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| import random | |
| import gradio as gr | |
| from datasets import load_dataset | |
| from PIL import Image | |
| from set import ExpiringMap | |
| # from model import get_sd_small, get_sd_tiny, get_sd_every | |
| from trans_google import google_translator | |
| import replicate | |
| from i18n import i18nTranslator | |
| word_list_dataset = load_dataset("Gustavosta/Stable-Diffusion-Prompts") | |
| word_list = word_list_dataset["train"]['Prompt'] | |
| # | |
| # from diffusers import EulerDiscreteScheduler, DDIMScheduler, KDPM2AncestralDiscreteScheduler, \ | |
| # UniPCMultistepScheduler, DPMSolverSinglestepScheduler, DEISMultistepScheduler, PNDMScheduler, \ | |
| # DPMSolverMultistepScheduler, HeunDiscreteScheduler, EulerAncestralDiscreteScheduler, DDPMScheduler, \ | |
| # LMSDiscreteScheduler, KDPM2DiscreteScheduler | |
| # import torch | |
| # import base64 | |
| # from io import BytesIO | |
| is_gpu_busy = False | |
| # translator = i18nTranslator() | |
| # translator.init(path='locales') | |
| samplers = [ | |
| "EulerDiscrete", | |
| "EulerAncestralDiscrete", | |
| "UniPCMultistep", | |
| "DPMSolverSinglestep", | |
| "DPMSolverMultistep", | |
| "KDPM2Discrete", | |
| "KDPM2AncestralDiscrete", | |
| "DEISMultistep", | |
| "HeunDiscrete", | |
| "PNDM", | |
| "DDPM", | |
| "DDIM", | |
| "LMSDiscrete", | |
| ] | |
| re_sampler = [ | |
| "DDIM", | |
| "K_EULER", | |
| "DPMSolverMultistep", | |
| "K_EULER_ANCESTRAL", | |
| "PNDM", | |
| "KLMS" | |
| ] | |
| rand = random.Random() | |
| translator = google_translator() | |
| # tiny_pipe = get_sd_tiny() | |
| # small_pipe = get_sd_small() | |
| # every_pipe = get_sd_every() | |
| # def get_pipe(width: int, height: int): | |
| # if width == 512 and height == 512: | |
| # return tiny_pipe | |
| # elif width == 256 and height == 256: | |
| # return small_pipe | |
| # else: | |
| # return every_pipe | |
| time_client_map = ExpiringMap() | |
| count_client_map = ExpiringMap() | |
| def infer(prompt: str, negative: str, width: int, height: int, sampler: str, | |
| steps: int, seed: int, scale, request: gr.Request): | |
| client_ip = request.client.host | |
| if client_ip != '127.0.0.1' and client_ip != 'localhost' and client_ip != '0.0.0.0': | |
| if time_client_map.get(client_ip): | |
| return None, "Too many requests, please try again later." | |
| else: | |
| time_client_map.put(client_ip, 1, 10) # 添加一个过期时间为 10 秒的项 | |
| count = count_client_map.get(client_ip) | |
| if count is None: | |
| count = 0 | |
| count += 1 | |
| if count > 5: | |
| return None, "Too many requests, please try again later more." | |
| else: | |
| count_client_map.put(client_ip, count, 24 * 60 * 60) # 添加一个过期时间为 24 小时的项 | |
| global is_gpu_busy | |
| if seed == 0: | |
| seed = rand.randint(0, 10000) | |
| else: | |
| seed = int(seed) | |
| # | |
| # pipeline = get_pipe(width, height) | |
| # | |
| images = [] | |
| # if torch.cuda.is_available(): | |
| # generator = torch.Generator(device="cuda").manual_seed(seed) | |
| # else: | |
| # generator = None | |
| # if sampler == "EulerDiscrete": | |
| # pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "EulerAncestralDiscrete": | |
| # pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "KDPM2Discrete": | |
| # pipeline.scheduler = KDPM2DiscreteScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "KDPM2AncestralDiscrete": | |
| # pipeline.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "UniPCMultistep": | |
| # pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "DPMSolverSinglestep": | |
| # pipeline.scheduler = DPMSolverSinglestepScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "DPMSolverMultistep": | |
| # pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "HeunDiscrete": | |
| # pipeline.scheduler = HeunDiscreteScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "DEISMultistep": | |
