Update app.py

app.py

@@ -10,340 +10,40 @@ import numpy as np
 from PIL import Image
 import random
 
-# Base MODEL_ID (using original Wan model that's compatible with diffusers)
-#MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-480P-Diffusers"
-MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-720P"
+MODEL_ID = "Wan-AI/Wan2.1-I2V-14B-720P-Diffusers"
 
-# FusionX enhancement LoRAs (based on FusionX composition)
 LORA_REPO_ID = "vrgamedevgirl84/Wan14BT2VFusioniX"
-LORA_FILENAME = "FusionX_LoRa/Wan2.1_I2V_14B_FusionX_LoRA.safetensors"
+LORA_FILENAME = "FusionX_LoRa/Wan2.1_T2V_14B_FusionX_LoRA.safetensors"
 
-
-# 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, 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")
 
-# Load FusionX enhancement LoRAs
-from huggingface_hub import hf_hub_download
-import torch
-
-from huggingface_hub import hf_hub_download
-import torch
-
-# Load FusionX enhancement LoRAs
-lora_adapters = []
-lora_weights = []
-
-# Print all named parameters (safely) from any pipeline
-def print_named_params(module, module_name=""):
-    print(f"\n🔍 Parameters in {module_name or 'pipeline'}:")
-    for name, param in module.named_parameters():
-        print(f"{name}: {param.shape}")
-
-# Try printing known submodules in the pipeline
-def print_all_pipeline_keys(pipe):
-    print("🧠 Exploring pipeline structure:")
-    for attr in dir(pipe):
-        if not attr.startswith("_"):
-            try:
-                obj = getattr(pipe, attr)
-                if isinstance(obj, torch.nn.Module):
-                    print_named_params(obj, attr)
-            except Exception as e:
-                print(f"⚠️ Could not inspect {attr}: {e}")
-
-# Print LoRA file contents
-def print_lora_checkpoint_keys(path):
-    try:
-        lora_checkpoint = torch.load(path, map_location="cpu")
-        print("\n📦 LoRA Checkpoint Keys:")
-        for k, v in lora_checkpoint.items():
-            print(f"{k}: {v.shape}")
-    except Exception as e:
-        print(f"❌ Failed to load LoRA for inspection: {e}")
-
-# Step 1: Explore the pipeline model structure
-print_all_pipeline_keys(pipe)
-
-# Step 2: Download LoRA file
-lora_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)
-
-# Step 3: Print LoRA checkpoint keys
-print_lora_checkpoint_keys(lora_path)
-
-# Step 4: Load and apply the LoRA
-try:
-    pipe.load_lora_weights(lora_path, adapter_name="main")
-    pipe.set_adapters(["main"], adapter_weights=[1.0])
-    pipe.fuse_lora()
-    print("✅ LoRA applied successfully.")
-except Exception as e:
-    print(f"❌ Failed to load LoRA: {e}")
-
-
-
-
-    
+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()
 
 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
+DEFAULT_H_SLIDER_VALUE = 640
+DEFAULT_W_SLIDER_VALUE = 1024
+NEW_FORMULA_MAX_AREA = 640.0 * 1024.0 
 
-SLIDER_MIN_H, SLIDER_MAX_H = 128, 1080
-SLIDER_MIN_W, SLIDER_MAX_W = 128, 1920
+SLIDER_MIN_H, SLIDER_MAX_H = 128, 1024
+SLIDER_MIN_W, SLIDER_MAX_W = 128, 1024
 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-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;
-}
+MAX_FRAMES_MODEL = 81 
 
-/* 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;
-}
+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"
 
-/* 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;
-    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,
@@ -385,19 +85,18 @@ def get_duration(input_image, prompt, height, width,
                    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
+    if steps > 4 and duration_seconds > 2:
+        return 90
+    elif steps > 4 or duration_seconds > 2:
+        return 75
     else:
-        return 65
+        return 60
 
 @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, 
+                   negative_prompt=default_negative_prompt, duration_seconds = 2,
+                   guidance_scale = 1, steps = 4,
+                   seed = 42, randomize_seed = False, 
                    progress=gr.Progress(track_tqdm=True)):
     
     if input_image is None:
@@ -412,19 +111,11 @@ 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=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),
+            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),
             generator=torch.Generator(device="cuda").manual_seed(current_seed)
         ).frames[0]
 
@@ -433,143 +124,55 @@ def generate_video(input_image, prompt, height, width,
     export_to_video(output_frames_list, video_path, fps=FIXED_FPS)
     return video_path, current_seed
 
-# --- Gradio UI ---
-css="""
-#title{text-align: center}
-#title h1{font-size: 3em; display:inline-flex; align-items:center}
-#title img{width: 100px; margin-right: 0.5em}
-#col-container { margin: 0 auto; max-width: 1000px; } /* Increased max-width for gallery */
-#gallery .grid-wrap{height: 20vh !important; max-height: 250px !important;} 
-.custom_lora_card { border: 1px solid #e0e0e0; border-radius: 8px; padding: 10px; margin-top: 10px; background-color: #f9f9f9; }
-.card_internal { display: flex; align-items: center; }
-.card_internal img { margin-right: 1em; border-radius: 4px; }
-.card_internal div h4 { margin-bottom: 0.2em; }
-.card_internal div small { font-size: 0.9em; color: #555; }
-#lora_list_link { font-size: 90%; background: var(--block-background-fill); padding: 0.5em 1em; border-radius: 8px; display:inline-block; margin-top:10px;}
-"""
-
-with gr.Blocks(css=css, theme=gr.themes.Ocean(font=[gr.themes.GoogleFont("Lexend Deca"), "sans-serif"])) as demo:
-    with gr.Column(elem_classes=["main-container"]):
-        gr.Markdown("# ✨ Fast 4 steps Wan 2.1 I2V (14B) with CausVid LoRA + Audio")
-        
-        
-        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.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():
-            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"
-            )
-        
+            video_output = gr.Video(label="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])
+
+    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"
+    )
 
 if __name__ == "__main__":
     demo.queue().launch()