, share_button]) |
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share_button.click(None, [], [], _js=share_js) |
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gr.Examples( |
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examples=[ |
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["./imgs/aaa (8).png"], |
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["./imgs/download (1).jpeg"], |
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["./imgs/0_oE0mLhfhtS_3Nfm2.png"], |
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["./imgs/02_HubertyBlog-1-1024x1024.jpg"], |
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["./imgs/jdn_jacques_de_nuce-1024x1024.jpg"], |
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["./imgs/c4ca473acde04280d44128ad8ee09e8a.jpg"], |
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["./imgs/canam-electric-motorcycles-scaled.jpg"], |
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["./imgs/e8717ce80b394d1b9a610d04a1decd3a.jpeg"], |
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["./imgs/Nature___Mountains_Big_Mountain_018453_31.jpg"], |
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["./imgs/Multible-sharing-room_ccexpress-2-1024x1024.jpeg"], |
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], |
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fn=predict, |
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inputs=[image], |
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cache_examples=False, |
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) |
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gr.HTML( |
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""" |
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<div class="footer"> |
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<p>Model by <a href="https://huggingface.co/diffusers" style="text-decoration: underline;" target="_blank">Diffusers</a> - Gradio Demo by 🤗 Hugging Face |
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</p> |
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</div> |
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""" |
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) |
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image_blocks.launch() |
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