Update app.py

app.py

@@ -10,195 +10,817 @@ import numpy as np
 from PIL import Image
 import random
 
-MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-480P-Diffusers"
+# Updated MODEL_ID to FusionX
+MODEL_ID = "vrgamedevgirl84/Wan14BT2VFusioniX"
+
+# Optional fallback LoRA (if needed for additional enhancement)
 LORA_REPO_ID = "Kijai/WanVideo_comfy"
 LORA_FILENAME = "Wan21_CausVid_14B_T2V_lora_rank32.safetensors"
 
+# Load FusionX model components
 image_encoder = CLIPVisionModel.from_pretrained(MODEL_ID, subfolder="image_encoder", torch_dtype=torch.float32)
 vae = AutoencoderKLWan.from_pretrained(MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
 pipe = WanImageToVideoPipeline.from_pretrained(
     MODEL_ID, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16
 )
+
+# FusionX optimized scheduler settings
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=8.0)
 pipe.to("cuda")
 
-causvid_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)
-pipe.load_lora_weights(causvid_path, adapter_name="causvid_lora")
-pipe.set_adapters(["causvid_lora"], adapter_weights=[0.95])
-pipe.fuse_lora()
+# Optional: Load additional LoRA for extra enhancement (can be commented out if not needed)
+try:
+    causvid_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)
+    pipe.load_lora_weights(causvid_path, adapter_name="causvid_lora")
+    pipe.set_adapters(["causvid_lora"], adapter_weights=[0.5])  # Lower weight since CausVid is already merged
+    pipe.fuse_lora()
+    print("Additional CausVid LoRA loaded for extra enhancement")
+except Exception as e:
+    print(f"CausVid LoRA not loaded (FusionX already includes CausVid): {e}")
 
 MOD_VALUE = 32
-DEFAULT_H_SLIDER_VALUE = 320
-DEFAULT_W_SLIDER_VALUE = 560
-NEW_FORMULA_MAX_AREA = 480.0 * 832.0 
+DEFAULT_H_SLIDER_VALUE = 576  # FusionX optimized default
+DEFAULT_W_SLIDER_VALUE = 1024  # FusionX optimized default
+NEW_FORMULA_MAX_AREA = 576.0 * 1024.0  # Updated for FusionX
 
-SLIDER_MIN_H, SLIDER_MAX_H = 128, 896
-SLIDER_MIN_W, SLIDER_MAX_W = 128, 896
+SLIDER_MIN_H, SLIDER_MAX_H = 128, 1080
+SLIDER_MIN_W, SLIDER_MAX_W = 128, 1920
 MAX_SEED = np.iinfo(np.int32).max
 
 FIXED_FPS = 24
 MIN_FRAMES_MODEL = 8
-MAX_FRAMES_MODEL = 120
+MAX_FRAMES_MODEL = 121  # FusionX supports up to 121 frames
 
-default_prompt_i2v = "make this image come alive, cinematic motion, smooth animation"
-default_negative_prompt = "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards, watermark, text, signature"
+# Enhanced prompts for FusionX
+default_prompt_i2v = "Cinematic motion, smooth animation, detailed textures, dynamic lighting, professional cinematography"
+default_negative_prompt = "Static image, no motion, blurred details, overexposed, underexposed, low quality, worst quality, JPEG artifacts, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, watermark, text, signature"
 
-# CSS 스타일 정의
+# Enhanced CSS for FusionX theme
 custom_css = """
-/* 전체 배경 그라디언트 */
+/* Enhanced FusionX theme with cinematic styling */
 .gradio-container {
     font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif !important;
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 25%, #f093fb 50%, #f5576c 75%, #fa709a 100%) !important;
+    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 25%, #0f3460 50%, #533a7d 75%, #6a4c93 100%) !important;
     background-size: 400% 400% !important;
-    animation: gradientShift 15s ease infinite !important;
+    animation: cinematicShift 20s ease infinite !important;
 }
 
-@keyframes gradientShift {
+@keyframes cinematicShift {
     0% { background-position: 0% 50%; }
-    50% { background-position: 100% 50%; }
+    25% { background-position: 100% 50%; }
+    50% { background-position: 100% 100%; }
+    75% { background-position: 0% 100%; }
     100% { background-position: 0% 50%; }
 }
 
-/* 메인 컨테이너 스타일 */
+/* Main container with cinematic glass effect */
 .main-container {
-    backdrop-filter: blur(10px);
-    background: rgba(255, 255, 255, 0.1) !important;
-    border-radius: 20px !important;
-    padding: 30px !important;
-    box-shadow: 0 8px 32px 0 rgba(31, 38, 135, 0.37) !important;
-    border: 1px solid rgba(255, 255, 255, 0.18) !important;
+    backdrop-filter: blur(15px);
+    background: rgba(255, 255, 255, 0.08) !important;
+    border-radius: 25px !important;
+    padding: 35px !important;
+    box-shadow: 0 12px 40px 0 rgba(31, 38, 135, 0.4) !important;
+    border: 1px solid rgba(255, 255, 255, 0.15) !important;
+    position: relative;
+    overflow: hidden;
+}
+
+.main-container::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    bottom: 0;
+    background: linear-gradient(45deg, rgba(255,255,255,0.1) 0%, transparent 50%, rgba(255,255,255,0.05) 100%);
+    pointer-events: none;
 }
 
