Delete app-backup.py

app-backup.py

@@ -1,345 +0,0 @@
-import spaces
-import argparse
-import os
-import time
-from os import path
-import shutil
-from datetime import datetime
-from safetensors.torch import load_file
-from huggingface_hub import hf_hub_download
-import gradio as gr
-import torch
-from diffusers import FluxPipeline
-from PIL import Image
-from transformers import pipeline
-import base64
-
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
-
-# Hugging Face 토큰 설정
-HF_TOKEN = os.getenv("HF_TOKEN")
-if HF_TOKEN is None:
-    raise ValueError("HF_TOKEN environment variable is not set")
-
-# Setup and initialization code
-cache_path = path.join(path.dirname(path.abspath(__file__)), "models")
-PERSISTENT_DIR = os.environ.get("PERSISTENT_DIR", ".")
-gallery_path = path.join(PERSISTENT_DIR, "gallery")
-
-os.environ["TRANSFORMERS_CACHE"] = cache_path
-os.environ["HF_HUB_CACHE"] = cache_path
-os.environ["HF_HOME"] = cache_path
-
-torch.backends.cuda.matmul.allow_tf32 = True
-
-# Create gallery directory if it doesn't exist
-if not path.exists(gallery_path):
-    os.makedirs(gallery_path, exist_ok=True)
-
-# 샘플 이미지와 프롬프트 정의
-SAMPLE_IMAGES = {
-    "3d2.webp": "the most famous hero according to Yuri Milner",
-    "3d3.webp": "purple nest",
-    "3d4.webp": "Timothy's sabbath",
-    "3d5.webp": "A schoolboy friend of Julián Carax, fun-loving and loyal",
-    "3d6.webp": "Friend of Daniel and his father",
-    "3d7.webp": "WHERE ships of purple gently toss On seas of daffodil",
-    "3d8.webp": "Beat the drums of tragedy for me, And let the white violins whir thin and slow",
-    "3d9.webp": "And let the choir sing a stormy song To drown the rattle of my dying breath.",
-    "3d10.webp": "Beat the drums of tragedy and death",
-    "3d11.webp": "Beat the drums of tragedy for me.",
-    "3d12.webp": "Touching the infinite, else far and untrod, With oracles divine that speak of God.",
-    "3d13.webp": "Night, standing on her starry pulpit, free, Utters them in the dread, the silver roll Of spheres, woods, winds and waves, alternately",
-    "3d14.webp": "On sermons deep, fit time to feast the soul.",
-    "3d15.webp": "The bee is cradled in the bud; and far, Cold glittering lights, the azure curtain, throng— Planet on beaming planet, star on star.",
-    "3d16.webp": "The lark's sweet pipe has ceased its latest song",
-    "3d17.webp": "the snake was a roaming dog",
-    "3d18.webp": "Antonio Battistella portraying Father of Giulia",
-    "3d19.webp": "So straight to her father the brisk young lady went, And said, grant me one favour, do give your consent",
-    "3d20.webp": "Before that we are marry’d let me your father see, All fear is, now miscarry’d, my heart is full of glee",
-    "3d21.webp": "My heart you now have gained, you are all I prize, So make yourself contented, pray be satisfied.",
-    "3d22.webp": "O pray what is the favour that of me you crave? If it lies in my power you the same shall have",
-    "3d23.webp": "Could I but see your father, and my mind reveal, I have both gold and silver, and houses at my will",
-    "3d1.webp": "the most famous hero according to Zhou Qi"
-}
-
-class timer:
-    def __init__(self, method_name="timed process"):
-        self.method = method_name
-    def __enter__(self):
-        self.start = time.time()
-        print(f"{self.method} starts")
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        end = time.time()
-        print(f"{self.method} took {str(round(end - self.start, 2))}s")
-
-# Model initialization
-if not path.exists(cache_path):
-    os.makedirs(cache_path, exist_ok=True)
-
-pipe = FluxPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-dev",
-    torch_dtype=torch.bfloat16,
-    use_auth_token=HF_TOKEN  # 경고 메시지가 뜨지만 무시 가능
-)
-
-# Hyper-SD LoRA 로드
-pipe.load_lora_weights(
-    hf_hub_download(
-        "ByteDance/Hyper-SD",
-        "Hyper-FLUX.1-dev-8steps-lora.safetensors",
-        use_auth_token=HF_TOKEN
-    )
-)
-pipe.fuse_lora(lora_scale=0.125)
-pipe.to(device="cuda", dtype=torch.bfloat16)
-
-def save_image(image):
-    """Save the generated image and return the path"""
-    try:
-        if not os.path.exists(gallery_path):
