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| from diffusers import AutoencoderKL, UNet2DConditionModel, StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, DPMSolverMultistepScheduler | |
| from diffusers import EulerAncestralDiscreteScheduler | |
| import gradio as gr | |
| import torch | |
| import os | |
| from PIL import Image | |
| import datetime | |
| import time | |
| import psutil | |
| from share_btn import community_icon_html, loading_icon_html, share_js | |
| def is_google_colab(): | |
| try: | |
| import google.colab | |
| return True | |
| except: | |
| return False | |
| is_colab = is_google_colab() | |
| start_time = time.time() | |
| if torch.cuda.is_available(): | |
| torchfloat = torch.float16 | |
| else: | |
| torchfloat = torch.float32 | |
| class Model: | |
| def __init__(self, name, path="", prefix=""): | |
| self.name = name | |
| self.path = path | |
| self.prefix = prefix | |
| self.pipe_t2i = None | |
| self.pipe_i2i = None | |
| models = [ | |
| Model("Cyberpunk Anime Diffusion", "DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style "), | |
| Model("DGSpitzer Art Diffusion", "DGSpitzer/DGSpitzer-Art-Diffusion", "dgspitzer painting,"), | |
| Model("Guan Yu Diffusion", "DGSpitzer/Guan-Yu-Diffusion", "") | |
| ] | |
| custom_model = None | |
| if is_colab: | |
| models.insert(0, Model("Custom model")) | |
| custom_model = models[0] | |
| last_mode = "txt2img" | |
| current_model = models[1] if is_colab else models[0] | |
| current_model_path = current_model.path | |
| if is_colab: | |
| pipe0 = StableDiffusionPipeline.from_pretrained( | |
| current_model.path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler"), | |
| safety_checker=lambda images, clip_input: (images, False) | |
| ) | |
| if torch.cuda.is_available(): | |
| pipe0 = pipe0.to("cuda") | |
| elif torch.cuda.is_available() == False: | |
| pipe0 = StableDiffusionPipeline.from_pretrained( | |
| current_model.path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler") | |
| ) | |
| else: | |
| eulera = EulerAncestralDiscreteScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000) | |
| pipe0 = StableDiffusionPipeline.from_pretrained( | |
| models[0].path, | |
| torch_dtype=torchfloat, | |
| scheduler=eulera | |
| ) | |
| pipe1 = StableDiffusionPipeline.from_pretrained( | |
| models[1].path, | |
| torch_dtype=torchfloat, | |
| scheduler=eulera, | |
| use_auth_token=os.environ.get("HF") | |
| ) | |
| # pipe1 = StableDiffusionPipeline.from_pretrained( | |
| # models[1].path, | |
| # torch_dtype=torchfloat, | |
| # scheduler=eulera | |
| # ) | |
| pipe2 = StableDiffusionPipeline.from_pretrained( | |
| models[2].path, | |
| torch_dtype=torchfloat, | |
| scheduler=eulera | |
| ) | |
| if torch.cuda.is_available(): | |
| pipe0 = pipe0.to("cuda") | |
| pipe1 = pipe1.to("cuda") | |
| pipe2 = pipe2.to("cuda") | |
| #pipe.enable_xformers_memory_efficient_attention() | |
| device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶" | |
| def error_str(error, title="Error"): | |
| return f"""#### {title} | |
| {error}""" if error else "" | |
| def custom_model_changed(path): | |
| models[0].path = path | |
| global current_model | |
| current_model = models[0] | |
| def on_model_change(model_name): | |
| prefix = "Enter prompt. \"" + next((m.prefix for m in models if m.name == model_name), None) + "\" is prefixed automatically" if model_name != models[0].name else "Don't forget to use the custom model prefix in the prompt!" | |
| return gr.update(visible = model_name == models[0].name), gr.update(placeholder=prefix) | |
| def inference(model_name, prompt, neg_prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, n_images=1): | |
| print("Generated image with prompt: " + prompt) | |
| if neg_prompt != "": | |
| print("Negative prompt: " + neg_prompt) | |
| print(psutil.virtual_memory()) # print memory usage | |
| global current_model | |
| for model in models: | |
| if model.name == model_name: | |
| current_model = model | |
| model_path = current_model.path | |
| generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None | |
| try: | |
| if img is not None: | |
| return img_to_img(model_path, prompt, neg_prompt, img, strength, guidance, steps, width, height, n_images, generator), None, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) | |
