Delete app.py

app.py

@@ -1,914 +0,0 @@
-import spaces
-import argparse
-import os
-import shutil
-import cv2
-import gradio as gr
-import numpy as np
-import torch
-from facexlib.utils.face_restoration_helper import FaceRestoreHelper
-import huggingface_hub
-from huggingface_hub import hf_hub_download
-from PIL import Image
-from torchvision.transforms.functional import normalize
-from gradio_client import Client
-import logging
-import time
-
-from dreamo.dreamo_pipeline import DreamOPipeline
-from dreamo.utils import img2tensor, resize_numpy_image_area, tensor2img, resize_numpy_image_long
-from tools import BEN2
-
-parser = argparse.ArgumentParser()
-parser.add_argument('--port', type=int, default=8080)
-parser.add_argument('--no_turbo', action='store_true')
-args = parser.parse_args()
-
-huggingface_hub.login(os.getenv('HF_TOKEN'))
-
-# Text-to-Image API URL
-TEXT2IMG_API_URL = "http://211.233.58.201:7896"
-
-# 로깅 설정
-logging.basicConfig(
-    level=logging.DEBUG,
-    format='%(asctime)s - %(levelname)s - %(message)s')
-
-try:
-    shutil.rmtree('gradio_cached_examples')
-except FileNotFoundError:
-    print("cache folder not exist")
-
-class Generator:
-    def __init__(self):
-        device = torch.device('cuda')
-        # preprocessing models
-        # background remove model: BEN2
-        self.bg_rm_model = BEN2.BEN_Base().to(device).eval()
-        hf_hub_download(repo_id='PramaLLC/BEN2', filename='BEN2_Base.pth', local_dir='models')
-        self.bg_rm_model.loadcheckpoints('models/BEN2_Base.pth')
-        # face crop and align tool: facexlib
-        self.face_helper = FaceRestoreHelper(
-            upscale_factor=1,
-            face_size=512,
-            crop_ratio=(1, 1),
-            det_model='retinaface_resnet50',
-            save_ext='png',
-            device=device,
-        )
-
-        # load dreamo
-        model_root = 'black-forest-labs/FLUX.1-dev'
-        dreamo_pipeline = DreamOPipeline.from_pretrained(model_root, torch_dtype=torch.bfloat16)
-        dreamo_pipeline.load_dreamo_model(device, use_turbo=not args.no_turbo)
-        self.dreamo_pipeline = dreamo_pipeline.to(device)
-
-    @torch.no_grad()
-    def get_align_face(self, img):
-        # the face preprocessing code is same as PuLID
-        self.face_helper.clean_all()
-        image_bgr = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
-        self.face_helper.read_image(image_bgr)
-        self.face_helper.get_face_landmarks_5(only_center_face=True)
-        self.face_helper.align_warp_face()
-        if len(self.face_helper.cropped_faces) == 0:
-            return None
-        align_face = self.face_helper.cropped_faces[0]
-
-        input = img2tensor(align_face, bgr2rgb=True).unsqueeze(0) / 255.0
-        input = input.to(torch.device("cuda"))
-        parsing_out = self.face_helper.face_parse(normalize(input, [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]))[0]
-        parsing_out = parsing_out.argmax(dim=1, keepdim=True)
-        bg_label = [0, 16, 18, 7, 8, 9, 14, 15]
-        bg = sum(parsing_out == i for i in bg_label).bool()
-        white_image = torch.ones_like(input)
-        # only keep the face features
-        face_features_image = torch.where(bg, white_image, input)
-        face_features_image = tensor2img(face_features_image, rgb2bgr=False)
-
-        return face_features_image
-
-
-generator = Generator()
-
-
-@spaces.GPU
-@torch.inference_mode()
-def generate_image(
-    ref_image1,
-    ref_image2,
-    ref_task1,
-    ref_task2,
-    prompt,
-    seed,
-    width=1024,
-    height=1024,
-    ref_res=512,
-    num_steps=12,
-    guidance=3.5,
-    true_cfg=1,
-    cfg_start_step=0,
-    cfg_end_step=0,
-    neg_prompt='',
-    neg_guidance=3.5,
-    first_step_guidance=0,
-):
-    print(prompt)
-    ref_conds = []