-            try:
-                os.makedirs(gallery_path, exist_ok=True)
-            except Exception as e:
-                print(f"Failed to create gallery directory: {str(e)}")
-                return None
-        
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        random_suffix = os.urandom(4).hex()
-        filename = f"generated_{timestamp}_{random_suffix}.png"
-        filepath = os.path.join(gallery_path, filename)
-        
-        try:
-            if isinstance(image, Image.Image):
-                image.save(filepath, "PNG", quality=100)
-            else:
-                image = Image.fromarray(image)
-                image.save(filepath, "PNG", quality=100)
-            
-            return filepath
-        except Exception as e:
-            print(f"Failed to save image: {str(e)}")
-            return None
-            
-    except Exception as e:
-        print(f"Error in save_image: {str(e)}")
-        return None
-
-def get_random_seed():
-    return torch.randint(0, 1000000, (1,)).item()
-
-@spaces.GPU
-def process_and_save_image(height=1024, width=1024, steps=8, scales=3.5, prompt="", seed=None):
-    global pipe
-    
-    if seed is None:
-        seed = get_random_seed()
-    
-    # 한글 감지 및 번역
-    def contains_korean(text):
-        return any(ord('가') <= ord(c) <= ord('힣') for c in text)
-    
-    # 프롬프트 전처리
-    if contains_korean(prompt):
-        translated = translator(prompt)[0]['translation_text']
-        prompt = translated
-    
-    formatted_prompt = f"wbgmsst, 3D, {prompt}, white background"
-    
-    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("inference"):
-        try:
-            generated_image = pipe(
-                prompt=[formatted_prompt],
-                generator=torch.Generator().manual_seed(int(seed)),
-                num_inference_steps=int(steps),
-                guidance_scale=float(scales),
-                height=int(height),
-                width=int(width),
-                max_sequence_length=256
-            ).images[0]
-            
-            saved_path = save_image(generated_image)
-            if saved_path is None:
-                print("Warning: Failed to save generated image")
-            
-            return generated_image
-        except Exception as e:
-            print(f"Error in image generation: {str(e)}")
-            return None
-
-def update_random_seed():
-    """버튼으로 눌렀을 때 새로운 시드를 업데이트"""
-    return gr.update(value=get_random_seed())
-
-# Gradio 인터페이스
-with gr.Blocks(
-    theme=gr.themes.Soft(),
-    css="""
-        .container {
-            background: linear-gradient(to bottom right, #1a1a1a, #4a4a4a);
-            border-radius: 20px;
-            padding: 20px;
-        }
-        .generate-btn {
-            background: linear-gradient(45deg, #2196F3, #00BCD4);
-            border: none;
-            color: white;
-            font-weight: bold;
-            border-radius: 10px;
-        }
-        .output-image {
-            border-radius: 15px;
-            box-shadow: 0 8px 16px rgba(0,0,0,0.2);
-        }
-        .fixed-width {
-            max-width: 1024px;
-            margin: auto;
-        }
-        .gallery-container {
-            margin-top: 40px;
-            padding: 20px;
-            background: #f5f5f5;
-            border-radius: 15px;
-            width: 100%;
-            margin: 0 auto;
-        }
-        .gallery-title {
-            text-align: center;
-            margin-bottom: 20px;
-            color: #333;
-            font-size: 1.5rem;
-        }
-    """
-) as demo:
-    gr.HTML(
-        """
-        <div style="text-align: center; max-width: 800px; margin: 0 auto; padding: 20px;">
-            <h1 style="font-size: 2.5rem; color: #2196F3;">3D Style Image Generator v2.0</h1>
-            <p style="font-size: 1.2rem; color: #666;">Create amazing 3D-style images with AI. https://discord.gg/openfreeai </p>
-        </div>
-        """
-    )
-    
-    with gr.Row(elem_classes="container"):
-        with gr.Column(scale=3):
-            prompt = gr.Textbox(
-                label="Image Description",
-                placeholder="Describe the 3D image you want to create...",