-/* 헤더 스타일 */
+/* Enhanced header with FusionX branding */
 h1 {
-    background: linear-gradient(45deg, #ffffff, #f0f0f0) !important;
+    background: linear-gradient(45deg, #ffffff, #f0f8ff, #e6e6fa) !important;
     -webkit-background-clip: text !important;
     -webkit-text-fill-color: transparent !important;
     background-clip: text !important;
-    font-weight: 800 !important;
-    font-size: 2.5rem !important;
+    font-weight: 900 !important;
+    font-size: 2.8rem !important;
     text-align: center !important;
-    margin-bottom: 2rem !important;
-    text-shadow: 2px 2px 4px rgba(0,0,0,0.1) !important;
+    margin-bottom: 2.5rem !important;
+    text-shadow: 2px 2px 8px rgba(0,0,0,0.3) !important;
+    position: relative;
 }
 
-/* 컴포넌트 컨테이너 스타일 */
+h1::after {
+    content: '🎬 FusionX Enhanced';
+    display: block;
+    font-size: 1rem;
+    color: #6a4c93;
+    margin-top: 0.5rem;
+    font-weight: 500;
+}
+
+/* Enhanced component containers */
 .input-container, .output-container {
-    background: rgba(255, 255, 255, 0.08) !important;
+    background: rgba(255, 255, 255, 0.06) !important;
+    border-radius: 20px !important;
+    padding: 25px !important;
+    margin: 15px 0 !important;
+    backdrop-filter: blur(10px) !important;
+    border: 1px solid rgba(255, 255, 255, 0.12) !important;
+    box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1) !important;
+}
+
+/* Cinematic input styling */
+input, textarea, .gr-box {
+    background: rgba(255, 255, 255, 0.95) !important;
+    border: 1px solid rgba(106, 76, 147, 0.3) !important;
+    border-radius: 12px !important;
+    color: #1a1a2e !important;
+    transition: all 0.4s ease !important;
+    box-shadow: 0 2px 8px rgba(106, 76, 147, 0.1) !important;
+}
+
+input:focus, textarea:focus {
+    background: rgba(255, 255, 255, 1) !important;
+    border-color: #6a4c93 !important;
+    box-shadow: 0 0 0 3px rgba(106, 76, 147, 0.15) !important;
+    transform: translateY(-1px) !important;
+}
+
+/* Enhanced FusionX button */
+.generate-btn {
+    background: linear-gradient(135deg, #6a4c93 0%, #533a7d 50%, #0f3460 100%) !important;
+    color: white !important;
+    font-weight: 700 !important;
+    font-size: 1.2rem !important;
+    padding: 15px 40px !important;
+    border-radius: 60px !important;
+    border: none !important;
+    cursor: pointer !important;
+    transition: all 0.4s ease !important;
+    box-shadow: 0 6px 20px rgba(106, 76, 147, 0.4) !important;
+    position: relative;
+    overflow: hidden;
+}
+
+.generate-btn::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: -100%;
+    width: 100%;
+    height: 100%;
+    background: linear-gradient(90deg, transparent, rgba(255,255,255,0.3), transparent);
+    transition: left 0.5s ease;
+}
+
+.generate-btn:hover::before {
+    left: 100%;
+}
+
+.generate-btn:hover {
+    transform: translateY(-3px) scale(1.02) !important;
+    box-shadow: 0 8px 25px rgba(106, 76, 147, 0.6) !important;
+}
+
+/* Enhanced slider styling */
+input[type="range"] {
+    background: transparent !important;
+}
+
+input[type="range"]::-webkit-slider-track {
+    background: linear-gradient(90deg, rgba(106, 76, 147, 0.3), rgba(83, 58, 125, 0.5)) !important;
+    border-radius: 8px !important;
+    height: 8px !important;
+}
+
+input[type="range"]::-webkit-slider-thumb {
+    background: linear-gradient(135deg, #6a4c93, #533a7d) !important;
+    border: 3px solid white !important;
+    border-radius: 50% !important;
+    cursor: pointer !important;
+    width: 22px !important;
+    height: 22px !important;
+    -webkit-appearance: none !important;
+    box-shadow: 0 2px 8px rgba(106, 76, 147, 0.3) !important;
+}
+
+/* Enhanced accordion */
+.gr-accordion {
+    background: rgba(255, 255, 255, 0.04) !important;
     border-radius: 15px !important;
-    padding: 20px !important;
-    margin: 10px 0 !important;
+    border: 1px solid rgba(255, 255, 255, 0.08) !important;
+    margin: 20px 0 !important;
     backdrop-filter: blur(5px) !important;
+}
+
+/* Enhanced labels */
+label {
+    color: #ffffff !important;
+    font-weight: 600 !important;
+    font-size: 1rem !important;
+    margin-bottom: 8px !important;
+    text-shadow: 1px 1px 2px rgba(0,0,0,0.5) !important;
+}
+
+/* Enhanced image upload */
+.image-upload {
+    border: 3px dashed rgba(106, 76, 147, 0.4) !important;
+    border-radius: 20px !important;
+    background: rgba(255, 255, 255, 0.03) !important;
+    transition: all 0.4s ease !important;
+    position: relative;
+}
+
+.image-upload:hover {
+    border-color: rgba(106, 76, 147, 0.7) !important;
+    background: rgba(255, 255, 255, 0.08) !important;
+    transform: scale(1.01) !important;
+}
+
+/* Enhanced video output */
+video {
+    border-radius: 20px !important;
+    box-shadow: 0 8px 30px rgba(0, 0, 0, 0.4) !important;
+    border: 2px solid rgba(106, 76, 147, 0.3) !important;
+}
+
+/* Enhanced examples section */
+.gr-examples {
+    background: rgba(255, 255, 255, 0.04) !important;
+    border-radius: 20px !important;
+    padding: 25px !important;
+    margin-top: 25px !important;
     border: 1px solid rgba(255, 255, 255, 0.1) !important;
 }
 