-    debug_images = []
-
-    ref_images = [ref_image1, ref_image2]
-    ref_tasks = [ref_task1, ref_task2]
-
-    for idx, (ref_image, ref_task) in enumerate(zip(ref_images, ref_tasks)):
-        if ref_image is not None:
-            if ref_task == "id":
-                ref_image = resize_numpy_image_long(ref_image, 1024)
-                ref_image = generator.get_align_face(ref_image)
-            elif ref_task != "style":
-                ref_image = generator.bg_rm_model.inference(Image.fromarray(ref_image))
-            if ref_task != "id":
-                ref_image = resize_numpy_image_area(np.array(ref_image), ref_res * ref_res)
-            debug_images.append(ref_image)
-            ref_image = img2tensor(ref_image, bgr2rgb=False).unsqueeze(0) / 255.0
-            ref_image = 2 * ref_image - 1.0
-            ref_conds.append(
-                {
-                    'img': ref_image,
-                    'task': ref_task,
-                    'idx': idx + 1,
-                }
-            )
-
-    seed = int(seed)
-    if seed == -1:
-        seed = torch.Generator(device="cpu").seed()
-
-    image = generator.dreamo_pipeline(
-        prompt=prompt,
-        width=width,
-        height=height,
-        num_inference_steps=num_steps,
-        guidance_scale=guidance,
-        ref_conds=ref_conds,
-        generator=torch.Generator(device="cpu").manual_seed(seed),
-        true_cfg_scale=true_cfg,
-        true_cfg_start_step=cfg_start_step,
-        true_cfg_end_step=cfg_end_step,
-        negative_prompt=neg_prompt,
-        neg_guidance_scale=neg_guidance,
-        first_step_guidance_scale=first_step_guidance if first_step_guidance > 0 else guidance,
-    ).images[0]
-
-    return image, debug_images, seed
-
-
-# Video generation functions
-import requests
-import random
-import tempfile
-import subprocess
-from gradio_client import Client, handle_file
-
-REMOTE_ENDPOINT = os.getenv("H100_URL") 
-
-client = Client(REMOTE_ENDPOINT)
-
-def run_process_video_api(image_path: str, prompt: str, video_length: float = 2.0):
-    seed_val = random.randint(0, 9999999)
-    negative_prompt = ""
-    use_teacache = True
-
-    result = client.predict(
-        input_image=handle_file(image_path),
-        prompt=prompt,
-        n_prompt=negative_prompt,
-        seed=seed_val,
-        use_teacache=use_teacache,
-        video_length=video_length,
-        api_name="/process",
-    )
-    video_dict, preview_dict, md_text, html_text = result
-    video_path = video_dict.get("video") if isinstance(video_dict, dict) else None
-    return video_path
-
-def add_watermark_to_video(input_video_path: str, watermark_text="Ginigen.com") -> str:
-    if not os.path.exists(input_video_path):
-        raise FileNotFoundError(f"Input video not found: {input_video_path}")
-
-    base, ext = os.path.splitext(input_video_path)
-    watermarked_path = base + "_wm" + ext
-    cmd = [
-        "ffmpeg", "-y",
-        "-i", input_video_path,
-        "-vf", f"drawtext=fontsize=20:fontcolor=white:text='{watermark_text}':x=w-tw-10:y=h-th-10:box=1:[email protected]:boxborderw=5",
-        "-codec:a", "copy",
-        watermarked_path
-    ]
-    try:
-        subprocess.run(cmd, check=True)
-    except Exception as e:
-        print(f"[WARN] FFmpeg watermark failed: {e}")
-        return input_video_path
-
-    return watermarked_path
-
-def generate_video_from_image(image_array: np.ndarray):
-    if image_array is None:
-        raise gr.Error("이미지가 없습니다.")
-
-    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as fp:
-        temp_img_path = fp.name
-        Image.fromarray(image_array).save(temp_img_path, format="PNG")
-
-    default_video_prompt = "Generate a video with smooth and natural movement. Objects should have visible motion while maintaining fluid transitions."
