Update app.py

app.py

@@ -9,69 +9,302 @@ from huggingface_hub import hf_hub_download
 import numpy as np
 from PIL import Image
 import random
-import random
-import logging
-import torchaudio
-import os
-import gc
-
-os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:512'
-os.environ['HF_HUB_CACHE'] = '/tmp/hub'  # Use temp directory to avoid filling persistent storage
-
 
-from diffusers import UniPCMultistepScheduler
-from transformers import CLIPTextModel, CLIPTokenizer
+# Base MODEL_ID (using original Wan model that's compatible with diffusers)
+MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-480P-Diffusers"
 
-from safetensors.torch import load_file
-from huggingface_hub import hf_hub_download
-import torch
+# FusionX enhancement LoRAs (based on FusionX composition)
+LORA_REPO_ID = "vrgamedevgirl84/Wan14BT2VFusioniX"
+LORA_FILENAME = "FusionX_LoRa/Wan2.1_T2V_14B_FusionX_LoRA.safetensors"
 
-# --- Base model setup (Wan T2V) ---
-MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-Diffusers"
-LORA_FILENAME = "FusionX_LoRa/Wan2.1_I2V_14B_FusionX_LoRA.safetensors"
 
-print("🚀 Loading Wan2.1 T2V base pipeline...")
+# Additional enhancement LoRAs for FusionX-like quality
+# ACCVIDEO_LORA_REPO = "alibaba-pai/Wan2.1-Fun-Reward-LoRAs"
+# MPS_LORA_FILENAME = "Wan2.1-MPS-Reward-LoRA.safetensors"
 
+# Load enhanced model components
+print("🚀 Loading FusionX Enhanced Wan2.1 I2V Model...")
+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,
-    torch_dtype=torch.bfloat16,
+    MODEL_ID, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16
 )
 
-# Optional: replace scheduler for more stable generation
+# FusionX optimized scheduler settings
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=8.0)
 pipe.to("cuda")
 
-# --- Load FusionX-style LoRA ---
-print("🔧 Loading FusionX LoRA...")
+# Load FusionX enhancement LoRAs
+lora_adapters = []
+lora_weights = []
+
 try:
-    lora_path = hf_hub_download(repo_id="FusionX_LoRa", filename=LORA_FILENAME)
-    pipe.load_lora_weights(lora_path, adapter_name="fusionx_lora")
-    pipe.set_adapters(["fusionx_lora"], adapter_weights=[1.0])
-    pipe.fuse_lora()
-    print("✅ FusionX LoRA applied (strength: 1.0)")
+    # Load CausVid LoRA (strength 1.0 as per FusionX)
+    causvid_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)
+    pipe.load_lora_weights(causvid_path, adapter_name="causvid_lora")
+    lora_adapters.append("causvid_lora")
+    lora_weights.append(1.0)  # FusionX uses 1.0 for CausVid
+    print("✅ CausVid LoRA loaded (strength: 1.0)")
 except Exception as e:
-    print(f"⚠️ Failed to load FusionX LoRA: {e}")
+    print(f"⚠️ CausVid LoRA not loaded: {e}")
+
 
-# --- Ready to generate ---
-print("✨ T2V model ready for text-to-video generation!")
 
+# Apply LoRA adapters if any were loaded
+if lora_adapters:
+    pipe.set_adapters(lora_adapters, adapter_weights=lora_weights)
+    pipe.fuse_lora()
+    print(f"🔥 FusionX Enhancement Applied: {len(lora_adapters)} LoRAs fused")
+else:
+    print("📝 No LoRAs loaded - using base Wan model")
 
 MOD_VALUE = 32
-DEFAULT_H_SLIDER_VALUE = 512
-DEFAULT_W_SLIDER_VALUE = 896
-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 = 81 
+MAX_FRAMES_MODEL = 121  # FusionX supports up to 121 frames
+
+# Enhanced prompts for FusionX-style output
+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, three legs, many people in the background, walking backwards"
+
+# 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, 0.95) !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;
+}
 
-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"
+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;
+    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;
+}
+
+/* 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,
@@ -108,11 +341,24 @@ def handle_image_upload_for_dims_wan(uploaded_pil_image, current_h_val, current_
         gr.Warning("Error attempting to calculate new dimensions")
         return gr.update(value=DEFAULT_H_SLIDER_VALUE), gr.update(value=DEFAULT_W_SLIDER_VALUE)
 