-/* 입력 필드 스타일 */
+/* Enhanced checkbox */
+input[type="checkbox"] {
+    accent-color: #6a4c93 !important;
+    transform: scale(1.2) !important;
+}
+
+/* Responsive enhancements */
+@media (max-width: 768px) {
+    h1 { font-size: 2.2rem !important; }
+    .main-container { padding: 25px !important; }
+    .generate-btn { padding: 12px 30px !important; font-size: 1.1rem !important; }
+}
+
+/* Badge container styling */
+.badge-container {
+    display: flex;
+    justify-content: center;
+    gap: 15px;
+    margin: 20px 0;
+    flex-wrap: wrap;
+}
+
+.badge-container img {
+    border-radius: 8px;
+    transition: transform 0.3s ease;
+}
+
+.badge-container img:hover {
+    transform: scale(1.05);
+}
+"""
+
+def _calculate_new_dimensions_wan(pil_image, mod_val, calculation_max_area,
+                                 min_slider_h, max_slider_h,
+                                 min_slider_w, max_slider_w,
+                                 default_h, default_w):
+    orig_w, orig_h = pil_image.size
+    if orig_w <= 0 or orig_h <= 0:
+        return default_h, default_w
+
+    aspect_ratio = orig_h / orig_w
+    
+    calc_h = round(np.sqrt(calculation_max_area * aspect_ratio))
+    calc_w = round(np.sqrt(calculation_max_area / aspect_ratio))
+
+    calc_h = max(mod_val, (calc_h // mod_val) * mod_val)
+    calc_w = max(mod_val, (calc_w // mod_val) * mod_val)
+    
+    new_h = int(np.clip(calc_h, min_slider_h, (max_slider_h // mod_val) * mod_val))
+    new_w = int(np.clip(calc_w, min_slider_w, (max_slider_w // mod_val) * mod_val))
+    
+    return new_h, new_w
+
+def handle_image_upload_for_dims_wan(uploaded_pil_image, current_h_val, current_w_val):
+    if uploaded_pil_image is None:
+        return gr.update(value=DEFAULT_H_SLIDER_VALUE), gr.update(value=DEFAULT_W_SLIDER_VALUE)
+    try:
+        new_h, new_w = _calculate_new_dimensions_wan(
+            uploaded_pil_image, MOD_VALUE, NEW_FORMULA_MAX_AREA,
+            SLIDER_MIN_H, SLIDER_MAX_H, SLIDER_MIN_W, SLIDER_MAX_W,
+            DEFAULT_H_SLIDER_VALUE, DEFAULT_W_SLIDER_VALUE
+        )
+        return gr.update(value=new_h), gr.update(value=new_w)
+    except Exception as e:
+        gr.Warning("Error attempting to calculate new dimensions")
+        return gr.update(value=DEFAULT_H_SLIDER_VALUE), gr.update(value=DEFAULT_W_SLIDER_VALUE)
+
+def get_duration(input_image, prompt, height, width, 
+                   negative_prompt, duration_seconds,
+                   guidance_scale, steps,
+                   seed, randomize_seed, 
+                   progress):
+    # FusionX optimized duration calculation
+    if steps > 8 and duration_seconds > 3:
+        return 100
+    elif steps > 8 or duration_seconds > 3:
+        return 80
+    else:
+        return 65
+
+@spaces.GPU(duration=get_duration)
+def generate_video(input_image, prompt, height, width, 
+                   negative_prompt=default_negative_prompt, duration_seconds = 3,
+                   guidance_scale = 1, steps = 8,  # FusionX optimized default
+                   seed = 42, randomize_seed = False, 
+                   progress=gr.Progress(track_tqdm=True)):
+    
+    if input_image is None:
+        raise gr.Error("Please upload an input image.")
+
+    target_h = max(MOD_VALUE, (int(height) // MOD_VALUE) * MOD_VALUE)
+    target_w = max(MOD_VALUE, (int(width) // MOD_VALUE) * MOD_VALUE)
+    
+    num_frames = np.clip(int(round(duration_seconds * FIXED_FPS)), MIN_FRAMES_MODEL, MAX_FRAMES_MODEL)
+    
+    current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
+
+    resized_image = input_image.resize((target_w, target_h))
+
+    # Enhanced prompt for FusionX model
+    enhanced_prompt = f"{prompt}, cinematic quality, smooth motion, detailed animation"
+
+    with torch.inference_mode():
+        output_frames_list = pipe(
+            image=resized_image, 
+            prompt=enhanced_prompt, 
+            negative_prompt=negative_prompt,
+            height=target_h, 
+            width=target_w, 
+            num_frames=num_frames,
+            guidance_scale=float(guidance_scale), 
+            num_inference_steps=int(steps),
+            generator=torch.Generator(device="cuda").manual_seed(current_seed)
+        ).frames[0]
+
+    with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
+        video_path = tmpfile.name
+    export_to_video(output_frames_list, video_path, fps=FIXED_FPS)
+    return video_path, current_seed
+
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    with gr.Column(elem_classes=["main-container"]):
+        gr.Markdown("# ⚡ Fast FusionX Wan 2.1 I2V Enhanced (14B)")
+
+        # Enhanced badges for FusionX
+        gr.HTML("""
+        <div class="badge-container">
+            <a href="https://huggingface.co/vrgamedevgirl84/Wan14BT2VFusioniX" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=FusionX&message=ENHANCED%20MODEL&color=%236a4c93&labelColor=%23533a7d&logo=huggingface&logoColor=%23ffffff&style=for-the-badge" alt="FusionX Enhanced">
+            </a>
+            <a href="https://huggingface.co/spaces/Heartsync/wan2-1-fast-security" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=FAST%20%26%20Furios&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="WAN Fast">
+            </a>
+            <a href="https://huggingface.co/spaces/Heartsync/WAN-VIDEO-AUDIO" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=VIDEO%20%26%20AUDIO&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="WAN Video Audio">
+            </a>
+        </div>
+        """)
+        
+        gr.Markdown("""
+        ### 🚀 Enhanced with FusionX Technology
+        **Features:** CausVid + AccVideo + MoviiGen1.1 + MPS Rewards LoRA + Custom Detail Enhancers
+        
+        **Optimizations:** 8-10 steps for premium quality • Enhanced motion realism • Superior temporal consistency
+        """)
+        
+        with gr.Row():
+            with gr.Column(elem_classes=["input-container"]):
+                input_image_component = gr.Image(
+                    type="pil", 
+                    label="🖼️ Input Image (auto-resized to target H/W)",
+                    elem_classes=["image-upload"]
+                )
+                prompt_input = gr.Textbox(
+                    label="✏️ Enhanced Prompt (FusionX automatically adds cinematic quality)", 
+                    value=default_prompt_i2v,
+                    lines=3
+                )
+                duration_seconds_input = gr.Slider(
+                    minimum=round(MIN_FRAMES_MODEL/FIXED_FPS,1), 
+                    maximum=round(MAX_FRAMES_MODEL/FIXED_FPS,1), 
+                    step=0.1, 
+                    value=3, 
+                    label="⏱️ Duration (seconds)", 
+                    info=f"FusionX supports {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps. Recommended: 3-5 seconds"
+                )
+                
+                with gr.Accordion("⚙️ Advanced FusionX Settings", open=False):
+                    negative_prompt_input = gr.Textbox(
+                        label="❌ Negative Prompt (Enhanced for FusionX)", 
+                        value=default_negative_prompt, 
+                        lines=4
+                    )
+                    seed_input = gr.Slider(
+                        label="🎲 Seed", 
+                        minimum=0, 
+                        maximum=MAX_SEED, 
+                        step=1, 
+                        value=42, 
+                        interactive=True
+                    )
+                    randomize_seed_checkbox = gr.Checkbox(
+                        label="🔀 Randomize seed", 
+                        value=True, 
+                        interactive=True
+                    )
+                    with gr.Row():
+                        height_input = gr.Slider(
+                            minimum=SLIDER_MIN_H, 
+                            maximum=SLIDER_MAX_H, 
+                            step=MOD_VALUE, 
+                            value=DEFAULT_H_SLIDER_VALUE, 
+                            label=f"📏 Output Height (FusionX optimized: {MOD_VALUE} multiples)"
+                        )
+                        width_input = gr.Slider(
+                            minimum=SLIDER_MIN_W, 
+                            maximum=SLIDER_MAX_W, 
+                            step=MOD_VALUE, 
+                            value=DEFAULT_W_SLIDER_VALUE, 
+                            label=f"📐 Output Width (FusionX optimized: {MOD_VALUE} multiples)"
+                        )
+                    steps_slider = gr.Slider(
+                        minimum=1, 
+                        maximum=20, 
+                        step=1, 
+                        value=8,  # FusionX optimized
+                        label="🚀 Inference Steps (FusionX: 8-10 recommended)", 