-    result_video_path = run_process_video_api(
-        image_path=temp_img_path,
-        prompt=default_video_prompt,
-        video_length=2.0,
-    )
-    if result_video_path is None:
-        raise gr.Error("영상 API 호출 실패 또는 결과 없음")
-
-    final_video = add_watermark_to_video(result_video_path, watermark_text="Ginigen.com")
-    return final_video
-
-
-# Text-to-Image functions
-def test_text2img_api_connection() -> str:
-    """Text-to-Image API 서버 연결 테스트"""
-    try:
-        client = Client(TEXT2IMG_API_URL)
-        return "API 연결 성공: 정상 작동 중"
-    except Exception as e:
-        logging.error(f"API connection test failed: {e}")
-        return f"API 연결 실패: {e}"
-
-def generate_text_to_image(prompt: str, width: int, height: int, guidance: float, inference_steps: int, seed: int) -> tuple:
-    """텍스트를 이미지로 생성하는 함수"""
-    if not prompt:
-        return None, "오류: 프롬프트를 입력해주세요"
-    
-    try:
-        client = Client(TEXT2IMG_API_URL)
-        result = client.predict(
-            prompt=prompt,
-            width=int(width),
-            height=int(height),
-            guidance=float(guidance),
-            inference_steps=int(inference_steps),
-            seed=int(seed),
-            do_img2img=False,
-            init_image=None,
-            image2image_strength=0.8,
-            resize_img=True,
-            api_name="/generate_image"
-        )
-        return result[0], f"사용된 시드: {result[1]}"
-    except Exception as e:
-        logging.error(f"Image generation failed: {str(e)}")
-        return None, f"오류: {str(e)}"
-
-# Image size presets
-IMAGE_PRESETS = {
-    "커스텀": {"width": 1024, "height": 1024, "label": "커스텀 크기"},
-    "1:1 정사각형": {"width": 1024, "height": 1024, "label": "1:1 (정사각형)"},
-    "4:3 표준": {"width": 1024, "height": 768, "label": "4:3 (표준)"},
-    "16:9 와이드스크린": {"width": 1024, "height": 576, "label": "16:9 (와이드스크린)"},
-    "9:16 세로형": {"width": 576, "height": 1024, "label": "9:16 (세로형)"},
-    "6:19 특수 세로형": {"width": 324, "height": 1024, "label": "6:19 (특수 세로형)"},
-    "Instagram 정사각형": {"width": 1080, "height": 1080, "label": "Instagram 정사각형 (1:1)"},
-    "Instagram 스토리": {"width": 1080, "height": 1920, "label": "Instagram 스토리 (9:16)"},
-    "Instagram 가로형": {"width": 1080, "height": 566, "label": "Instagram 가로형 (1.91:1)"},
-    "Facebook 커버": {"width": 820, "height": 312, "label": "Facebook 커버 (2.63:1)"},
-    "Twitter 헤더": {"width": 1500, "height": 500, "label": "Twitter 헤더 (3:1)"},
-    "YouTube 썸네일": {"width": 1280, "height": 720, "label": "YouTube 썸네일 (16:9)"},
-    "LinkedIn 배너": {"width": 1584, "height": 396, "label": "LinkedIn 배너 (4:1)"},
-}
-
-def update_dimensions(preset):
-    """선택된 프리셋에 따라 width, height 업데이트"""
-    if preset in IMAGE_PRESETS:
-        return IMAGE_PRESETS[preset]["width"], IMAGE_PRESETS[preset]["height"]
-    return 1024, 1024
-
-
-# Custom CSS
-_CUSTOM_CSS_ = """
-:root {
-    --primary-color: #f8c3cd;
-    --secondary-color: #b3e5fc;
-    --background-color: #f5f5f7;
-    --card-background: #ffffff;
-    --text-color: #424242;
-    --accent-color: #ffb6c1;
-    --success-color: #c8e6c9;
-    --warning-color: #fff9c4;
-    --shadow-color: rgba(0, 0, 0, 0.1);
-    --border-radius: 12px;
-}
-
-body {
-    background-color: var(--background-color) !important;
-    font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif !important;
-}
-
-.gradio-container {
-    max-width: 1200px !important;
-    margin: 0 auto !important;
-}
-
-h1 {
-    color: #9c27b0 !important;
-    font-weight: 800 !important;
-    text-shadow: 2px 2px 4px rgba(156, 39, 176, 0.2) !important;
-    letter-spacing: -0.5px !important;
-}
-
-.panel-box {
-    border-radius: var(--border-radius) !important;
-    box-shadow: 0 8px 16px var(--shadow-color) !important;
-    background-color: var(--card-background) !important;
-    border: none !important;
-    overflow: hidden !important;
-    padding: 20px !important;
-    margin-bottom: 20px !important;
-}
-
-button.gr-button {
-    background: linear-gradient(135deg, var(--primary-color), #e1bee7) !important;
-    border-radius: var(--border-radius) !important;
-    color: #4a148c !important;
-    font-weight: 600 !important;
-    border: none !important;
-    padding: 10px 20px !important;
-    transition: all 0.3s ease !important;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1) !important;
-}
-
-button.gr-button:hover {
-    transform: translateY(-2px) !important;
-    box-shadow: 0 6px 10px rgba(0, 0, 0, 0.15) !important;
-    background: linear-gradient(135deg, #e1bee7, var(--primary-color)) !important;
-}
-
-input, select, textarea, .gr-input {
-    border-radius: 8px !important;
-    border: 2px solid #e0e0e0 !important;
-    padding: 10px 15px !important;
-    transition: all 0.3s ease !important;