| # pipeline.scheduler = DEISMultistepScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "PNDM": | |
| # pipeline.scheduler = PNDMScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "DDPM": | |
| # pipeline.scheduler = DDPMScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "DDIM": | |
| # pipeline.scheduler = DDIMScheduler.from_config(pipeline.scheduler.config) | |
| # elif sampler == "LMSDiscrete": | |
| # pipeline.scheduler = LMSDiscreteScheduler.from_config(pipeline.scheduler.config) | |
| try: | |
| translate_prompt = translator.translate(prompt, lang_tgt='en') | |
| translate_negative = translator.translate(negative, lang_tgt='en') | |
| except Exception as ex: | |
| print(ex) | |
| translate_prompt = prompt | |
| translate_negative = negative | |
| output = replicate.run( | |
| "stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf", | |
| input={ | |
| "prompt": translate_prompt, | |
| "negative_prompt": translate_negative, | |
| "guidance_scale": scale, | |
| "num_inference_steps": steps, | |
| "seed": seed, | |
| "scheduler": sampler, | |
| } | |
| ) | |
| # image = pipeline(prompt=translate_prompt, | |
| # negative_prompt=translate_negative, | |
| # guidance_scale=scale, | |
| # num_inference_steps=steps, | |
| # generator=generator, | |
| # height=height, | |
| # width=width).images[0] | |
| # buffered = BytesIO() | |
| # image.save(buffered, format="JPEG") | |
| # img_str = base64.b64encode(buffered.getvalue()) | |
| # img_base64 = bytes("data:image/jpeg;base64,", encoding='utf-8') + img_str | |
| images.append(output[0]) | |
| return images, "" | |
| css = """ | |
| .gradio-container { | |
| font-family: 'IBM Plex Sans', sans-serif; | |
| } | |
| .gr-button { | |
| color: white; | |
| border-color: black; | |
| background: black; | |
| } | |
| input[type='range'] { | |
| accent-color: black; | |
| } | |
| .dark input[type='range'] { | |
| accent-color: #dfdfdf; | |
| } | |
| .container { | |
| max-width: 1130px; | |
| margin: auto; | |
| padding-top: 1.5rem; | |
| } | |
| #prompt-column { | |
| min-height: 500px | |
| } | |
| #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-btn { | |
| font-size: .7rem !important; | |
| line-height: 19px; | |
| margin-top: 12px; | |
| margin-bottom: 12px; | |
| padding: 2px 8px; | |
| border-radius: 14px !important; | |
| } | |
| #advanced-options { | |
| display: none; | |
| 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%; | |
| } | |
| .animate-spin { | |
| animation: spin 1s linear infinite; | |
| } | |
| @keyframes spin { | |
| from { | |
| transform: rotate(0deg); | |
| } | |
| to { | |
| transform: rotate(360deg); | |
| } | |
| } | |
| #share-btn-container { | |
| 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; | |
| margin-top: 10px; | |
| margin-left: auto; | |
| } | |
| #share-btn { | |
| 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;right:0; | |
| } | |
| #share-btn * { | |
| all: unset; | |
| } | |
| #share-btn-container div:nth-child(-n+2){ | |
| width: auto !important; | |
| min-height: 0px !important; | |
| } | |
| #share-btn-container .wrap { | |
| display: none !important; | |
| } | |
| .gr-form{ | |
| flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0; | |
| } | |
| #prompt-container{ | |
| gap: 0; | |
| } | |
| #prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem} | |
| #component-16{border-top-width: 1px!important;margin-top: 1em} | |
| .image_duplication{position: absolute; width: 100px; left: 50px} | |
| .generate-container {display: flex; justify-content: flex-end;} | |
| #generate-btn {background: linear-gradient(to bottom right, #ffedd5, #fdba74)} | |
| """ | |
| block = gr.Blocks(css=css) | |
| # text, negative, width, height, sampler, steps, seed, guidance_scale | |
| # examples = [ | |
| # [ | |
| # 'A high tech solarpunk utopia in the Amazon rainforest', | |
| # 'low quality', | |
| # 512, | |
| # 512, | |
| # 'ddim', | |
| # 30, | |
| # 0, | |