+                        info="FusionX delivers excellent results in just 8-10 steps!"
+                    ) 
+                    guidance_scale_input = gr.Slider(
+                        minimum=0.0, 
+                        maximum=20.0, 
+                        step=0.5, 
+                        value=1.0, 
+                        label="🎯 Guidance Scale (FusionX optimized)", 
+                        visible=False
+                    )
+
+                generate_button = gr.Button(
+                    "🎬 Generate FusionX Video", 
+                    variant="primary",
+                    elem_classes=["generate-btn"]
+                )
+                
+            with gr.Column(elem_classes=["output-container"]):
+                video_output = gr.Video(
+                    label="🎥 FusionX Generated Video", 
+                    autoplay=True, 
+                    interactive=False
+                )
+
+        input_image_component.upload(
+            fn=handle_image_upload_for_dims_wan,
+            inputs=[input_image_component, height_input, width_input],
+            outputs=[height_input, width_input]
+        )
+        
+        input_image_component.clear( 
+            fn=handle_image_upload_for_dims_wan,
+            inputs=[input_image_component, height_input, width_input],
+            outputs=[height_input, width_input]
+        )
+        
+        ui_inputs = [
+            input_image_component, prompt_input, height_input, width_input,
+            negative_prompt_input, duration_seconds_input,
+            guidance_scale_input, steps_slider, seed_input, randomize_seed_checkbox
+        ]
+        generate_button.click(fn=generate_video, inputs=ui_inputs, outputs=[video_output, seed_input])
+
+        with gr.Column():
+            gr.Examples(
+                examples=[ 
+                    ["peng.png", "a penguin gracefully dancing in the pristine snow, cinematic motion with detailed feathers", 576, 1024],
+                    ["forg.jpg", "the frog jumps energetically with smooth, lifelike motion and detailed texture", 832, 576],
+                    ["example.jpg", "person walking through a bustling city street, dynamic camera movement, cinematic lighting", 720, 1280],
+                ],
+                inputs=[input_image_component, prompt_input, height_input, width_input], 
+                outputs=[video_output, seed_input], 
+                fn=generate_video, 
+                cache_examples="lazy",
+                label="🌟 FusionX Example Gallery"
+            )
+            
+        gr.Markdown("""
+        ### 🔧 FusionX Model Information
+        
+        **Base Model:** Wan2.1 14B T2V Enhanced with multiple research-grade components
+        
+        **Integrated Components:**
+        - 🔗 **CausVid**: Advanced causal motion modeling
+        - 🔗 **AccVideo**: Improved temporal alignment & speed boost  
+        - 🔗 **MoviiGen1.1**: Cinematic smoothness & lighting
+        - 🔗 **MPS Rewards LoRA**: Motion & detail optimization
+        - ✨ **Custom LoRAs**: Texture & clarity enhancements
+        
+        **Performance:** Optimized for 8-10 steps • Up to 50% faster rendering • Enhanced motion quality
+        
+        **License:** Apache 2.0 / MIT - Open source and permissive
+        """)
+
+if __name__ == "__main__":
+    demo.queue().launch()import torch
+from diffusers import AutoencoderKLWan, WanImageToVideoPipeline, UniPCMultistepScheduler
+from diffusers.utils import export_to_video
+from transformers import CLIPVisionModel
+import gradio as gr
+import tempfile
+import spaces
+from huggingface_hub import hf_hub_download
+import numpy as np
+from PIL import Image
+import random
+
+# Updated MODEL_ID to FusionX
+MODEL_ID = "vrgamedevgirl84/Wan14BT2VFusioniX"
+
+# Optional fallback LoRA (if needed for additional enhancement)
+LORA_REPO_ID = "Kijai/WanVideo_comfy"
+LORA_FILENAME = "Wan21_CausVid_14B_T2V_lora_rank32.safetensors"
+
+# Load FusionX model components
+image_encoder = CLIPVisionModel.from_pretrained(MODEL_ID, subfolder="image_encoder", torch_dtype=torch.float32)
+vae = AutoencoderKLWan.from_pretrained(MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
+pipe = WanImageToVideoPipeline.from_pretrained(
+    MODEL_ID, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16
+)
+
+# FusionX optimized scheduler settings
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=8.0)
+pipe.to("cuda")
+
+# Optional: Load additional LoRA for extra enhancement (can be commented out if not needed)
+try:
+    causvid_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)
+    pipe.load_lora_weights(causvid_path, adapter_name="causvid_lora")
+    pipe.set_adapters(["causvid_lora"], adapter_weights=[0.5])  # Lower weight since CausVid is already merged
+    pipe.fuse_lora()
+    print("Additional CausVid LoRA loaded for extra enhancement")
+except Exception as e:
+    print(f"CausVid LoRA not loaded (FusionX already includes CausVid): {e}")
+
+MOD_VALUE = 32
+DEFAULT_H_SLIDER_VALUE = 576  # FusionX optimized default
+DEFAULT_W_SLIDER_VALUE = 1024  # FusionX optimized default
+NEW_FORMULA_MAX_AREA = 576.0 * 1024.0  # Updated for FusionX
+
+SLIDER_MIN_H, SLIDER_MAX_H = 128, 1080
+SLIDER_MIN_W, SLIDER_MAX_W = 128, 1920
+MAX_SEED = np.iinfo(np.int32).max
+
+FIXED_FPS = 24
+MIN_FRAMES_MODEL = 8
+MAX_FRAMES_MODEL = 121  # FusionX supports up to 121 frames
+
+# Enhanced prompts for FusionX
+default_prompt_i2v = "Cinematic motion, smooth animation, detailed textures, dynamic lighting, professional cinematography"
+default_negative_prompt = "Static image, no motion, blurred details, overexposed, underexposed, low quality, worst quality, JPEG artifacts, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, watermark, text, signature"
+
+# Enhanced CSS for FusionX theme
+custom_css = """
+/* Enhanced FusionX theme with cinematic styling */
+.gradio-container {
+    font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif !important;
+    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 25%, #0f3460 50%, #533a7d 75%, #6a4c93 100%) !important;
+    background-size: 400% 400% !important;
+    animation: cinematicShift 20s ease infinite !important;
+}
+
+@keyframes cinematicShift {
+    0% { background-position: 0% 50%; }
+    25% { background-position: 100% 50%; }
+    50% { background-position: 100% 100%; }
+    75% { background-position: 0% 100%; }
+    100% { background-position: 0% 50%; }
+}
+
+/* Main container with cinematic glass effect */
+.main-container {
+    backdrop-filter: blur(15px);
+    background: rgba(255, 255, 255, 0.08) !important;
+    border-radius: 25px !important;
+    padding: 35px !important;
+    box-shadow: 0 12px 40px 0 rgba(31, 38, 135, 0.4) !important;
+    border: 1px solid rgba(255, 255, 255, 0.15) !important;
+    position: relative;
+    overflow: hidden;
+}
+
+.main-container::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    bottom: 0;
+    background: linear-gradient(45deg, rgba(255,255,255,0.1) 0%, transparent 50%, rgba(255,255,255,0.05) 100%);
+    pointer-events: none;
+}
+
+/* Enhanced header with FusionX branding */
+h1 {
+    background: linear-gradient(45deg, #ffffff, #f0f8ff, #e6e6fa) !important;
+    -webkit-background-clip: text !important;
+    -webkit-text-fill-color: transparent !important;
+    background-clip: text !important;
+    font-weight: 900 !important;
+    font-size: 2.8rem !important;
+    text-align: center !important;
+    margin-bottom: 2.5rem !important;
+    text-shadow: 2px 2px 8px rgba(0,0,0,0.3) !important;
+    position: relative;
+}
+
+h1::after {
+    content: '🎬 FusionX Enhanced';
+    display: block;
+    font-size: 1rem;
+    color: #6a4c93;
+    margin-top: 0.5rem;
+    font-weight: 500;
+}
+
+/* Enhanced component containers */
+.input-container, .output-container {
+    background: rgba(255, 255, 255, 0.06) !important;
+    border-radius: 20px !important;
+    padding: 25px !important;
+    margin: 15px 0 !important;
+    backdrop-filter: blur(10px) !important;
+    border: 1px solid rgba(255, 255, 255, 0.12) !important;
+    box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1) !important;
+}
+
+/* Cinematic input styling */
 input, textarea, .gr-box {
-    background: rgba(255, 255, 255, 0.9) !important;
-    border: 1px solid rgba(255, 255, 255, 0.3) !important;
-    border-radius: 10px !important;
-    color: #333 !important;
-    transition: all 0.3s ease !important;
+    background: rgba(255, 255, 255, 0.95) !important;
+    border: 1px solid rgba(106, 76, 147, 0.3) !important;
+    border-radius: 12px !important;
+    color: #1a1a2e !important;
+    transition: all 0.4s ease !important;
+    box-shadow: 0 2px 8px rgba(106, 76, 147, 0.1) !important;
 }
 