-    background-color: #fafafa !important;
-}
-
-input:focus, select:focus, textarea:focus, .gr-input:focus {
-    border-color: var(--primary-color) !important;
-    box-shadow: 0 0 0 3px rgba(248, 195, 205, 0.3) !important;
-}
-
-.gr-form input[type=range] {
-    appearance: none !important;
-    width: 100% !important;
-    height: 6px !important;
-    background: #e0e0e0 !important;
-    border-radius: 5px !important;
-    outline: none !important;
-}
-
-.gr-form input[type=range]::-webkit-slider-thumb {
-    appearance: none !important;
-    width: 16px !important;
-    height: 16px !important;
-    background: var(--primary-color) !important;
-    border-radius: 50% !important;
-    cursor: pointer !important;
-    border: 2px solid white !important;
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1) !important;
-}
-
-.gr-form select {
-    background-color: white !important;
-    border: 2px solid #e0e0e0 !important;
-    border-radius: 8px !important;
-    padding: 10px 15px !important;
-}
-
-.gr-image-input {
-    border: 2px dashed #b39ddb !important;
-    border-radius: var(--border-radius) !important;
-    background-color: #f3e5f5 !important;
-    padding: 20px !important;
-    display: flex !important;
-    flex-direction: column !important;
-    align-items: center !important;
-    justify-content: center !important;
-    transition: all 0.3s ease !important;
-}
-
-.gr-image-input:hover {
-    background-color: #ede7f6 !important;
-    border-color: #9575cd !important;
-}
-
-body::before {
-    content: "" !important;
-    position: fixed !important;
-    top: 0 !important;
-    left: 0 !important;
-    width: 100% !important;
-    height: 100% !important;
-    background: 
-        radial-gradient(circle at 10% 20%, rgba(248, 195, 205, 0.1) 0%, rgba(245, 245, 247, 0) 20%),
-        radial-gradient(circle at 80% 70%, rgba(179, 229, 252, 0.1) 0%, rgba(245, 245, 247, 0) 20%) !important;
-    pointer-events: none !important;
-    z-index: -1 !important;
-}
-
-.gr-gallery {
-    grid-gap: 15px !important;
-}
-
-.gr-gallery-item {
-    border-radius: var(--border-radius) !important;
-    overflow: hidden !important;
-    box-shadow: 0 4px 8px var(--shadow-color) !important;
-    transition: transform 0.3s ease !important;
-}
-
-.gr-gallery-item:hover {
-    transform: scale(1.02) !important;
-}
-
-.gr-form label {
-    font-weight: 600 !important;
-    color: #673ab7 !important;
-    margin-bottom: 5px !important;
-}
-
-.gr-padded {
-    padding: 20px !important;
-}
-
-.gr-compact {
-    gap: 15px !important;
-}
-
-.gr-form > div {
-    margin-bottom: 16px !important;
-}
-
-.gr-form h3 {
-    color: #7b1fa2 !important;
-    margin-top: 5px !important;
-    margin-bottom: 15px !important;
-    border-bottom: 2px solid #e1bee7 !important;
-    padding-bottom: 8px !important;
-}
-
-#examples-panel {
-    background-color: #f3e5f5 !important;
-    border-radius: var(--border-radius) !important;
-    padding: 15px !important;
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.05) !important;
-}
-
-#examples-panel h2 {
-    color: #7b1fa2 !important;
-    font-size: 1.5rem !important;
-    margin-bottom: 15px !important;
-}
-
-.gr-accordion {
-    border: 1px solid #e0e0e0 !important;
-    border-radius: var(--border-radius) !important;
-    overflow: hidden !important;
-}
-
-.gr-accordion summary {
-    padding: 12px 16px !important;
-    background-color: #f9f9f9 !important;
-    cursor: pointer !important;
-    font-weight: 600 !important;
-    color: #673ab7 !important;
-}
-
-#generate-btn, #text2img-generate-btn {
-    background: linear-gradient(135deg, #ff9a9e, #fad0c4) !important;
-    font-size: 1.1rem !important;
-    padding: 12px 24px !important;
-    margin-top: 10px !important;
-    margin-bottom: 15px !important;
-    width: 100% !important;
-}
-
-#generate-btn:hover, #text2img-generate-btn:hover {
-    background: linear-gradient(135deg, #fad0c4, #ff9a9e) !important;
-}
-
-/* Tab styling */
-.gr-tabs {
-    border: none !important;
-    margin-top: 20px !important;
-}
-
-.gr-tab {
-    background-color: #f3e5f5 !important;
-    border: none !important;
-    padding: 12px 24px !important;
-    font-weight: 600 !important;
-    color: #673ab7 !important;
-    transition: all 0.3s ease !important;
-}
-
-.gr-tab.selected {
-    background: linear-gradient(135deg, var(--primary-color), #e1bee7) !important;
-    color: white !important;
-}
-
-.gr-tab:hover {
-    background-color: #ede7f6 !important;
-}
-"""
-
-_HEADER_ = '''
-<div style="text-align: center; max-width: 850px; margin: 0 auto; padding: 25px 0;">
-    <div style="background: linear-gradient(135deg, #f8c3cd, #e1bee7, #b3e5fc); color: white; padding: 15px; border-radius: 15px; box-shadow: 0 10px 20px rgba(0,0,0,0.1); margin-bottom: 20px;">
