app.py

import spaces
import gradio as gr
import torch
from PIL import Image
from diffusers import DiffusionPipeline
import random
from transformers import pipeline


torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
torch.backends.cuda.matmul.allow_tf32 = True

# 번역 모델 초기화
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Flux-Xmas-Realpix-LoRA"
trigger_word = ""
pipe.load_lora_weights(lora_repo)

pipe.to("cuda")



MAX_SEED = 2**32-1

@spaces.GPU()
def translate_and_generate(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
    # 한글 감지 및 번역
    def contains_korean(text):
        return any(ord('가') <= ord(char) <= ord('힣') for char in text)
    
    if contains_korean(prompt):
        # 한글을 영어로 번역
        translated = translator(prompt)[0]['translation_text']
        actual_prompt = translated
    else:
        actual_prompt = prompt

    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    generator = torch.Generator(device="cuda").manual_seed(seed)

    progress(0, "Starting image generation...")

    for i in range(1, steps + 1):
        if i % (steps // 10) == 0:
            progress(i / steps * 100, f"Processing step {i} of {steps}...")

    image = pipe(
        prompt=f"{actual_prompt} {trigger_word}",
        num_inference_steps=steps,
        guidance_scale=cfg_scale,
        width=width,
        height=height,
        generator=generator,
        joint_attention_kwargs={"scale": lora_scale},
    ).images[0]

    progress(100, "Completed!")
    return image, seed

example_image_path = "example0.webp"
example_prompt = """Cozy winter scene with a Christmas atmosphere: a snow-covered cabin in the forest, warm light glowing from the windows, surrounded by sparkling Christmas decorations and a beautifully adorned Christmas tree. The sky is filled with stars, and soft snowflakes are gently falling, creating a serene and warm ambiance"""
example_cfg_scale = 3.2
example_steps = 32
example_width = 1152
example_height = 896
example_seed = 3981632454
example_lora_scale = 0.85

def load_example():
    example_image = Image.open(example_image_path)
    return example_prompt, example_cfg_scale, example_steps, True, example_seed, example_width, example_height, example_lora_scale, example_image

css = """
.container {
    max-width: 1400px; 
    margin: auto; 
    padding: 20px;
    position: relative;
    min-height: 100vh;
}
body {
    background-image: url('file/example0.webp');
    background-size: cover;
    background-position: center;
    background-attachment: fixed;
    margin: 0;
    padding: 0;
}
.header {
    text-align: center; 
    margin-bottom: 30px;
    color: white;
    text-shadow: 2px 2px 4px rgba(0,0,0,0.7);
}
.generate-btn {
    background-color: #2ecc71 !important; 
    color: white !important; 
    margin: 20px auto !important; 
    display: block !important; 
    width: 200px !important;
}
.generate-btn:hover {
    background-color: #27ae60 !important;
}
.parameter-box, .result-box, .prompt-box, .audio-controls {
    background-color: rgba(245, 246, 250, 0.8);
    padding: 20px; 
    border-radius: 10px; 
    margin: 10px 0;
    backdrop-filter: blur(5px);
}
.result-box {
    width: 90%;
    margin: 20px auto;
}
.image-output {
    margin: 0 auto; 
    display: block; 
    max-width: 800px !important;
}
.prompt-box {
    width: 90%;
    margin: 20px auto;
}
.accordion {
    margin-top: 20px;
    background-color: rgba(245, 246, 250, 0.8);
    backdrop-filter: blur(5px);
}
.audio-controls {
    position: fixed;
    bottom: 20px;
    right: 20px;
    z-index: 1000;
    display: flex;
    gap: 10px;
    align-items: center;
}
.audio-btn {
    padding: 10px 20px;
    border-radius: 5px;
    border: none;
    background: rgba(46, 204, 113, 0.9);
    color: white;
    cursor: pointer;
}
.audio-btn:hover {
    background: rgba(39, 174, 96, 0.9);
}
@keyframes snow {
    0% {
        transform: translateY(0) translateX(0);
    }
    100% {
        transform: translateY(100vh) translateX(100px);
    }
}

.snowflake {
    position: fixed;
    top: -10px;
    color: white;
    font-size: 20px;
    animation: snow 5s linear infinite;
}
@keyframes snow {
    0% {
        transform: translateY(0) translateX(0);
    }
    100% {
        transform: translateY(100vh) translateX(100px);
    }
}

