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| import gradio as gr | |
| import requests | |
| import io | |
| import random | |
| import os | |
| from PIL import Image | |
| from deep_translator import GoogleTranslator | |
| from langdetect import detect | |
| API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl" | |
| API_TOKEN = os.getenv("HF_READ_TOKEN") | |
| headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
| models_list = ["AbsoluteReality 1.8.1", "DALL-E 3 XL", "Playground 2", "Openjourney 4", "Lyriel 1.6", "Animagine XL 2.0", "Counterfeit 2.5", "Realistic Vision 5.1", "Incursios 1.6", "Anime Detailer XL", "Vector Art XL", "epiCRealism", "PixelArt XL", "NewReality XL", "Anything 5.0", "PixArt XL 2.0", "Disney Cartoon", "CleanLinearMix", "Waifu 1.4"] | |
| def query(prompt, model, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, width=512, height=512): | |
| if prompt == "" or prompt == None: | |
| return None | |
| API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN"), os.getenv("HF_READ_TOKEN_2"), os.getenv("HF_READ_TOKEN_3"), os.getenv("HF_READ_TOKEN_4"), os.getenv("HF_READ_TOKEN_5")]) # it is free | |
| headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
| language = detect(prompt) | |
| key = random.randint(0, 999) | |
| print(f'\033[1mГенерация {key}:\033[0m {prompt}') | |
| if language == 'ru': | |
| prompt = GoogleTranslator(source='ru', target='en').translate(prompt) | |
| print(f'\033[1mГенерация {key} перевод:\033[0m {prompt}') | |
| if model == 'DALL-E 3 XL': | |
| API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl" | |
| if model == 'Playground 2': | |
| API_URL = "https://api-inference.huggingface.co/models/playgroundai/playground-v2-1024px-aesthetic" | |
| if model == 'Openjourney 4': | |
| API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney-v4" | |
| if model == 'AbsoluteReality 1.8.1': | |
| API_URL = "https://api-inference.huggingface.co/models/digiplay/AbsoluteReality_v1.8.1" | |
| if model == 'Lyriel 1.6': | |
| API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/lyrielv16" | |
| if model == 'Animagine XL 2.0': | |
| API_URL = "https://api-inference.huggingface.co/models/Linaqruf/animagine-xl-2.0" | |
| if model == 'Counterfeit 2.5': | |
| API_URL = "https://api-inference.huggingface.co/models/gsdf/Counterfeit-V2.5" | |
| if model == 'Realistic Vision 5.1': | |
| API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/realistic-vision-v51" | |
| if model == 'Incursios 1.6': | |
| API_URL = "https://api-inference.huggingface.co/models/digiplay/incursiosMemeDiffusion_v1.6" | |
| if model == 'Anime Detailer XL': | |
| API_URL = "https://api-inference.huggingface.co/models/Linaqruf/anime-detailer-xl-lora" | |
| if model == 'epiCRealism': | |
| API_URL = "https://api-inference.huggingface.co/models/emilianJR/epiCRealism" | |
| if model == 'PixelArt XL': | |
| API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl" | |
| if model == 'NewReality XL': | |
| API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/newrealityxl-global-nsfw" | |
| if model == 'Anything 5.0': | |
| API_URL = "https://api-inference.huggingface.co/models/hogiahien/anything-v5-edited" | |
| if model == 'PixArt XL 2.0': | |
| API_URL = "https://api-inference.huggingface.co/models/PixArt-alpha/PixArt-XL-2-1024-MS" | |
| if model == 'Vector Art XL': | |
| API_URL = "https://api-inference.huggingface.co/models/DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora" | |
| if model == 'Disney Cartoon': | |
| API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/disney-pixal-cartoon" | |
| if model == 'CleanLinearMix': | |
| API_URL = "https://api-inference.huggingface.co/models/digiplay/CleanLinearMix_nsfw" | |
| if model == 'Waifu 1.4': | |
| API_URL = "https://api-inference.huggingface.co/models/gisohi6975/nsfw-waifu-diffusion" | |
| payload = { | |
| "inputs": prompt, | |
| "is_negative": is_negative, | |
| "steps": steps, | |
| "cfg_scale": cfg_scale, | |
| "seed": seed if seed != -1 else random.randint(1, 1000000000), | |
| "width": width, | |
| "height": height | |
| } | |
| image_bytes = requests.post(API_URL, headers=headers, json=payload).content | |
| image = Image.open(io.BytesIO(image_bytes)) | |
| print(f'\033[1mГенерация {key} завершена!\033[0m ({prompt})') | |
| return image | |
| css = """ | |
| footer {visibility: hidden !important;} | |
| """ | |
| with gr.Blocks(css=css) as dalle: | |
| with gr.Tab("Базовые настройки"): | |
| with gr.Row(): | |
| with gr.Column(elem_id="prompt-container"): | |
| with gr.Row(): | |
| text_prompt = gr.Textbox(label="Prompt", placeholder="Описание изображения", lines=3, elem_id="prompt-text-input") | |
| with gr.Row(): | |
| model = gr.Radio(label="Модель", value="DALL-E 3 XL", choices=models_list) | |
| with gr.Tab("Расширенные настройки"): | |
| with gr.Row(): | |
| negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Чего не должно быть на изображении", value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness", lines=3, elem_id="negative-prompt-text-input") | |
| with gr.Row(): | |
| steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1) | |
| with gr.Row(): | |
| cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1) | |
| with gr.Row(): | |
| method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"]) | |
| with gr.Row(): | |
| seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) | |
| with gr.Tab("Beta"): | |
| with gr.Row(): | |
| width = gr.Slider(label="Ширина", value=512, minimum=15, maximum=1024, step=1) | |
| height = gr.Slider(label="Длина", value=512, minimum=15, maximum=1024, step=1) | |
| with gr.Row(): | |
| text_button = gr.Button("Генерация", variant='primary', elem_id="gen-button") | |
| with gr.Row(): | |
| image_output = gr.Image(type="pil", label="Изображение", elem_id="gallery") | |
| text_button.click(query, inputs=[text_prompt, model, negative_prompt, steps, cfg, method, seed, width, height], outputs=image_output) | |
| dalle.launch(show_api=False) |