-        <h1 style="font-size: 3rem; font-weight: 800; margin: 0; color: white; text-shadow: 2px 2px 4px rgba(0,0,0,0.2);">✨ DreamO Video ✨</h1>
-        <p style="font-size: 1.2rem; margin: 10px 0 0;">Create customized images with advanced AI</p>
-    </div>
-
-    <div style="background: white; padding: 15px; border-radius: 12px; box-shadow: 0 5px 15px rgba(0,0,0,0.05);">
-        <p style="font-size: 1rem; margin: 0;">In the current demo version, due to ZeroGPU limitations, video generation is restricted to 2 seconds only. (The full version supports generation of up to 60 seconds)</p>
-    </div>
-
-</div>
-
-<div style="background: #fff9c4; padding: 15px; border-radius: 12px; margin-bottom: 20px; border-left: 5px solid #ffd54f; box-shadow: 0 5px 15px rgba(0,0,0,0.05);">
-    <h3 style="margin-top: 0; color: #ff6f00;">🚩 Update Notes:</h3>
-    <ul style="margin-bottom: 0; padding-left: 20px;">
-        <li><b>2025.05.11:</b> We have updated the model to mitigate over-saturation and plastic-face issues. The new version shows consistent improvements over the previous release.</li>
-        <li><b>2025.05.13:</b> 'DreamO Video' Integration version Release</li>
-        <li><b>2025.05.28:</b> Added 'Text-to-Image' tab with multiple aspect ratios and SNS presets</li>
-    </ul>
-</div>
-'''
-
-_CITE_ = r"""
-<div style="background: white; padding: 20px; border-radius: 12px; margin-top: 20px; box-shadow: 0 5px 15px rgba(0,0,0,0.05);">
-    <p style="margin: 0; font-size: 1.1rem;">If DreamO is helpful, please help to ⭐ the <a href='https://discord.gg/openfreeai' target='_blank' style="color: #9c27b0; font-weight: 600;">community</a>. Thanks!</p>
-    <hr style="border: none; height: 1px; background-color: #e0e0e0; margin: 15px 0;">
-    <h4 style="margin: 0 0 10px; color: #7b1fa2;">📧 Contact</h4>
-    <p style="margin: 0;">If you have any questions or feedback, feel free to open a discussion or contact <b>[email protected]</b></p>
-</div>
-"""
-
-def create_demo():
-    with gr.Blocks(css=_CUSTOM_CSS_) as demo:
-        gr.HTML(_HEADER_)
-
-        with gr.Tabs():
-            # DreamO Tab
-            with gr.Tab("DreamO (참조 이미지 기반)"):
-                with gr.Row():
-                    with gr.Column(scale=6):
-                        with gr.Group(elem_id="input-panel", elem_classes="panel-box"):
-                            gr.Markdown("### 📸 Reference Images")
-                            with gr.Row():
-                                with gr.Column():
-                                    ref_image1 = gr.Image(label="Reference Image 1", type="numpy", height=256, elem_id="ref-image-1")
-                                    ref_task1 = gr.Dropdown(choices=["ip", "id", "style"], value="ip", label="Task for Reference Image 1", elem_id="ref-task-1")
-                                
-                                with gr.Column():
-                                    ref_image2 = gr.Image(label="Reference Image 2", type="numpy", height=256, elem_id="ref-image-2")
-                                    ref_task2 = gr.Dropdown(choices=["ip", "id", "style"], value="ip", label="Task for Reference Image 2", elem_id="ref-task-2")
-                            
-                            gr.Markdown("### ✏️ Generation Parameters")
-                            prompt = gr.Textbox(label="Prompt", value="a person playing guitar in the street", elem_id="prompt-input")
-                            
-                            with gr.Row():
-                                width = gr.Slider(768, 1024, 1024, step=16, label="Width", elem_id="width-slider")
-                                height = gr.Slider(768, 1024, 1024, step=16, label="Height", elem_id="height-slider")
-                            
-                            with gr.Row():
-                                num_steps = gr.Slider(8, 30, 12, step=1, label="Number of Steps", elem_id="steps-slider")
-                                guidance = gr.Slider(1.0, 10.0, 3.5, step=0.1, label="Guidance Scale", elem_id="guidance-slider")
-                            
-                            seed = gr.Textbox(label="Seed (-1 for random)", value="-1", elem_id="seed-input")
-                            
-                            with gr.Accordion("Advanced Options", open=False):
-                                ref_res = gr.Slider(512, 1024, 512, step=16, label="Resolution for Reference Image")
-                                neg_prompt = gr.Textbox(label="Negative Prompt", value="")
-                                neg_guidance = gr.Slider(1.0, 10.0, 3.5, step=0.1, label="Negative Guidance")
-                                
-                                with gr.Row():
-                                    true_cfg = gr.Slider(1, 5, 1, step=0.1, label="True CFG")