.snowflake {
    position: fixed;
    top: -10px;
    color: white;
    font-size: 20px;
    animation: snow 5s linear infinite;
}
"""
js_code = """
function createSnowflake() {
    const snowflake = document.createElement('div');
    snowflake.classList.add('snowflake');
    snowflake.innerHTML = '❄';
    snowflake.style.left = Math.random() * 100 + 'vw';
    snowflake.style.animationDuration = Math.random() * 3 + 2 + 's';
    snowflake.style.opacity = Math.random();
    document.body.appendChild(snowflake);
    
    setTimeout(() => {
        snowflake.remove();
    }, 5000);
}

setInterval(createSnowflake, 100);
"""
with gr.Blocks(css=css) as app:
    gr.HTML(f"<script>{js_code}</script>")
    
    with gr.Column(elem_classes="container"):
        gr.Markdown("# 🎄 X-MAS LoRA", elem_classes="header")
        
        # 이미지 출력 영역
        with gr.Group(elem_classes="result-box"):
            gr.Markdown("### 🖼️ Generated Image")
            result = gr.Image(label="Result", elem_classes="image-output")
        
        # 프롬프트 입력 박스
        with gr.Group(elem_classes="prompt-box"):
            prompt = gr.TextArea(
                label="✍️ Your Prompt (한글 또는 영어)",
                placeholder="이미지를 설명하세요...",
                lines=5
            )
            generate_button = gr.Button(
                "🚀 Generate Image",
                elem_classes="generate-btn"
            )
        
        # 옵션들을 아코디언으로 구성
        with gr.Accordion("🎨 Advanced Options", open=False, elem_classes="accordion"):
            with gr.Group(elem_classes="parameter-box"):
                gr.Markdown("### 🎛️ Generation Parameters")
                with gr.Row():
                    with gr.Column():
                        cfg_scale = gr.Slider(
                            label="CFG Scale",
                            minimum=1,
                            maximum=20,
                            step=0.5,
                            value=example_cfg_scale
                        )
                        steps = gr.Slider(
                            label="Steps",
                            minimum=1,
                            maximum=100,
                            step=1,
                            value=example_steps
                        )
                        lora_scale = gr.Slider(
                            label="LoRA Scale",
                            minimum=0,
                            maximum=1,
                            step=0.01,
                            value=example_lora_scale
                        )
            
            with gr.Group(elem_classes="parameter-box"):
                gr.Markdown("### 📐 Image Dimensions")
                with gr.Row():
                    width = gr.Slider(
                        label="Width",
                        minimum=256,
                        maximum=1536,
                        step=64,
                        value=example_width
                    )
                    height = gr.Slider(
                        label="Height",
                        minimum=256,
                        maximum=1536,
                        step=64,
                        value=example_height
                    )
            
            with gr.Group(elem_classes="parameter-box"):
                gr.Markdown("### 🎲 Seed Settings")
                with gr.Row():
                    randomize_seed = gr.Checkbox(
                        True,
                        label="Randomize seed"
                    )
                    seed = gr.Slider(
                        label="Seed",
                        minimum=0,
                        maximum=MAX_SEED,
                        step=1,
                        value=example_seed
                    )

    # 오디오 컨트롤 - 컨테이너 밖에 배치
    gr.HTML("""
        <div class="audio-controls">
            <button class="audio-btn" onclick="toggleAudio(1)">Play Music 1</button>
            <button class="audio-btn" onclick="toggleAudio(2)">Play Music 2</button>
            <button class="audio-btn" onclick="stopAllAudio()">Stop All</button>
        </div>
        <audio id="bgMusic1" loop style="display: none;">
            <source src="file/1.mp3" type="audio/mp3">
        </audio>
        <audio id="bgMusic2" loop style="display: none;">
            <source src="file/2.mp3" type="audio/mp3">
        </audio>
        <script>
            let currentlyPlaying = null;
            
            function toggleAudio(num) {
                const audio = document.getElementById('bgMusic' + num);
                const otherAudio = document.getElementById('bgMusic' + (num === 1 ? 2 : 1));
                
                if (currentlyPlaying === audio) {
                    audio.pause();
                    currentlyPlaying = null;
                } else {
                    if (currentlyPlaying) {
                        currentlyPlaying.pause();
                    }
                    otherAudio.pause();
                    audio.play();
                    currentlyPlaying = audio;
                }
            }
            
            function stopAllAudio() {
                document.getElementById('bgMusic1').pause();
                document.getElementById('bgMusic2').pause();
                currentlyPlaying = null;
            }
        </script>
    """)

    app.load(
        load_example,
        inputs=[],
        outputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, result]
    )
    
    generate_button.click(
        translate_and_generate,
        inputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
        outputs=[result, seed]
    )

app.queue()
app.launch()