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Running
on
Zero
Running
on
Zero
import gradio as gr | |
import numpy as np | |
import random | |
import spaces | |
import torch | |
from diffusers import DiffusionPipeline | |
from transformers import pipeline | |
# ๋ฒ์ญ ํ์ดํ๋ผ์ธ ๋ฐ ํ๋์จ์ด ์ค์ | |
device = "cuda" if torch.cuda.is_available() else "cpu" | |
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", device=device) | |
dtype = torch.bfloat16 | |
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype).to(device) | |
MAX_SEED = np.iinfo(np.int32).max | |
MAX_IMAGE_SIZE = 2048 | |
def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)): | |
if randomize_seed: | |
seed = random.randint(0, MAX_SEED) | |
generator = torch.Generator().manual_seed(seed) | |
# ํ๊ธ ์ ๋ ฅ ๊ฐ์ง ๋ฐ ๋ฒ์ญ | |
if any('\uAC00' <= char <= '\uD7A3' for char in prompt): | |
print("Translating Korean prompt...") | |
translated_prompt = translator(prompt, max_length=512)[0]['translation_text'] | |
print("Translated prompt:", translated_prompt) | |
prompt = translated_prompt | |
image = pipe( | |
prompt = prompt, | |
width = width, | |
height = height, | |
num_inference_steps = num_inference_steps, | |
generator = generator, | |
guidance_scale=0.0 | |
).images[0] | |
return image, seed | |
examples = [ | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: ROCKET] [Text: 'WORLD'] [Background: BLUE COLOR]"], | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: UNIVERSE] [Text: 'COCA COLA'] [Background: COLORFUL]"], | |
["simple futuristic logo kamikaze drone on a shield, minimalistic, vector, 2D, simple lines, White background --v 4"], | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: MOUNTAIN] [Text: 'abc@gmail.com'] [Background: RED COLOR] "], | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: HUMAN] [Text: 'ABC.COM'] [Background: YELLOW COLOR] "], | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: HOUSE] [Text: 'T.010-1234-1234'] [Background: COLORFUL] "], | |
["Create a new logo for a [Color Tone: Blue] [Design Concept: LION] [Text: 'SOCCER CLUB'] [Background: GREEN COLOR]"] | |
] | |
css = """ | |
footer { | |
visibility: hidden; | |
} | |
""" | |
with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo: | |
with gr.Column(elem_id="col-container"): | |
with gr.Row(): | |
prompt = gr.Text( | |
label="Prompt", | |
show_label=False, | |
max_lines=1, | |
placeholder="Enter your prompt", | |
container=False, | |
elem_id="prompt" | |
) | |
run_button = gr.Button("Run", scale=0) | |
result = gr.Image(label="Result", show_label=False, elem_id="result") | |
with gr.Accordion("Advanced Settings", open=False, elem_id="advanced-settings"): | |
seed = gr.Slider( | |
label="Seed", | |
minimum=0, | |
maximum=MAX_SEED, | |
step=1, | |
value=0, | |
) | |
randomize_seed = gr.Checkbox(label="Randomize seed", value=True) | |
with gr.Row(): | |
width = gr.Slider( | |
label="Width", | |
minimum=256, | |
maximum=MAX_IMAGE_SIZE, | |
step=32, | |
value=512, | |
) | |
height = gr.Slider( | |
label="Height", | |
minimum=256, | |
maximum=MAX_IMAGE_SIZE, | |
step=32, | |
value=512, | |
) | |
with gr.Row(): | |
num_inference_steps = gr.Slider( | |
label="Number of inference steps", | |
minimum=1, | |
maximum=50, | |
step=1, | |
value=4, | |
) | |
gr.Examples( | |
examples=examples, | |
fn=infer, | |
inputs=[prompt], | |
outputs=[result, seed], | |
cache_examples="lazy" | |
) | |
gr.on( | |
triggers=[run_button.click, prompt.submit], | |
fn=infer, | |
inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps], | |
outputs=[result, seed] | |
) | |
demo.launch() | |