-@spaces.GPU
+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 = 10,
-                   guidance_scale = 1, steps = 4,
-                   seed = 42, randomize_seed = False, 
+                   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:
@@ -127,11 +373,19 @@ def generate_video(input_image, prompt, height, width,
 
     resized_image = input_image.resize((target_w, target_h))
 
+    # Enhanced prompt for FusionX-style output
+    enhanced_prompt = f"{prompt}, cinematic quality, smooth motion, detailed animation, dynamic lighting"
+
     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]
 
@@ -140,55 +394,146 @@ def generate_video(input_image, prompt, height, width,
     export_to_video(output_frames_list, video_path, fps=FIXED_FPS)
     return video_path, current_seed
 
-with gr.Blocks() as demo:
-    gr.Markdown("# Fast 4 steps Wan 2.1 I2V (14B) with CausVid LoRA")
-    gr.Markdown("[CausVid](https://github.com/tianweiy/CausVid) is a distilled version of Wan 2.1 to run faster in just 4-8 steps, [extracted as LoRA by Kijai](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan21_CausVid_14B_T2V_lora_rank32.safetensors) and is compatible with 🧨 diffusers")
-    with gr.Row():
-        with gr.Column():
-            input_image_component = gr.Image(type="pil", label="Input Image (auto-resized to target H/W)")
-            prompt_input = gr.Textbox(label="Prompt", value=default_prompt_i2v)
-            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, label="Duration (seconds)", info=f"Clamped to model's {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps.")
-            
-            with gr.Accordion("Advanced Settings", open=False):
-                negative_prompt_input = gr.Textbox(label="Negative Prompt", value=default_negative_prompt, lines=3)
-                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 (multiple of {MOD_VALUE})")
-                    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})")
-                steps_slider = gr.Slider(minimum=1, maximum=30, step=1, value=4, label="Inference Steps") 
-                guidance_scale_input = gr.Slider(minimum=0.0, maximum=20.0, step=0.5, value=1.0, label="Guidance Scale", visible=False)
-
-            generate_button = gr.Button("Generate Video", variant="primary")
-        with gr.Column():
-            video_output = gr.Video(label="Generated Video", autoplay=True, interactive=False)
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    with gr.Column(elem_classes=["main-container"]):
+        gr.Markdown("# ⚡ FusionX Enhanced Wan 2.1 I2V (14B)")
 
-    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])
-
-    gr.Examples(
-        examples=[ 
-            ["peng.png", "a penguin playfully dancing in the snow, Antarctica", 896, 512],
-            ["forg.jpg", "the frog jumps around", 448, 832],
-        ],
-        inputs=[input_image_component, prompt_input, height_input, width_input], outputs=[video_output, seed_input], fn=generate_video, cache_examples="lazy"
-    )
+        # 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-T2V-FusioniX" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=BASE&message=WAN%202.1%20T2V-FusioniX&color=%23008080&labelColor=%23533a7d&logo=huggingface&logoColor=%23ffffff&style=for-the-badge" alt="Base Model">
+            </a>
+            <a href="https://huggingface.co/spaces/Heartsync/WAN2-1-fast-T2V-FusioniX2" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=BASE&message=WAN%202.1%20T2V-Fusioni2X&color=%23008080&labelColor=%23533a7d&logo=huggingface&logoColor=%23ffffff&style=for-the-badge" alt="Base Model">
+            </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">
+            </a>
+        </div>
+        """)
+        
+        
+        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-style enhancements applied)", 
+                    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=2, 
+                    label="⏱️ Duration (seconds)", 
+                    info=f"FusionX Enhanced supports {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps. Recommended: 2-5 seconds"
+                )
+                
+                with gr.Accordion("⚙️ Advanced FusionX Settings", open=False):
+                    negative_prompt_input = gr.Textbox(
+                        label="❌ Negative Prompt (FusionX Enhanced)", 
+                        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 Enhanced: 8-10 recommended)", 
+                        info="FusionX Enhanced 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 Enhanced Video", 
+                    variant="primary",
+                    elem_classes=["generate-btn"]
+                )
+                
+            with gr.Column(elem_classes=["output-container"]):
+                video_output = gr.Video(
+                    label="🎥 FusionX Enhanced 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, 576],
+                    ["frog.jpg", "the frog jumps energetically with smooth, lifelike motion and detailed texture", 576, 576],
+                ],
+                inputs=[input_image_component, prompt_input, height_input, width_input], 
+                outputs=[video_output, seed_input], 
+                fn=generate_video, 
+                cache_examples="lazy",
+                label="🌟 FusionX Enhanced Example Gallery"
+            )
+        
 
 if __name__ == "__main__":
     demo.queue().launch()