File size: 3,924 Bytes
9ea64ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | 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
# Project by Nymbo
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)
# Prefer the visitor's own account (Sign in with Hugging Face); fall back to the Space token.
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"]) |