| else: | |
| return txt_to_img(model_path, prompt, neg_prompt, guidance, steps, width, height, n_images, generator), None, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) | |
| except Exception as e: | |
| return None, error_str(e), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False) | |
| def inference_example(model_name, prompt, neg_prompt, guidance, steps, width=512, height=512): | |
| _image, _error, _bool1, _bool2, _bool3 = inference(model_name, prompt, neg_prompt, guidance, steps, width, height) | |
| return _image | |
| def txt_to_img(model_path, prompt, neg_prompt, guidance, steps, width, height, n_images, generator): | |
| print(f"{datetime.datetime.now()} txt_to_img, model: {current_model.name}") | |
| global last_mode | |
| global pipe0 | |
| global pipe1 | |
| global pipe2 | |
| global current_model_path | |
| if model_path != current_model_path or last_mode != "txt2img": | |
| current_model_path = model_path | |
| if is_colab or current_model == custom_model: | |
| pipe0 = StableDiffusionPipeline.from_pretrained( | |
| current_model_path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler"), | |
| safety_checker=lambda images, clip_input: (images, False) | |
| ) | |
| if torch.cuda.is_available(): | |
| pipe0 = pipe0.to("cuda") | |
| # pipe.enable_xformers_memory_efficient_attention() | |
| elif torch.cuda.is_available() == False: | |
| pipe0 = StableDiffusionPipeline.from_pretrained( | |
| current_model_path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler") | |
| ) | |
| last_mode = "txt2img" | |
| prompt = current_model.prefix + prompt | |
| if current_model == models[0] or is_colab or torch.cuda.is_available() == False: | |
| result = pipe0( | |
| prompt, | |
| negative_prompt = neg_prompt, | |
| num_images_per_prompt=n_images, | |
| num_inference_steps = int(steps), | |
| guidance_scale = guidance, | |
| width = width, | |
| height = height, | |
| generator = generator) | |
| elif current_model == models[1]: | |
| result = pipe1( | |
| prompt, | |
| negative_prompt = neg_prompt, | |
| num_images_per_prompt=n_images, | |
| num_inference_steps = int(steps), | |
| guidance_scale = guidance, | |
| width = width, | |
| height = height, | |
| generator = generator) | |
| elif current_model == models[2]: | |
| result = pipe2( | |
| prompt, | |
| negative_prompt = neg_prompt, | |
| num_images_per_prompt=n_images, | |
| num_inference_steps = int(steps), | |
| guidance_scale = guidance, | |
| width = width, | |
| height = height, | |
| generator = generator) | |
| print("Job done! Filtering nsfw content") | |
| return replace_nsfw_images(result) | |
| def img_to_img(model_path, prompt, neg_prompt, img, strength, guidance, steps, width, height, n_images, generator): | |
| print(f"{datetime.datetime.now()} img_to_img, model: {model_path}") | |
| global last_mode | |
| global pipe0 | |
| global pipe1 | |
| global current_model_path | |
| if model_path != current_model_path or last_mode != "img2img": | |
| current_model_path = model_path | |
| if is_colab or current_model == custom_model: | |
| pipe0 = StableDiffusionImg2ImgPipeline.from_pretrained( | |
| current_model_path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler"), | |
| safety_checker=lambda images, clip_input: (images, False) | |
| ) | |
| else: | |
| pipe0 = StableDiffusionImg2ImgPipeline.from_pretrained( | |
| current_model_path, | |
| torch_dtype=torchfloat, | |
| scheduler=DPMSolverMultistepScheduler.from_pretrained(current_model.path, subfolder="scheduler") | |
| ) | |
| # pipe = pipe.to("cpu") | |
| # pipe = current_model.pipe_i2i | |
| if torch.cuda.is_available(): | |
| pipe0 = pipe0.to("cuda") | |
| #pipe0.enable_xformers_memory_efficient_attention() | |
| last_mode = "img2img" | |
| prompt = current_model.prefix + prompt | |
| ratio = min(height / img.height, width / img.width) | |
| img = img.resize((int(img.width * ratio), int(img.height * ratio)), Image.LANCZOS) | |
| result = pipe0( | |
| prompt, | |
| negative_prompt = neg_prompt, | |
| num_images_per_prompt=n_images, | |
| image = img, | |
| num_inference_steps = int(steps), | |
| strength = strength, | |
| guidance_scale = guidance, | |
| # width = width, | |
| # height = height, | |
