Update app.py

app.py

@@ -153,7 +153,7 @@ def generate_image(
 
 
 # -----------------------------
-# (1) 여기에 영상 API 호출을 위한 추가 코드
+# 영상 API 호출을 위한 추가 코드
 # -----------------------------
 import requests
 import random
@@ -161,7 +161,7 @@ import tempfile
 import subprocess
 from gradio_client import Client, handle_file
 
-# 예시: 원격 서버 Endpoint (필요하다면 수정)
+# 원격 서버 Endpoint
 REMOTE_ENDPOINT = os.getenv("H100_URL") 
 
 client = Client(REMOTE_ENDPOINT)
@@ -169,7 +169,6 @@ client = Client(REMOTE_ENDPOINT)
 def run_process_video_api(image_path: str, prompt: str, video_length: float = 2.0):
     """
     원격 /process 엔드포인트 호출하여 영상을 생성.
-    (예시: prompt, negative_prompt, seed 등은 하드코딩하거나 원하는대로 조정 가능)
     """
     # 랜덤 시드
     seed_val = random.randint(0, 9999999)
@@ -605,7 +604,7 @@ def create_demo():
                     output_image = gr.Image(label="Generated Image", elem_id="output-image", format='png')
                     seed_output = gr.Textbox(label="Used Seed", elem_id="seed-output")
                     
-                    # (2) 영상 생성 버튼 & 출력 영역 추가
+                    # 영상 생성 버튼 & 출력 영역
                     generate_video_btn = gr.Button("🎬 Generate Video from Image")
                     output_video = gr.Video(label="Generated Video", elem_id="video-output")
 
@@ -700,7 +699,7 @@ def create_demo():
                 fn=generate_image,
             )
 
-        # 기존 이미지 생성 함수와 연결
+        # 이미지 생성 함수와 연결
         generate_btn.click(
             fn=generate_image,
             inputs=[
@@ -725,756 +724,7 @@ def create_demo():
             outputs=[output_image, debug_image, seed_output],
         )
 
