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app.py

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+import gradio as gr
+import time
+import numpy as np
+from PIL import Image
+import random
+
+# Mock Pipeline Class to simulate the processing stages described
+# In a real scenario, this would interface with Diffusers/PyTorch models
+class VideoGenerationPipeline:
+    def __init__(self):
+        self.device = "cpu"  # Mock device
+
+    def preprocess(self, image):
+        """Simulate Stage 1: Upscaling and Preprocessing"""
+        time.sleep(1)
+        return image
+
+    def generate_sequence(self, image, steps):
+        """Simulate Stage 2: Frame Generation"""
+        time.sleep(2)
+        return [image] * steps
+
+    def render_video(self, frames, fps):
+        """Simulate Stage 3: Video Rendering"""
+        time.sleep(1)
+        # Return a dummy video path or placeholder
+        return "output_video.mp4"
+
+# Initialize the mock pipeline
+pipeline = VideoGenerationPipeline()
+
+def process_video(
+    reference_image, 
+    pace_slider, 
+    motion_slider, 
+    num_frames, 
+    guidance_scale,
+    progress=gr.Progress()
+):
+    """
+    Main inference function simulating a complex multi-stage pipeline.
+    Uses gr.Progress to provide user feedback during long operations.
+    """
+    if reference_image is None:
+        raise gr.Error("Please upload a reference image first.")
+    
+    try:
+        # Stage 1: Preprocessing
+        progress(0.1, desc="Stage 1: Preprocessing & Upscaling...")
+        _ = pipeline.preprocess(reference_image)
+        
+        # Stage 2: Sequence Generation
+        progress(0.4, desc="Stage 2: Generating Frame Sequence...")
+        # Simulate variable processing time based on complexity
+        time.sleep(1 + (motion_slider * 0.5))
+        
+        # Stage 3: Choreography/Motion
+        progress(0.7, desc="Stage 3: Applying Motion & Choreography...")
+        _ = pipeline.generate_sequence(reference_image, num_frames)
+        
+        # Stage 4: Final Render
+        progress(0.9, desc="Stage 4: Rendering Final Video...")
+        output_path = pipeline.render_video([], fps=25)
+        
+        progress(1.0, desc="Complete!")
+        
+        # In a real app, return the actual video file path
+        # Here we return the input as a placeholder for the demo
+        return reference_image
+
+    except Exception as e:
+        raise gr.Error(f"Pipeline failed: {str(e)}")
+
+# Gradio 6 Application Structure
+# CRITICAL: gr.Blocks() takes NO parameters in Gradio 6
+with gr.Blocks() as demo:
+    
+    # Header with required attribution
+    gr.HTML("""
+    <div style="text-align: center; margin-bottom: 20px;">
+        <h1>Pro-Video Img2Vid Pipeline</h1>
+        <p>Advanced Image-to-Video Generation Workflow</p>
+        <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color: #007bff; text-decoration: none;">Built with anycoder</a>
+    </div>
+    """)
+    
+    # Layout: Sidebar for controls, Main area for IO
+    with gr.Row():
+        
+        # Sidebar for Configuration
+        with gr.Sidebar(width=320):
+            gr.Markdown("## Configuration")
+            
+            gr.Markdown("### Generation Settings")
+            pace_slider = gr.Slider(
+                minimum=0.6, 
+                maximum=1.4, 
+                value=0.9, 
+                step=0.05, 
+                label="Generation Pace",
+                info="Lower is faster processing"
+            )
+            
+            motion_slider = gr.Slider(
+                minimum=0.8, 
+                maximum=2.0, 
+                value=1.2, 
+                step=0.1, 
+                label="Motion Intensity",
+                info="Controls movement magnitude"
+            )
+            
+            num_frames = gr.Slider(
+                minimum=16,
+                maximum=64,
+                value=24,
+                step=4,
+                label="Frame Count",
+                info="Total frames in output"
+            )
+            
+            guidance_scale = gr.Slider(
+                minimum=5.0,
+                maximum=15.0,
+                value=7.5,
+                step=0.5,
+                label="Guidance Scale",
+                info="Adherence to prompt"
+            )
+            
+            gr.Markdown("---")
+            gr.Markdown("### System Info")
+            system_status = gr.Textbox(
+                value="System Ready (CUDA: Available)", 
+                label="Status", 
+                interactive=False
+            )
+        
+        # Main Content Area
+        with gr.Column(scale=1):
+            
+            gr.Markdown("## Input / Output")
+            
+            with gr.Row():
+                with gr.Column():
+                    input_image = gr.Image(
+                        type="pil", 
+                        label="Reference Image",
+                        sources=["upload", "clipboard"],
+                        height=400
+                    )
+                    
+                    # Action Buttons
+                    with gr.Row():
+                        generate_btn = gr.Button("Generate Video", variant="primary", size="lg")
+                        clear_btn = gr.ClearButton([input_image], variant="stop")
+                
+                with gr.Column():
+                    output_video = gr.Video(
+                        label="Generated Video Output (25fps)", 
+                        autoplay=True,
+                        height=400
+                    )
+            
+            # Advanced Settings Accordion
+            with gr.Accordion("Advanced Settings", open=False):
+                seed = gr.Number(label="Seed (Random for -1)", value=-1, precision=0)
+                negative_prompt = gr.Textbox(
+                    label="Negative Prompt", 
+                    placeholder="blur, distortion, low quality...",
+                    lines=2
+                )
+                enable_lora = gr.Checkbox(label="Enable Custom LoRA", value=False)
+
+    # Event Listeners
+    # Gradio 6 uses api_visibility instead of just api_name
+    generate_btn.click(
+        fn=process_video,
+        inputs=[
+            input_image, 
+            pace_slider, 
+            motion_slider, 
+            num_frames,
+            guidance_scale
+        ],
+        outputs=output_video,
+        api_visibility="public"
+    )
+
+# Gradio 6 Launch Method
+# CRITICAL: All parameters (theme, css, etc.) go here, NOT in gr.Blocks()
+demo.launch(
+    theme=gr.themes.Soft(
+        primary_hue="indigo",
+        secondary_hue="blue",
+        neutral_hue="slate",
+        font=gr.themes.GoogleFont("Inter"),
+        text_size="lg",
+        spacing_size="lg",
+        radius_size="md"
+    ),
+    # Custom CSS for additional polish
+    css="""
+    .gradio-container {
+        max-width: 1400px !important;
+    }
+    h1 {
+        font-weight: 700 !important;
+        color: #1f2937 !important;
+    }
+    """,
+    footer_links=[
+        {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}
+    ]
+)

requirements.txt

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+Pillow
+gradio
+numpy