| generator = generator) | |
| return replace_nsfw_images(result) | |
| def replace_nsfw_images(results): | |
| #Only return 1 image for community sharing | |
| if is_colab: | |
| return results.images[0] | |
| for i in range(len(results.images)): | |
| if results.nsfw_content_detected[i]: | |
| results.images[i] = Image.open("nsfw_placeholder.jpg") | |
| return results.images[0] | |
| css = """ | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| a {text-decoration-line: underline; font-weight: 600;} | |
| .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; | |
| } | |
| #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; | |
| } | |
| #gallery{min-height:20rem} | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| gr.HTML( | |
| """ | |
| <div style="text-align: center; max-width: 700px; margin: 0 auto;"> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <h1 style="font-weight: 900; margin-bottom: 7px;"> | |
| DGSpitzer Diffusion Space | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Online Demo for <a href="https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion" target="_blank">Cyberpunk Anime Diffusion</a> & <a href="https://huggingface.co/DGSpitzer/DGSpitzer-Art-Diffusion" target="_blank">DGSpitzer Art Diffusion</a> & <a href="https://huggingface.co/DGSpitzer/Guan-Yu-Diffusion" target="_blank">Guan Yu Diffusion</a>. Based of the projects by anzorq <a href="https://twitter.com/hahahahohohe"></a> and fffiloni <a href="https://twitter.com/fffiloni"></a> | |
| </p> | |
| </div> | |
| <div | |
| style=" | |
| gap: 1.2rem; | |
| font-size: 1rem; | |
| " | |
| > | |
| <p>Another online version without queue: <a href="https://colab.research.google.com/github/HelixNGC7293/cyberpunk-anime-diffusion/blob/main/cyberpunk_anime_diffusion.ipynb"><img data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" src="https://camo.githubusercontent.com/84f0493939e0c4de4e6dbe113251b4bfb5353e57134ffd9fcab6b8714514d4d1/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667"></a></p> | |
| </div> | |
| """ | |
| ) | |
| gr.Markdown(''' | |
| 👇 Buy me a coffee if you like ♥ this project! | |
| [](https://www.buymeacoffee.com/dgspitzer) | |
| ''') | |
| with gr.Row(): | |
| with gr.Column(): | |
| model_name = gr.Dropdown(label="Model", choices=[m.name for m in models], value=current_model.name) | |
| #prompt = gr.Textbox(label="Prompt", show_label=False, max_lines=2, placeholder="Enter your prompt~", elem_id="input-prompt").style(container=False) | |
| prompt = gr.Textbox(label="Prompt", show_label=False, max_lines=2, placeholder="Enter your prompt~", elem_id="input-prompt") | |
| neg_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter what you don't want to generate", elem_id="input-neg-prompt") | |
| width_input = gr.Slider(label="Width", value=576, maximum=768, minimum=384, step=64) | |
| height_input = gr.Slider(label="Height", value=576, maximum=768, minimum=384, step=64) | |
| #n_images = gr.Slider(label="Images", value=1, minimum=1, maximum=4, step=1) | |
| guidance = gr.Slider(label="Guidance scale", value=7, maximum=10) | |
| steps = gr.Slider(label="Steps", value=20, maximum=50, minimum=2) | |
| seed = gr.Slider(0, 2147483647, label='Seed (0 = random)', value=0, step=1) | |
| run = gr.Button(value="Run") | |
| gr.Markdown(f"Running on: {device}") | |
| # with gr.Column(scale=45): | |
| # with gr.Tab("Text to Image"): | |
| # with gr.Group(): | |
| # gr.Markdown(f"Current in text to Image Mode, ") | |
| # #seed = gr.Slider(0, 2147483647, label='Seed (0 = random)', value=0, step=1) | |
| # with gr.Tab("Image to Image"): | |
| # with gr.Group(): | |
| # gr.Markdown(f"Image to Image Mode") | |
| # image = gr.Image(label="Image", height=256, tool="editor", type="pil") | |
| # strength = gr.Slider(label="Transformation strength", minimum=0, maximum=1, step=0.01, value=0.5) | |
| with gr.Column(): | |
| image_out = gr.Image(height=512, type="filepath", elem_id="output-img") | |
| error_output = gr.Markdown() | |
| #gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto") | |
| with gr.Column(elem_id="col-container"): | |
| with gr.Group(elem_id="share-btn-container"): | |
| community_icon = gr.HTML(community_icon_html, visible=False) | |
| loading_icon = gr.HTML(loading_icon_html, visible=False) | |
