| import gradio as gr
|
| from huggingface_hub import InferenceClient
|
| import random
|
| import os
|
| import time
|
| from PIL import Image
|
| from deep_translator import GoogleTranslator
|
| import json
|
|
|
|
|
|
|
| MODEL = "stabilityai/stable-diffusion-3-medium-diffusers"
|
| API_TOKEN = os.getenv("HF_READ_TOKEN")
|
|
|
|
|
| def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, oauth_token: gr.OAuthToken | None = None):
|
| if prompt == "" or prompt == None:
|
| return None
|
|
|
| key = random.randint(0, 999)
|
|
|
|
|
| token = oauth_token.token if oauth_token is not None else API_TOKEN
|
| if not token:
|
| raise gr.Error("Please sign in with Hugging Face to generate images.")
|
|
|
| try:
|
| prompt = GoogleTranslator(source='auto', target='en').translate(prompt) or prompt
|
| except Exception as e:
|
| print(f"Translation skipped: {e}")
|
| print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
|
|
|
| prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
|
| print(f'\033[1mGeneration {key}:\033[0m {prompt}')
|
|
|
| client = InferenceClient(token=token)
|
| try:
|
| image = client.text_to_image(
|
| prompt,
|
| model=MODEL,
|
| negative_prompt=is_negative or None,
|
| num_inference_steps=int(steps),
|
| guidance_scale=float(cfg_scale),
|
| seed=int(seed) if int(seed) != -1 else random.randint(1, 1000000000),
|
| )
|
| except Exception as e:
|
| print(f"Error: Failed to get image: {e}")
|
| raise gr.Error(f"Generation failed: {e}")
|
| print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
|
| return image
|
|
|
| css = """
|
| #app-container {
|
| max-width: 600px;
|
| margin-left: auto;
|
| margin-right: auto;
|
| }
|
| """
|
|
|
| with gr.Blocks() as app:
|
| gr.LoginButton()
|
| gr.HTML("<center><h1>Stable Diffusion 3 Medium</h1></center>")
|
| with gr.Column(elem_id="app-container"):
|
| with gr.Row():
|
| with gr.Column(elem_id="prompt-container"):
|
| with gr.Row():
|
| text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
|
| with gr.Row():
|
| with gr.Accordion("Advanced Settings", open=False):
|
| negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
|
| steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
|
| cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
|
| method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
|
| strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
|
| seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
|
|
|
| with gr.Row():
|
| text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
|
| with gr.Row():
|
| image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
|
|
|
| text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength], outputs=image_output)
|
|
|
| app.launch(theme='Nymbo/Nymbo_Theme', css=css, footer_links=["gradio", "settings"]) |