 input:focus, textarea:focus {
     background: rgba(255, 255, 255, 1) !important;
-    border-color: #667eea !important;
-    box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1) !important;
+    border-color: #6a4c93 !important;
+    box-shadow: 0 0 0 3px rgba(106, 76, 147, 0.15) !important;
+    transform: translateY(-1px) !important;
 }
 
-/* 버튼 스타일 */
+/* Enhanced FusionX button */
 .generate-btn {
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    background: linear-gradient(135deg, #6a4c93 0%, #533a7d 50%, #0f3460 100%) !important;
     color: white !important;
-    font-weight: 600 !important;
-    font-size: 1.1rem !important;
-    padding: 12px 30px !important;
-    border-radius: 50px !important;
+    font-weight: 700 !important;
+    font-size: 1.2rem !important;
+    padding: 15px 40px !important;
+    border-radius: 60px !important;
     border: none !important;
     cursor: pointer !important;
-    transition: all 0.3s ease !important;
-    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4) !important;
+    transition: all 0.4s ease !important;
+    box-shadow: 0 6px 20px rgba(106, 76, 147, 0.4) !important;
+    position: relative;
+    overflow: hidden;
+}
+
+.generate-btn::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: -100%;
+    width: 100%;
+    height: 100%;
+    background: linear-gradient(90deg, transparent, rgba(255,255,255,0.3), transparent);
+    transition: left 0.5s ease;
+}
+
+.generate-btn:hover::before {
+    left: 100%;
 }
 