-                                    first_step_guidance = gr.Slider(0, 10, 0, step=0.1, label="First Step Guidance")
-                                
-                                with gr.Row():
-                                    cfg_start_step = gr.Slider(0, 30, 0, step=1, label="CFG Start Step")
-                                    cfg_end_step = gr.Slider(0, 30, 0, step=1, label="CFG End Step")
-                            
-                            generate_btn = gr.Button("✨ Generate Image", elem_id="generate-btn")
-                            gr.HTML(_CITE_)
-
-                    with gr.Column(scale=6):
-                        with gr.Group(elem_id="output-panel", elem_classes="panel-box"):
-                            gr.Markdown("### 🖼️ Generated Result")
-                            output_image = gr.Image(label="Generated Image", elem_id="output-image", format='png')
-                            seed_output = gr.Textbox(label="Used Seed", elem_id="seed-output")
-                            
-                            generate_video_btn = gr.Button("🎬 Generate Video from Image")
-                            output_video = gr.Video(label="Generated Video", elem_id="video-output")
-
-                            gr.Markdown("### 🔍 Preprocessing")
-                            debug_image = gr.Gallery(
-                                label="Preprocessing Results (including face crop and background removal)",
-                                elem_id="debug-gallery",
-                            )
-
-                with gr.Group(elem_id="examples-panel", elem_classes="panel-box"):
-                    gr.Markdown("## 📚 Examples")
-                    example_inps = [
-                        [
-                            'example_inputs/choi.jpg',
-                            None,
-                            'ip',
-                            'ip',
-                            'a woman sitting on the cloud, playing guitar',
-                            1206523688721442817,
-                        ],
-                        [
-                            'example_inputs/choi.jpg',
-                            None,
-                            'id',
-                            'ip',
-                            'a woman holding a sign saying "TOP", on the mountain',
-                            10441727852953907380,
-                        ],
-                        [
-                            'example_inputs/perfume.png',
-                            None,
-                            'ip',
-                            'ip',
-                            'a perfume under spotlight',
-                            116150031980664704,
-                        ],
-                        [
-                            'example_inputs/choi.jpg',
-                            None,
-                            'id',
-                            'ip',
-                            'portrait, in alps',
-                            5443415087540486371,
-                        ],
-                        [
-                            'example_inputs/mickey.png',
-                            None,
-                            'style',
-                            'ip',
-                            'generate a same style image. A rooster wearing overalls.',
-                            6245580464677124951,
-                        ],
-                        [
-                            'example_inputs/mountain.png',
-                            None,
-                            'style',
-                            'ip',
-                            'generate a same style image. A pavilion by the river, and the distant mountains are endless',
-                            5248066378927500767,
-                        ],
-                        [
-                            'example_inputs/shirt.png',
-                            'example_inputs/skirt.jpeg',
-                            'ip',
-                            'ip',
-                            'A girl is wearing a short-sleeved shirt and a short skirt on the beach.',
-                            9514069256241143615,
-                        ],
-                        [
-                            'example_inputs/woman2.png',
-                            'example_inputs/dress.png',
-                            'id',
-                            'ip',
-                            'the woman wearing a dress, In the banquet hall',
-                            7698454872441022867,
-                        ],
-                        [
-                            'example_inputs/dog1.png',
-                            'example_inputs/dog2.png',
-                            'ip',