-        # (3) 영상 생성 버튼 클릭 -> generate_video_from_image() 호출
-        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],
-        )
-
-    return demo
-
-
-if __name__ == '__main__':
-    demo = create_demo()
-    demo.launch(
-        server_name="0.0.0.0",
-        share=True,
-        ssr_mode=False
-    )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 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'))
-
-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
-
-
-# -----------------------------
-# (1) 여기에 영상 API 호출을 위한 추가 코드
-# -----------------------------
-import requests
-import random
-import tempfile
-import subprocess
-from gradio_client import Client, handle_file
-
-# 예시: 원격 서버 Endpoint (필요하다면 수정)
-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):
-    """
-    원격 /process 엔드포인트 호출하여 영상을 생성.
-    (예시: prompt, negative_prompt, seed 등은 하드코딩하거나 원하는대로 조정 가능)
-    """
-    # 랜덤 시드
-    seed_val = random.randint(0, 9999999)
-    # negative_prompt = "" 등 고정
-    negative_prompt = ""
-    use_teacache = True
-
-    # /process 호출 (gradio_client)
-    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",
-    )
-    # result는 (video_dict, preview_dict, md_text, html_text) 구조
-    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:
-    """
-    FFmpeg로 영상에 오른쪽 하단 워터마크를 추가한 새 영상을 리턴
-    """
-    if not os.path.exists(input_video_path):
-        raise FileNotFoundError(f"Input video not found: {input_video_path}")
-
-    # 출력 경로
-    base, ext = os.path.splitext(input_video_path)
-    watermarked_path = base + "_wm" + ext
-    # ffmpeg 명령어 구성
-    # - y: 덮어쓰기
-    # drawtext 필터로 오른쪽 하단(x=w-tw-10, y=h-th-10)에 boxcolor=black 반투명 박스
-    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:boxcolor=black@0.5: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  # 실패 시 원본 반환
-
-    return watermarked_path
-
-def generate_video_from_image(image_array: np.ndarray):
-    """
-    1) Numpy 이미지를 임시 파일로 저장
-    2) 원격 API로 2초 영상 생성 (기본 prompt 고정)
-    3) FFmpeg로 'Ginigen.com' 워터마크 추가
-    4) 최종 mp4 경로 반환
-    """
-    if image_array is None:
-        raise gr.Error("이미지가 없습니다.")
-
-    # (1) 임시 파일로 저장
-    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as fp:
-        temp_img_path = fp.name
-        Image.fromarray(image_array).save(temp_img_path, format="PNG")
-
-    # (2) 원격 API 호출
-    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")
-
-    # (3) FFmpeg 워터마크 추가
-    final_video = add_watermark_to_video(result_video_path, watermark_text="Ginigen.com")
-    return final_video
-
-
-# -----------------------------
-# Custom CSS, Headers, etc.
-# -----------------------------
-_CUSTOM_CSS_ = """
-:root {
-    --primary-color: #f8c3cd;            /* Sakura pink - primary accent */
-    --secondary-color: #b3e5fc;          /* Pastel blue - secondary accent */
-    --background-color: #f5f5f7;         /* Very light gray background */
-    --card-background: #ffffff;          /* White for cards */
-    --text-color: #424242;               /* Dark gray for text */
-    --accent-color: #ffb6c1;             /* Light pink for accents */
-    --success-color: #c8e6c9;            /* Pastel green for success */
-    --warning-color: #fff9c4;            /* Pastel yellow for warnings */
-    --shadow-color: rgba(0, 0, 0, 0.1);  /* Shadow color */
-    --border-radius: 12px;               /* Rounded corners */
-}
-
-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;
-    padding-top: 0 !important;
-}
-
-/* Remove any default margins that might push content up */
-#component-0 {
-    margin-top: 0 !important;
-    padding-top: 0 !important;
-}
-
-/* Ensure the main container starts from the top */
-.main {
-    margin-top: 0 !important;
-    padding-top: 10px !important;
-}
-
-/* Header styling */
-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;
-}
-
-/* Card styling for panels */
-.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 styling */
-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 fields styling */
-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;
-}
-
-/* Slider styling */
-.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;
-}
-
-/* Dropdown styling */
-.gr-form select {
-    background-color: white !important;
-    border: 2px solid #e0e0e0 !important;
-    border-radius: 8px !important;
-    padding: 10px 15px !important;
-}
-
-.gr-form select option {
-    padding: 10px !important;
-}
-
-/* Image upload area */
-.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;
-}
-
-/* Remove the background pattern that might interfere with visibility */
-body::before {
-    display: none !important;
-}
-
-/* Gallery styling */
-.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;
-}
-
-/* Label styling */
-.gr-form label {
-    font-weight: 600 !important;
-    color: #673ab7 !important;
-    margin-bottom: 5px !important;
-}
-
-/* Improve spacing */
-.gr-padded {
-    padding: 20px !important;
-}
-
-.gr-compact {
-    gap: 15px !important;
-}
-
-.gr-form > div {
-    margin-bottom: 16px !important;
-}
-
-/* Headings */
-.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 section */
-#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;
-}
-
-/* Accordion styling */
-.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 button special styling */
-#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 {
-    background: linear-gradient(135deg, #fad0c4, #ff9a9e) !important;
-}
-
-/* Ensure proper scrolling behavior */
-html {
-    scroll-behavior: smooth !important;
-}
-
-/* Fix any overflow issues that might hide content */
-.contain {
-    overflow: visible !important;
-}
-
-/* Additional fixes for header visibility */
-.header-wrap {
-    position: relative !important;
-    margin-top: 0 !important;
-}
-
-/* Ensure the first element is visible */
-.gradio-container > :first-child {
-    margin-top: 0 !important;
-    padding-top: 10px !important;
-}
-"""
-
-_HEADER_ = '''
-<div style="text-align: center; max-width: 850px; margin: 0 auto; padding: 20px 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>
-    </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>arxivgpt@gmail.com</b></p>
-</div>
-"""
-
-def create_demo():
-    with gr.Blocks(css=_CUSTOM_CSS_) as demo:
-        gr.HTML(_HEADER_)
-
-        gr.HTML(
-            """
-            <div class='container' style='display:flex; justify-content:center; gap:12px; margin-bottom: 20px;'>
-                <a href="https://huggingface.co/spaces/openfree/Best-AI" target="_blank">
-                    <img src="https://img.shields.io/static/v1?label=OpenFree&message=BEST%20AI%20Services&color=%230000ff&labelColor=%23000080&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="OpenFree badge">
-                </a>
-        
-                <a href="https://discord.gg/openfreeai" target="_blank">
-                    <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord badge">
-                </a>
-            </div>
-            """
-        )
-        
-        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")
-                    
-                    # (2) 영상 생성 버튼 & 출력 영역 추가
-                    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,
-            )
-
-        # 기존 이미지 생성 함수와 연결
-        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],
-        )
-
-        # (3) 영상 생성 버튼 클릭 -> generate_video_from_image() 호출
+        # 영상 생성 버튼 클릭 -> generate_video_from_image() 호출
         def on_click_generate_video(img):
             if img is None:
                 raise gr.Error("먼저 이미지를 생성해주세요.")