 .generate-btn:hover {
-    transform: translateY(-2px) !important;
-    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.6) !important;
+    transform: translateY(-3px) scale(1.02) !important;
+    box-shadow: 0 8px 25px rgba(106, 76, 147, 0.6) !important;
 }
 
-/* 슬라이더 스타일 */
+/* Enhanced slider styling */
 input[type="range"] {
     background: transparent !important;
 }
 
 input[type="range"]::-webkit-slider-track {
-    background: rgba(255, 255, 255, 0.3) !important;
-    border-radius: 5px !important;
-    height: 6px !important;
+    background: linear-gradient(90deg, rgba(106, 76, 147, 0.3), rgba(83, 58, 125, 0.5)) !important;
+    border-radius: 8px !important;
+    height: 8px !important;
 }
 
 input[type="range"]::-webkit-slider-thumb {
-    background: linear-gradient(135deg, #667eea, #764ba2) !important;
-    border: 2px solid white !important;
+    background: linear-gradient(135deg, #6a4c93, #533a7d) !important;
+    border: 3px solid white !important;
     border-radius: 50% !important;
     cursor: pointer !important;
-    width: 18px !important;
-    height: 18px !important;
+    width: 22px !important;
+    height: 22px !important;
     -webkit-appearance: none !important;
+    box-shadow: 0 2px 8px rgba(106, 76, 147, 0.3) !important;
 }
 
-/* Accordion 스타일 */
+/* Enhanced accordion */
 .gr-accordion {
-    background: rgba(255, 255, 255, 0.05) !important;
-    border-radius: 10px !important;
-    border: 1px solid rgba(255, 255, 255, 0.1) !important;
-    margin: 15px 0 !important;
+    background: rgba(255, 255, 255, 0.04) !important;
+    border-radius: 15px !important;
+    border: 1px solid rgba(255, 255, 255, 0.08) !important;
+    margin: 20px 0 !important;
+    backdrop-filter: blur(5px) !important;
 }
 
-/* 라벨 스타일 */
+/* Enhanced labels */
 label {
     color: #ffffff !important;
-    font-weight: 500 !important;
-    font-size: 0.95rem !important;
-    margin-bottom: 5px !important;
+    font-weight: 600 !important;
+    font-size: 1rem !important;
+    margin-bottom: 8px !important;
+    text-shadow: 1px 1px 2px rgba(0,0,0,0.5) !important;
 }
 
-/* 이미지 업로드 영역 */
+/* Enhanced image upload */
 .image-upload {
-    border: 2px dashed rgba(255, 255, 255, 0.3) !important;
-    border-radius: 15px !important;
-    background: rgba(255, 255, 255, 0.05) !important;
-    transition: all 0.3s ease !important;
+    border: 3px dashed rgba(106, 76, 147, 0.4) !important;
+    border-radius: 20px !important;
+    background: rgba(255, 255, 255, 0.03) !important;
+    transition: all 0.4s ease !important;
+    position: relative;
 }
 