-                            'ip',
-                            'two dogs in the jungle',
-                            6187006025405083344,
-                        ],
-                    ]
-                    gr.Examples(
-                        examples=example_inps,
-                        inputs=[ref_image1, ref_image2, ref_task1, ref_task2, prompt, seed],
-                        label='Examples by category: IP task (rows 1-4), ID task (row 5), Style task (rows 6-7), Try-On task (rows 8-9)',
-                        cache_examples='lazy',
-                        outputs=[output_image, debug_image, seed_output],
-                        fn=generate_image,
-                    )
-
-                # Event handlers for DreamO tab
-                generate_btn.click(
-                    fn=generate_image,
-                    inputs=[
-                        ref_image1,
-                        ref_image2,
-                        ref_task1,
-                        ref_task2,
-                        prompt,
-                        seed,
-                        width,
-                        height,
-                        ref_res,
-                        num_steps,
-                        guidance,
-                        true_cfg,
-                        cfg_start_step,
-                        cfg_end_step,
-                        neg_prompt,
-                        neg_guidance,
-                        first_step_guidance,
-                    ],
-                    outputs=[output_image, debug_image, seed_output],
-                )
-
-                def on_click_generate_video(img):
-                    if img is None:
-                        raise gr.Error("먼저 이미지를 생성해주세요.")
-                    video_path = generate_video_from_image(img)
-                    return video_path
-
-                generate_video_btn.click(
-                    fn=on_click_generate_video,
-                    inputs=[output_image],
-                    outputs=[output_video],
-                )
-
-            # Text-to-Image Tab
-            with gr.Tab("텍스트 to 이미지"):
-                with gr.Row():
-                    with gr.Column(scale=6):
-                        with gr.Group(elem_id="text2img-input-panel", elem_classes="panel-box"):
-                            gr.Markdown("### 📝 텍스트로 이미지 생성")
-                            
-                            # API 상태 표시
-                            text2img_status = gr.Textbox(
-                                label="API 상태",
-                                value="API 연결 확인 중...",
-                                interactive=False
-                            )
-                            
-                            # 프롬프트 입력
-                            text2img_prompt = gr.Textbox(
-                                label="프롬프트",
-                                placeholder="생성하고 싶은 이미지를 설명하세요...",
-                                lines=3
-                            )
-                            
-                            # 이미지 크기 프리셋
-                            size_preset = gr.Dropdown(
-                                choices=list(IMAGE_PRESETS.keys()),
-                                value="1:1 정사각형",
-                                label="이미지 크기 프리셋",
-                                interactive=True
-                            )
-                            
-                            with gr.Row():
-                                text2img_width = gr.Slider(
-                                    minimum=256,
-                                    maximum=2048,
-                                    value=1024,
-                                    step=64,
-                                    label="너비"
-                                )
-                                
-                                text2img_height = gr.Slider(
-                                    minimum=256,
-                                    maximum=2048,
-                                    value=1024,
-                                    step=64,
-                                    label="높이"
-                                )
-                            
-                            with gr.Row():
-                                text2img_guidance = gr.Slider(
-                                    minimum=1.0,
-                                    maximum=20.0,
-                                    value=3.5,
-                                    step=0.1,
-                                    label="가이던스 스케일"
-                                )
-                                
-                                text2img_steps = gr.Slider(
-                                    minimum=1,
-                                    maximum=50,
-                                    value=30,