| # 9 | |
| # ], | |
| # [ | |
| # 'A pikachu fine dining with a view to the Eiffel Tower', | |
| # 'low quality', | |
| # 512, | |
| # 512, | |
| # 'ddim', | |
| # 30, | |
| # 0, | |
| # 9 | |
| # ], | |
| # [ | |
| # 'A mecha robot in a favela in expressionist style', | |
| # 'low quality, 3d, photorealistic', | |
| # 512, | |
| # 512, | |
| # 'ddim', | |
| # 30, | |
| # 0, | |
| # 9 | |
| # ], | |
| # [ | |
| # 'an insect robot preparing a delicious meal', | |
| # 'low quality, illustration', | |
| # 512, | |
| # 512, | |
| # 'ddim', | |
| # 30, | |
| # 0, | |
| # 9 | |
| # ], | |
| # [ | |
| # "A small cabin on top of a snowy mountain in the style of Disney, artstation", | |
| # 'low quality, ugly', | |
| # 512, | |
| # 512, | |
| # 'ddim', | |
| # 30, | |
| # 0, | |
| # 9 | |
| # ], | |
| # ] | |
| examples = list(map(lambda x: [ | |
| x, | |
| 'low quality', | |
| 512, | |
| 512, | |
| 'DPMSolverMultistep', | |
| 30, | |
| 0, | |
| 9 | |
| ], word_list))[:500] | |
| with block: | |
| title = "Stable Diffusion 2.1 Demo" | |
| desc = """ small stable diffusion Demo App. <br /> | |
| Click <strong>Generate image</strong> Button to generate image. <br /> | |
| Also Change params to have a try <br /> | |
| more size may cost more time. <br /> | |
| It's just a simplified demo, you can use more advanced features optimize image quality <br />""" | |
| tutorial_link = "https://docs.cworld.ai/docs/cworld-ai/quick-start-stable-diffusion" | |
| gr.HTML( | |
| f""" | |
| <div style="text-align: center; margin: 0 auto;"> | |
| <a href="https://cworld.ai"> | |
| <svg style="margin: 0 auto;" width="155" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 407 100"> | |
| <g id="SvgjsG2746" | |
| transform="matrix(0.8454106280193237,0,0,0.8454106280193237,-4.2270531400966185,-4.2270531400966185)" | |
| fill="#111"> | |
| <g xmlns="http://www.w3.org/2000/svg"> | |
| <g> | |
| <g> | |
| <path d="M50,11c21.5,0,39,17.5,39,39S71.5,89,50,89S11,71.5,11,50S28.5,11,50,11 M50,5C25.1,5,5,25.1,5,50s20.1,45,45,45 s45-20.1,45-45S74.9,5,50,5L50,5z"></path> | |
| </g> | |
| </g> | |
| <path d="M55,75H45v-5c0-2.8,2.2-5,5-5h0c2.8,0,5,2.2,5,5V75z"></path> | |
| <rect x="25" y="35" width="10" height="20"></rect> | |
| <rect x="65" y="35" width="10" height="20"></rect> | |
| </g> | |
| </g> | |
| <g id="SvgjsG2747" | |
| transform="matrix(3.3650250410766605,0,0,3.3650250410766605,93.98098208712985,-3.546415304677616)" | |
| fill="#111"> | |
| <path | |
| d="M8.1 17.42 l1.42 1.28 c-0.94 1.04 -2.28 1.5 -3.78 1.5 c-2.84 0 -5.14 -2.18 -5.14 -5.12 s2.3 -5.14 5.14 -5.14 c1.5 0 2.84 0.46 3.78 1.5 l-1.42 1.28 c-0.58 -0.78 -1.42 -1.08 -2.36 -1.08 c-1.7 0 -3.08 1.42 -3.08 3.44 c0 2 1.38 3.44 3.08 3.44 c0.94 0 1.78 -0.3 2.36 -1.1 z M23.42 10.12 l2.06 0 l-3.76 9.88 l-1.26 0 l-2.46 -6.4 l-2.44 6.4 l-1.26 0 l-3.78 -9.88 l2.08 0 l2.34 6.9 l2.06 -6.08 l0.26 -0.82 l1.48 0 l0.28 0.82 l2.06 6.08 z M31.62 11.64 c-1.7 0 -3.08 1.42 -3.08 3.44 c0 2 1.38 3.44 3.08 3.44 s3.08 -1.44 3.08 -3.44 c0 -2.02 -1.38 -3.44 -3.08 -3.44 z M31.62 9.94 c2.84 0 5.14 2.2 5.14 5.14 s-2.3 5.12 -5.14 5.12 s-5.14 -2.18 -5.14 -5.12 s2.3 -5.14 5.14 -5.14 z M44.9 10.24 l-0.44 1.62 c-0.14 -0.08 -0.58 -0.22 -0.94 -0.22 c-1.7 0 -2.5 1.62 -2.5 3.62 l0 4.74 l-2.06 0 l0 -9.88 l2.06 0 l0 1.4 c0.24 -0.92 1.3 -1.58 2.48 -1.58 c0.54 0 1.12 0.14 1.4 0.3 z M48.379999999999995 4.619999999999999 l0 15.38 l-2.08 0 l0 -15.38 l2.08 0 z M50.98 15.08 c0 -2.94 2.1 -5.14 4.94 -5.14 c0.98 0 2.18 0.42 2.84 0.96 l0 -5.9 l2.08 0 l0 15 l-2.08 0 l0 -0.74 c-0.78 0.58 -1.86 0.94 -2.84 0.94 c-2.84 0 -4.94 -2.18 -4.94 -5.12 z M53.06 15.08 c0 2 1.38 3.44 3.06 3.44 c1.12 0 2.12 -0.52 2.64 -1.58 c0.28 -0.54 0.44 -1.18 0.44 -1.86 s-0.16 -1.32 -0.44 -1.88 c-0.52 -1.06 -1.52 -1.56 -2.64 -1.56 c-1.68 0 -3.06 1.42 -3.06 3.44 z M66.46 18.78 c0 0.8 -0.62 1.42 -1.42 1.42 c-0.78 0 -1.4 -0.62 -1.4 -1.42 c0 -0.76 0.62 -1.38 1.4 -1.38 c0.8 0 1.42 0.62 1.42 1.38 z M73.08 9.92 c2.84 0 3.98 1.72 3.98 3.18 l0 6.9 l-2.06 0 l0 -1.08 c-0.72 0.98 -2 1.26 -2.8 1.26 c-2.26 0 -3.74 -1.32 -3.74 -3.08 c0 -2.46 1.84 -3.34 3.74 -3.34 l2.8 0 l0 -0.66 c0 -0.62 -0.24 -1.48 -1.92 -1.48 c-0.94 0 -1.8 0.5 -2.36 1.28 l-1.42 -1.28 c0.94 -1.04 2.28 -1.7 3.78 -1.7 z M75 16.92 l0 -1.48 l-2.52 0 c-1.22 0 -2.08 0.62 -1.94 1.74 c0.12 0.94 0.88 1.32 1.94 1.32 c1.9 0 2.52 -0.9 2.52 -1.58 z M81.9 10.12 l0 9.88 l-2.06 0 l0 -9.88 l2.06 0 z M82 6.5 c0 0.64 -0.5 1.14 -1.14 1.14 c-0.62 0 -1.12 -0.5 -1.12 -1.14 c0 -0.62 0.5 -1.12 1.12 -1.12 c0.64 0 1.14 0.5 1.14 1.12 z"></path> | |