 .image-upload:hover {
-    border-color: rgba(255, 255, 255, 0.5) !important;
-    background: rgba(255, 255, 255, 0.1) !important;
+    border-color: rgba(106, 76, 147, 0.7) !important;
+    background: rgba(255, 255, 255, 0.08) !important;
+    transform: scale(1.01) !important;
 }
 
-/* 비디오 출력 영역 */
+/* Enhanced video output */
 video {
-    border-radius: 15px !important;
-    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.3) !important;
+    border-radius: 20px !important;
+    box-shadow: 0 8px 30px rgba(0, 0, 0, 0.4) !important;
+    border: 2px solid rgba(106, 76, 147, 0.3) !important;
 }
 
-/* Examples 섹션 스타일 */
+/* Enhanced examples section */
 .gr-examples {
-    background: rgba(255, 255, 255, 0.05) !important;
-    border-radius: 15px !important;
-    padding: 20px !important;
-    margin-top: 20px !important;
+    background: rgba(255, 255, 255, 0.04) !important;
+    border-radius: 20px !important;
+    padding: 25px !important;
+    margin-top: 25px !important;
+    border: 1px solid rgba(255, 255, 255, 0.1) !important;
 }
 
-/* Checkbox 스타일 */
+/* Enhanced checkbox */
 input[type="checkbox"] {
-    accent-color: #667eea !important;
+    accent-color: #6a4c93 !important;
+    transform: scale(1.2) !important;
 }
 
-/* 반응형 애니메이션 */
+/* Responsive enhancements */
 @media (max-width: 768px) {
-    h1 { font-size: 2rem !important; }
-    .main-container { padding: 20px !important; }
+    h1 { font-size: 2.2rem !important; }
+    .main-container { padding: 25px !important; }
+    .generate-btn { padding: 12px 30px !important; font-size: 1.1rem !important; }
+}
+
+/* Badge container styling */
+.badge-container {
+    display: flex;
+    justify-content: center;
+    gap: 15px;
+    margin: 20px 0;
+    flex-wrap: wrap;
+}
+
+.badge-container img {
+    border-radius: 8px;
+    transition: transform 0.3s ease;
+}
+
+.badge-container img:hover {
+    transform: scale(1.05);
 }
 """
 
@@ -242,17 +864,18 @@ def get_duration(input_image, prompt, height, width,
                    guidance_scale, steps,
                    seed, randomize_seed, 
                    progress):
-    if steps > 4 and duration_seconds > 2:
-        return 90
-    elif steps > 4 or duration_seconds > 2:
-        return 75
+    # FusionX optimized duration calculation
+    if steps > 8 and duration_seconds > 3:
+        return 100
+    elif steps > 8 or duration_seconds > 3:
+        return 80
     else:
-        return 60
+        return 65
 
 @spaces.GPU(duration=get_duration)
 def generate_video(input_image, prompt, height, width, 
-                   negative_prompt=default_negative_prompt, duration_seconds = 2,
-                   guidance_scale = 1, steps = 4,
+                   negative_prompt=default_negative_prompt, duration_seconds = 3,
+                   guidance_scale = 1, steps = 8,  # FusionX optimized default
                    seed = 42, randomize_seed = False, 
                    progress=gr.Progress(track_tqdm=True)):
     
@@ -268,11 +891,19 @@ def generate_video(input_image, prompt, height, width,
 
     resized_image = input_image.resize((target_w, target_h))
 
+    # Enhanced prompt for FusionX model
+    enhanced_prompt = f"{prompt}, cinematic quality, smooth motion, detailed animation"
+
     with torch.inference_mode():
         output_frames_list = pipe(
-            image=resized_image, prompt=prompt, negative_prompt=negative_prompt,
-            height=target_h, width=target_w, num_frames=num_frames,
-            guidance_scale=float(guidance_scale), num_inference_steps=int(steps),
+            image=resized_image, 
+            prompt=enhanced_prompt, 
+            negative_prompt=negative_prompt,
+            height=target_h, 
+            width=target_w, 
+            num_frames=num_frames,
+            guidance_scale=float(guidance_scale), 
+            num_inference_steps=int(steps),
             generator=torch.Generator(device="cuda").manual_seed(current_seed)
         ).frames[0]
 
@@ -283,20 +914,30 @@ def generate_video(input_image, prompt, height, width,
 
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
     with gr.Column(elem_classes=["main-container"]):
-        gr.Markdown("# ✨ Fast 4 steps Wan 2.1 I2V (14B) with CausVid LoRA")
+        gr.Markdown("# ⚡ Fast FusionX Wan 2.1 I2V Enhanced (14B)")
 
-        # Add badges side by side
+        # Enhanced badges for FusionX
         gr.HTML("""
         <div class="badge-container">
+            <a href="https://huggingface.co/vrgamedevgirl84/Wan14BT2VFusioniX" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=FusionX&message=ENHANCED%20MODEL&color=%236a4c93&labelColor=%23533a7d&logo=huggingface&logoColor=%23ffffff&style=for-the-badge" alt="FusionX Enhanced">
+            </a>
             <a href="https://huggingface.co/spaces/Heartsync/wan2-1-fast-security" target="_blank">
-                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=FAST%20%26%20Furios&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="badge">
+                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=FAST%20%26%20Furios&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="WAN Fast">
             </a>
             <a href="https://huggingface.co/spaces/Heartsync/WAN-VIDEO-AUDIO" target="_blank">
-                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=VIDEO%20%26%20AUDIO&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="badge">
+                <img src="https://img.shields.io/static/v1?label=WAN%202.1&message=VIDEO%20%26%20AUDIO&color=%23008080&labelColor=%230000ff&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="WAN Video Audio">
             </a>
         </div>
         """)
         