-                lines=3
-            )
-            
-            with gr.Accordion("Advanced Settings", open=False):
-                with gr.Row():
-                    height = gr.Slider(
-                        label="Height",
-                        minimum=256,
-                        maximum=1152,
-                        step=64,
-                        value=1024
-                    )
-                    width = gr.Slider(
-                        label="Width",
-                        minimum=256,
-                        maximum=1152,
-                        step=64,
-                        value=1024
-                    )
-                
-                with gr.Row():
-                    steps = gr.Slider(
-                        label="Inference Steps",
-                        minimum=6,
-                        maximum=25,
-                        step=1,
-                        value=8
-                    )
-                    scales = gr.Slider(
-                        label="Guidance Scale",
-                        minimum=0.0,
-                        maximum=5.0,
-                        step=0.1,
-                        value=3.5
-                    )
-                
-                seed = gr.Number(
-                    label="Seed (random by default, set for reproducibility)",
-                    value=get_random_seed(),
-                    precision=0
-                )
-                
-                randomize_seed = gr.Button("🎲 Randomize Seed", elem_classes=["generate-btn"])
-            
-            generate_btn = gr.Button(
-                "✨ Generate Image",
-                elem_classes=["generate-btn"]
-            )
-
-        with gr.Column(scale=4, elem_classes=["fixed-width"]):
-            output = gr.Image(
-                label="Generated Image",
-                elem_id="output-image",
-                elem_classes=["output-image", "fixed-width"],
-                value="3d.webp"
-            )
-
-    # gallery-container 부분을 Group으로 감싸 화면 전체에 확장
-    with gr.Group(elem_classes="gallery-container"):
-        gr.HTML("<h2 class='gallery-title'>Gallery</h2>")
-        
-        gallery_html = """
-        <div style='
-            display: grid; 
-            grid-template-columns: repeat(4, 1fr); 
-            gap: 20px;
-            width: 100%;
-        '>
-        """
-        
-        for img_file, prompt_text in SAMPLE_IMAGES.items():
-            img_path = os.path.abspath(img_file)
-            if os.path.exists(img_path):
-                try:
-                    with open(img_path, "rb") as img:
-                        img_data = base64.b64encode(img.read()).decode()
-                    gallery_html += f"""
-                    <div style='
-                        border: 1px solid #ddd;
-                        border-radius: 10px;
-                        padding: 10px;
-                        background: white;
-                        box-shadow: 0 4px 8px rgba(0,0,0,0.1);
-                    '>
-                        <img src='data:image/webp;base64,{img_data}'
-                            style='width: 100%; 
-                            border-radius: 8px;
-                            margin-bottom: 10px;'
-                        >
-                        <p style='
-                            margin: 5px 0;
-                            font-weight: bold;
-                            color: #333;
-                            padding: 10px;
-                        '>Prompt: {prompt_text}</p>
-                    </div>
-                    """
-                except Exception as e:
-                    print(f"Error loading image {img_file}: {str(e)}")
-        
-        gallery_html += "</div>"
-        gr.HTML(gallery_html)
-    
-    # 이벤트 핸들러
-    generate_btn.click(
-        fn=process_and_save_image,
-        inputs=[height, width, steps, scales, prompt, seed],
-        outputs=output
-    )
-
-    randomize_seed.click(
-        fn=update_random_seed,
-        inputs=None,
-        outputs=seed
-    )
-
-if __name__ == "__main__":
-    demo.launch(allowed_paths=[PERSISTENT_DIR])