| share_button = gr.Button("Share to community", elem_id="share-btn", visible=False) | |
| if is_colab: | |
| model_name.change(on_model_change, inputs=model_name, outputs=[custom_model_group, prompt], queue=False) | |
| custom_model_path.change(custom_model_changed, inputs=custom_model_path, outputs=None) | |
| #outputs = [gallery, error_output] | |
| run.click(inference, inputs=[model_name, prompt, neg_prompt, guidance, steps, width_input, height_input, seed], outputs=[image_out, error_output, share_button, community_icon, loading_icon]) | |
| share_button.click(None, [], [], _js=share_js) | |
| gr.Examples([ | |
| [models[0].name, "perfect face portrait of beautiful smile girl, clean face, wears hoody, half body, soldier working in a cyberpunk city, cleavage, intricate, 8k, highly detailed, digital painting, intense, sharp focus", "out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 512, 704], | |
| [models[0].name, "portrait of a beautiful fancy gorgeous anime girl, intricate details", "out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 448, 640], | |
| [models[0].name, "city landscape with fancy car, racing on the road, gopro, intricate details, 4k, cyberpunk", "out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 704, 704], | |
| [models[0].name, "portrait of liu yifei girl, soldier working in a cyberpunk city, cleavage, intricate, 8k, highly detailed, digital painting, intense, sharp focus", "out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 704, 704], | |
| [models[0].name, "portrait of a muscular beard male in dgs illustration style, half-body, holding robot arms, strong chest", "out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 512, 640], | |
| [models[1].name, "portrait of professional photo of a cute girl, brown hair, freckles, perfect nose, fringe, green eyes, space clothing, space suit, glowing dragon logo on chest, dragon clothes, wearing orange dragon robe, blue dragon belt, dragon pants, dragon cape, action scene, dramatic pose, medium_breasts, perfect face, perfect eyes, pores, soft light,strong body, intricate detail,sharp focus, detailed background, masterpiece, highest quality, 4k, thick thighs, strong legs, tall, High detail RAW color, in spaceship, metal walls, feminine, highly detailed, white neon lights, skin pores, smile, high detail hair, sharp body, detailed body, gorgeous face, realistic, real, fit", "lowres, low quality, twisted,unappealing,uneven,unprofessional,draft,fake face, fake,uneven body, unnatural face, plastic face,out of focus,out of frame, poorly drawn, crippled, crooked, broken, weird, distorted, erased, cut, mutilated, sloppy, ugly, pixelated, bad hands, aliasing, poorly drawn, sloppy, over exposed, over saturated, burnt image, sloppy, fuzzy, poor quality, pixelated, sleepy, closed-eyes, pixelated, ugly, bad anatomy, hideous, deformed, mutant, sloppy, poorly drawn, poorly detailed, smudged, sketch, pencil, doll, plastic, disfigured, close up, topless, nude, naked, cleavage, tits, belly", 7, 30, 576, 576], | |
| [models[1].name, "professional photo portrait of muscular man male, brown hair, freckles, fringe, brown eyes, space clothing, space suit, glowing UNSC logo on chest, wearing blue astronaut robe, blue space belt, dragon pants, action scene, ", "lowres, low quality, twisted,unappealing,uneven,unprofessional,draft,fake face, fake,uneven body, unnatural face, plastic face,out of focus,out of frame, poorly drawn, crippled, crooked, broken, weird, distorted, erased, cut, mutilated, sloppy, ugly, pixelated, bad hands, aliasing, poorly drawn, sloppy, over exposed, over saturated, burnt image, sloppy, fuzzy, poor quality, pixelated, sleepy, closed-eyes, pixelated, ugly, bad anatomy, hideous, deformed, mutant, sloppy, poorly drawn, poorly detailed, smudged, sketch, pencil, doll, plastic, disfigured, close up, topless, nude, naked, cleavage, tits, belly", 7, 30, 576, 576], | |
| [models[1].name, "a painting of professional portrait steampunk lady doctor, smart eyes,high-tec huge glasses, very thick dark eyebrow, brown eyes, tan skin, short fancy braid hair, intricate deails, aquiline nose", "cat ear, body out of frame, deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limbs", 7, 30, 576, 576], | |
