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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") # it is free
headers = {"Authorization": f"Bearer {API_TOKEN}"}
def query(prompt, model, is_negative=False, steps=20, cfg_scale=7, seed=None):
language = detect(prompt)
if language == 'ru':
prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
print(f'\033[1mГенерация:\033[0m {prompt}')
if model == 'DALL-E 3 XL':
API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
if model == 'SDXL Turbo':
API_URL = "https://api-inference.huggingface.co/models/stabilityai/sdxl-turbo"
payload = {
"inputs": prompt,
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
image_bytes = requests.post(API_URL, headers=headers, json=payload).content
image = Image.open(io.BytesIO(image_bytes))
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"):
text_prompt = gr.Textbox(label="Prompt", placeholder="Описание изображения", lines=3, elem_id="prompt-text-input")
model = gr.Radio(label="Модель", value="DALL-E 3 XL", choices=["DALL-E 3 XL", "SDXL Turbo"])
with gr.Tab("Расширенные настройки"):
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():
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], outputs=image_output)
dalle.launch(show_api=False) |