-                                    step=1,
-                                    label="인퍼런스 스텝"
-                                )
-                            
-                            text2img_seed = gr.Number(
-                                label="시드 (-1: 랜덤)",
-                                value=-1,
-                                precision=0
-                            )
-                            
-                            text2img_generate_btn = gr.Button("✨ 이미지 생성", elem_id="text2img-generate-btn")
-                            
-                            # 생성 상태 표시
-                            text2img_generation_status = gr.Textbox(
-                                label="생성 상태",
-                                value="",
-                                interactive=False,
-                                visible=False
-                            )
-
-                    with gr.Column(scale=6):
-                        with gr.Group(elem_id="text2img-output-panel", elem_classes="panel-box"):
-                            gr.Markdown("### 🖼️ 생성 결과")
-                            text2img_output = gr.Image(label="생성된 이미지", format='png')
-                            text2img_used_seed = gr.Textbox(label="사용된 시드")
-                            
-                            # 비디오 생성 버튼
-                            text2img_video_btn = gr.Button("🎬 이미지를 비디오로 변환")
-                            text2img_video = gr.Video(label="생성된 비디오")
-
-                # Text-to-Image 탭 예제
-                with gr.Group(elem_id="text2img-examples-panel", elem_classes="panel-box"):
-                    gr.Markdown("## 📚 텍스트 to 이미지 예제")
-                    text2img_examples = [
-                        ["A serene Japanese garden with cherry blossoms", "1:1 정사각형", 3.5, 30, 42],
-                        ["Futuristic cityscape at sunset, cyberpunk style", "16:9 와이드스크린", 4.0, 35, 123],
-                        ["Portrait of a mysterious woman with flowing hair", "Instagram 스토리", 3.0, 25, 789],
-                        ["Epic fantasy dragon breathing fire", "YouTube 썸네일", 5.0, 40, 456],
-                        ["Minimalist logo design for tech company", "LinkedIn 배너", 3.5, 30, 321],
-                    ]
-                    gr.Examples(
-                        examples=text2img_examples,
-                        inputs=[text2img_prompt, size_preset, text2img_guidance, text2img_steps, text2img_seed],
-                        label='예제 프롬프트와 설정',
-                        cache_examples=False,
-                    )
-
-                # Event handlers for Text-to-Image tab
-                size_preset.change(
-                    fn=update_dimensions,
-                    inputs=[size_preset],
-                    outputs=[text2img_width, text2img_height]
-                )
-
-                def on_text2img_generate_click():
-                    text2img_generation_status.visible = True
-                    text2img_generation_status.value = "이미지 생성 중... 잠시만 기다려주세요"
-                    return text2img_generation_status
-
-                def on_text2img_generate_complete():
-                    text2img_generation_status.value = "이미지 생성 완료!"
-                    return text2img_generation_status
-
-                text2img_generate_btn.click(
-                    fn=on_text2img_generate_click,
-                    outputs=[text2img_generation_status]
-                ).then(
-                    fn=generate_text_to_image,
-                    inputs=[text2img_prompt, text2img_width, text2img_height, text2img_guidance, text2img_steps, text2img_seed],
-                    outputs=[text2img_output, text2img_used_seed]
-                ).then(
-                    fn=on_text2img_generate_complete,
-                    outputs=[text2img_generation_status]
-                )
-
-                def on_text2img_video_click(img):
-                    if img is None:
-                        raise gr.Error("먼저 이미지를 생성해주세요.")
-                    video_path = generate_video_from_image(img)
-                    return video_path
-
-                text2img_video_btn.click(
-                    fn=on_text2img_video_click,
-                    inputs=[text2img_output],
-                    outputs=[text2img_video],
-                )
-
-                # API 상태 확인
-                def check_text2img_api_status():
-                    return test_text2img_api_connection()
-
-                demo.load(
-                    fn=check_text2img_api_status,
-                    outputs=[text2img_status]
-                )
-
-    return demo
-
-
-if __name__ == '__main__':
-    demo = create_demo()
-    demo.launch(
-        server_name="0.0.0.0",
-        share=True,
-        ssr_mode=False
-    )