app.py

import gradio as gr
import spaces
import torch
import os

# ==========================================
# 1. 核心处理函数 (骨架)
# ==========================================
@spaces.GPU
def run_stylization(input_video_path, prompt, noise_scale, shift_gamma, steps, guidance_scale, seed):
    """
    这里是实际推理逻辑的占位符。
    """
    if not input_video_path:
        return None
    
    print("========== Inference Start ==========")
    print(f"Video Path: {input_video_path}")
    print(f"Prompt: {prompt}")
    print(f"Params: Noise={noise_scale}, Gamma={shift_gamma}, Steps={steps}, CFG={guidance_scale}, Seed={seed}")

    # [Prototype Logic] 直接返回输入视频用于演示
    return input_video_path

# ==========================================
# 2. 界面布局 (Gradio Blocks)
# ==========================================

# 移除 CSS 参数以修复 TypeError
with gr.Blocks() as demo:
    with gr.Column(elem_id="col-container"):
        gr.Markdown("# 🎥 ViBT Video Stylization Interface")
        gr.Markdown("上传视频并设置风格化参数。")

        with gr.Row():
            # --- 左侧：输入与设置 ---
            with gr.Column():
                # 视频输入
                input_video = gr.Video(label="Source Video", sources=["upload"])
                
                # 提示词
                prompt_input = gr.Textbox(
                    label="Style Prompt", 
                    placeholder="e.g., Van Gogh style, cyberpunk city...",
                    value="Oil painting style, vivid colors"
                )

                # 高级参数折叠区
                with gr.Accordion("Advanced Settings", open=True):
                    with gr.Row():
                        noise_scale = gr.Slider(
                            label="Noise Scale", minimum=0.0, maximum=2.0, step=0.1, value=1.0, 
                            info="Controls how much noise is added."
                        )
                        shift_gamma = gr.Slider(
                            label="Shift Gamma", minimum=1.0, maximum=10.0, step=0.5, value=5.0,
                            info="Scheduler parameter."
                        )
                    
                    with gr.Row():
                        num_steps = gr.Slider(
                            label="Inference Steps", minimum=10, maximum=50, step=1, value=28,
                            info="More steps = higher quality but slower."
                        )
                        guidance_scale = gr.Slider(
                            label="Guidance Scale (CFG)", minimum=1.0, maximum=20.0, step=0.5, value=1.5,
                            info="How closely to follow the prompt."
                        )
                    
                    seed = gr.Number(label="Seed", value=42, precision=0)

                # 提交按钮
                run_btn = gr.Button("Generate Video", variant="primary")

            # --- 右侧：结果输出 ---
            with gr.Column():
                output_video = gr.Video(label="Stylized Result", interactive=False)

    # ==========================================
    # 3. 事件绑定
    # ==========================================
    run_btn.click(
        fn=run_stylization,
        inputs=[
            input_video, 
            prompt_input, 
            noise_scale, 
            shift_gamma, 
            num_steps, 
            guidance_scale, 
            seed
        ],
        outputs=[output_video]
    )

if __name__ == "__main__":
    demo.launch()