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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
@spaces.GPU()
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: '[email protected]'] [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()
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