app.py

import gradio as gr
import time
import os

# This is a placeholder function to simulate the backend processing.
# In a real application, this function would contain the logic for a deep learning model 
# to perform character replacement. For this UI demo, we simulate a processing delay 
# and simply return the original video.
def replace_character(source_image, target_video, progress=gr.Progress(track_tqdm=True)):
    """
    Simulates the character replacement process in a video.

    Args:
        source_image (str): File path to the source character image.
        target_video (str): File path to the target video.
        progress (gr.Progress): Gradio progress tracker to show processing status.

    Returns:
        str: File path of the processed video. For this demo, it's the original video.
    """
    if source_image is None:
        raise gr.Error("Please upload a character reference image.")
    if target_video is None:
        raise gr.Error("Please upload a target video.")

    # Simulate a multi-stage AI process
    stages = [
        "Initializing model...",
        "Detecting faces and bodies in video...",
        "Tracking primary character...",
        "Generating character mask...",
        "Swapping frames with reference image...",
        "Rendering final video..."
    ]
    
    for stage in progress.tqdm(stages, desc="Starting process"):
        # Simulate work for each stage
        time.sleep(2.5)

    # In a real implementation, you would return the path to the newly created video file.
    return target_video

# Define the Gradio interface using gr.Blocks for a custom layout
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    # Header and description
    gr.HTML(
        """
        <div style="text-align: center; max-width: 800px; margin: 0 auto;">
            <h1 style="font-weight: 900; font-size: 2.5rem;">🎭 AI Video Character Replacement</h1>
            <p style="margin-top: 1rem; font-size: 1.1rem; color: #4B5563;">
                Provide a reference image of a character and a target video. The AI will replace a character in the video with the one from your image.
                <br>
                <em>(Note: This is a UI demonstration. The backend simulates the process and returns the original video.)</em>
            </p>
            <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="text-decoration: none; color: #3B82F6; font-weight: 500;">
                Built with anycoder
            </a>
        </div>
        """
    )
    
    # Main UI layout with inputs and outputs
    with gr.Row(variant="panel", equal_height=True):
        # Input column
        with gr.Column(scale=1, min_width=300):
            gr.Markdown("### 1. Inputs")
            source_image = gr.Image(
                type="filepath", 
                label="Character Reference Image",
                info="Upload a clear image of the character you want to insert."
            )
            target_video = gr.Video(
                label="Target Video",
                info="Upload the video where you want to replace a character."
            )
            submit_btn = gr.Button("✨ Replace Character", variant="primary")
            
        # Output column
        with gr.Column(scale=1, min_width=300):
            gr.Markdown("### 2. Result")
            output_video = gr.Video(
                label="Result Video", 
                interactive=False,
                info="The processed video will appear here."
            )

    # Link the button to the processing function
    submit_btn.click(
        fn=replace_character,
        inputs=[source_image, target_video],
        outputs=output_video
    )

# Launch the application
if __name__ == "__main__":
    demo.launch()
```