| </g> | |
| </svg> | |
| </a> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px"> | |
| {title} | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;"> | |
| {desc} | |
| There is the <a href="{tutorial_link}"> tutorial </a> | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): | |
| with gr.Column(elem_id="prompt-column"): | |
| text = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| elem_id="prompt-text-input", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| negative = gr.Textbox( | |
| label="Enter your negative prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter a negative prompt", | |
| elem_id="negative-prompt-text-input", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| with gr.Row(elem_id="txt2img_size", scale=4): | |
| width = gr.Slider(minimum=64, maximum=1024, step=8, label="Width", value=512, | |
| elem_id="txt2img_width") | |
| height = gr.Slider(minimum=64, maximum=1024, step=8, label="Height", value=512, | |
| elem_id="txt2img_height") | |
| with gr.Row(elem_id="txt2img_sampler", scale=4): | |
| seed = gr.Number(value=0, label="Seed", elem_id="txt2img_seed") | |
| sampler = gr.Dropdown( | |
| re_sampler, value="DPMSolverMultistep", | |
| multiselect=False, | |
| label="Sampler", | |
| info="sampler select" | |
| ) | |
| steps = gr.Slider(minimum=1, maximum=50, step=1, elem_id=f"steps", label="Sampling steps", | |
| value=20) | |
| with gr.Accordion("Advanced settings", open=False): | |
| # gr.Markdown("Advanced settings are temporarily unavailable") | |
| # samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1) | |
| # steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1) | |
| guidance_scale = gr.Slider( | |
| label="Guidance Scale", minimum=0, maximum=40, value=9, step=0.1 | |
| ) | |
| with gr.Row(elem_id="generate-container", elem_classes="generate-container").style(height="100"): | |
| btn = gr.Button("Generate image", elem_id="generate-btn", elem_classes="generate-btn").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| full_width=False, | |
| ) | |
| with gr.Column(): | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery" | |
| ).style() | |
| result = gr.Textbox(label="Run Status") | |
| # with gr.Group(elem_id="container-advanced-btns"): | |
| # # advanced_button = gr.Button("Advanced options", elem_id="advanced-btn") | |
| # with gr.Group(elem_id="share-btn-container"): | |
| # community_icon = gr.HTML(community_icon_html) | |
| # loading_icon = gr.HTML(loading_icon_html) | |
| # share_button = gr.Button("Share to community", elem_id="share-btn") | |
| ex = gr.Examples(examples=examples, fn=infer, | |
| inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale], | |
| outputs=[gallery, result], | |
| examples_per_page=5, | |
| cache_examples=False) | |
| ex.dataset.headers = [""] | |
| negative.submit(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale], | |
| outputs=[gallery, result], postprocess=False) | |
| text.submit(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale], | |
| outputs=[gallery, result], postprocess=False) | |
| btn.click(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale], | |
| outputs=[gallery, result], postprocess=False) | |
| block.queue(concurrency_count=5, | |
| max_size=100).launch( | |
| max_threads=150, | |
| # server_port=6006, | |
| # share=True, | |
| ) | |