+        gr.Markdown("""
+        ### 🚀 Enhanced with FusionX Technology
+        **Features:** CausVid + AccVideo + MoviiGen1.1 + MPS Rewards LoRA + Custom Detail Enhancers
+        
+        **Optimizations:** 8-10 steps for premium quality • Enhanced motion realism • Superior temporal consistency
+        """)
+        
         with gr.Row():
             with gr.Column(elem_classes=["input-container"]):
                 input_image_component = gr.Image(
@@ -305,24 +946,24 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
                     elem_classes=["image-upload"]
                 )
                 prompt_input = gr.Textbox(
-                    label="✏️ Prompt", 
+                    label="✏️ Enhanced Prompt (FusionX automatically adds cinematic quality)", 
                     value=default_prompt_i2v,
-                    lines=2
+                    lines=3
                 )
                 duration_seconds_input = gr.Slider(
                     minimum=round(MIN_FRAMES_MODEL/FIXED_FPS,1), 
                     maximum=round(MAX_FRAMES_MODEL/FIXED_FPS,1), 
                     step=0.1, 
-                    value=2, 
+                    value=3, 
                     label="⏱️ Duration (seconds)", 
-                    info=f"Clamped to model's {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps."
+                    info=f"FusionX supports {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps. Recommended: 3-5 seconds"
                 )
                 
-                with gr.Accordion("⚙️ Advanced Settings", open=False):
+                with gr.Accordion("⚙️ Advanced FusionX Settings", open=False):
                     negative_prompt_input = gr.Textbox(
-                        label="❌ Negative Prompt", 
+                        label="❌ Negative Prompt (Enhanced for FusionX)", 
                         value=default_negative_prompt, 
-                        lines=3
+                        lines=4
                     )
                     seed_input = gr.Slider(
                         label="🎲 Seed", 
@@ -343,40 +984,41 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
                             maximum=SLIDER_MAX_H, 
                             step=MOD_VALUE, 
                             value=DEFAULT_H_SLIDER_VALUE, 
-                            label=f"📏 Output Height (multiple of {MOD_VALUE})"
+                            label=f"📏 Output Height (FusionX optimized: {MOD_VALUE} multiples)"
                         )
                         width_input = gr.Slider(
                             minimum=SLIDER_MIN_W, 
                             maximum=SLIDER_MAX_W, 
                             step=MOD_VALUE, 
                             value=DEFAULT_W_SLIDER_VALUE, 
-                            label=f"📐 Output Width (multiple of {MOD_VALUE})"
+                            label=f"📐 Output Width (FusionX optimized: {MOD_VALUE} multiples)"
                         )
                     steps_slider = gr.Slider(
                         minimum=1, 
-                        maximum=30, 
+                        maximum=20, 
                         step=1, 
-                        value=4, 
-                        label="🚀 Inference Steps"
+                        value=8,  # FusionX optimized
+                        label="🚀 Inference Steps (FusionX: 8-10 recommended)", 
+                        info="FusionX delivers excellent results in just 8-10 steps!"
                     ) 
                     guidance_scale_input = gr.Slider(
                         minimum=0.0, 
                         maximum=20.0, 
                         step=0.5, 
                         value=1.0, 
-                        label="🎯 Guidance Scale", 
+                        label="🎯 Guidance Scale (FusionX optimized)", 
                         visible=False
                     )
 
                 generate_button = gr.Button(
-                    "🎬 Generate Video", 
+                    "🎬 Generate FusionX Video", 
                     variant="primary",
                     elem_classes=["generate-btn"]
                 )
                 
             with gr.Column(elem_classes=["output-container"]):
                 video_output = gr.Video(
-                    label="🎥 Generated Video", 
+                    label="🎥 FusionX Generated Video", 
                     autoplay=True, 
                     interactive=False
                 )
@@ -403,15 +1045,33 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
         with gr.Column():
             gr.Examples(
                 examples=[ 
-                    ["peng.png", "a penguin playfully dancing in the snow, Antarctica", 896, 512],
-                    ["forg.jpg", "the frog jumps around", 448, 832],
+                    ["peng.png", "a penguin gracefully dancing in the pristine snow, cinematic motion with detailed feathers", 576, 1024],
+                    ["forg.jpg", "the frog jumps energetically with smooth, lifelike motion and detailed texture", 832, 576],
+                    ["example.jpg", "person walking through a bustling city street, dynamic camera movement, cinematic lighting", 720, 1280],
                 ],
                 inputs=[input_image_component, prompt_input, height_input, width_input], 
                 outputs=[video_output, seed_input], 
                 fn=generate_video, 
                 cache_examples="lazy",
-                label="🌟 Example Gallery"
+                label="🌟 FusionX Example Gallery"
             )
+            
+        gr.Markdown("""
+        ### 🔧 FusionX Model Information
+        
+        **Base Model:** Wan2.1 14B T2V Enhanced with multiple research-grade components
+        
+        **Integrated Components:**
+        - 🔗 **CausVid**: Advanced causal motion modeling
+        - 🔗 **AccVideo**: Improved temporal alignment & speed boost  
+        - 🔗 **MoviiGen1.1**: Cinematic smoothness & lighting
+        - 🔗 **MPS Rewards LoRA**: Motion & detail optimization
+        - ✨ **Custom LoRAs**: Texture & clarity enhancements
+        
+        **Performance:** Optimized for 8-10 steps • Up to 50% faster rendering • Enhanced motion quality
+        
+        **License:** Apache 2.0 / MIT - Open source and permissive
+        """)
 
 if __name__ == "__main__":
     demo.queue().launch()