| [models[1].name, "a whiteshape professional portrait steampunk fancy bun very short hair girl, gears clothes, heavy armor, masterpiece, 4k, action scene, dramatic pose, small_breasts, perfect face, perfect eyes, pores, soft light,strong body, intricate detail,sharp focus, detailed background, masterpiece, highest quality, 4k, thick thighs, strong legs, tall, High detail RAW color, in spaceship, metal walls, feminine, highly detailed, white neon lights, skin pores, smile, high detail hair, sharp body, detailed body, gorgeous face, realistic, real, fit", "cat ear, body out of frame, deformed, blurry, bad anatomy, ugly, disfigured, poorly drawn face, mutation, mutated, extra limbs", 7, 30, 576, 576], | |
| [models[1].name, "outline anime portrait of a beautiful martial art girl", "saturation, purple, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[1].name, "a beautiful mech girl, 4k, photorealistic", "saturation", 7, 30, 576, 576], | |
| [models[1].name, "portrait of a girl, photorealistic painting paladin priest working in a magical tavern, cleavage, perfect face, curvy hair, intricate, 8k, highly detailed, intense, sharp focus, Anime, outline", "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet", 7, 30, 576, 576], | |
| [models[1].name, "a mech robot", "purple", 7, 30, 576, 576], | |
| [models[1].name, "portrait of a beautiful very young teen cowboy girl who embodies the rugged and independent spirit of the Old West. She should be strong-willed and confident, with a sharp sense of justice and a heart of gold. Her style should be a blend of traditional Western fashion and modern flair, with a touch of glamour and femininity. Whether she's taming wild horses, fighting off bandits, or just enjoying the sunset on the prairie, this cowboy girl is a force to be reckoned with and a sight to behold.", "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet", 7, 30, 576, 576], | |
| [models[1].name, "a muscular man from space", "blurry, out of focus", 7, 30, 576, 576], | |
| [models[1].name, "landscape of a cyberpunk soldier man in the battlefield, dark light, far away", "blurry, out of focus", 7, 30, 704, 576], | |
| [models[2].name, "Portrait of guanyu walking in ancient battlefield, close up shot", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "Portrait of a man holding very cute panda plushie, Guanyu", "", 7, 30, 576, 576], | |
| [models[2].name, "taking selfie on ancient battlefield of China, guanyu, gopro, sharp focus, old scratched photo, three kingdoms warriors everywhere, masterpiece", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "superman, portrait of fancy superhero guanyu, golden spiderman, mech, robot, high tech, shining core, intricate details, 4k", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "batman, portrait of fancy superhero guanyu, golden spiderman, mech, robot, high tech, shining core, intricate details, 4k", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a huge gundam mech fighting against guanyu", "blurry, out of focus", 7, 30, 576, 576], | |
| [models[2].name, "a cute nendoroid figure toy guanyu", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a cute funko figure toy guanyu", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a lego guanyu", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a gorgeous wuxia girl standing in the palace", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a handsome wuxia man", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| [models[2].name, "a wuxia girl diving underwater, surrounded by a shark", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 20, 576, 576], | |
| [models[2].name, "a cute nendoroid wuxia figure toy", "blurry, out of focus, scary, creepy, evil, disfigured, missing limbs, ugly, gross, missing fingers", 7, 30, 576, 576], | |
| ], [model_name, prompt, neg_prompt, guidance, steps, width_input, height_input], outputs=image_out, fn=inference_example, cache_examples=torch.cuda.is_available()) | |
| gr.Markdown(''' | |
| Models and Space by [@DGSpitzer](https://www.youtube.com/channel/UCzzsYBF4qwtMwJaPJZ5SuPg)❤️ [@大谷的游戏创作小屋](https://space.bilibili.com/176003) | |
| [](https://twitter.com/DGSpitzer) | |
|  | |
|  | |
| ''') | |
| if not is_colab: | |
| demo.queue(concurrency_count=1) | |
| demo.launch(debug=is_colab, share=is_colab) |