infer.py

# Copyright Alibaba Inc. All Rights Reserved.

import argparse
import os
import subprocess
from datetime import datetime
from pathlib import Path

import cv2
import librosa
import torch
from PIL import Image
from transformers import Wav2Vec2Model, Wav2Vec2Processor

# 注意：以下导入在完整版本中需要
# from diffsynth import ModelManager, WanVideoPipeline
from model import FantasyTalkingAudioConditionModel
from utils import get_audio_features, resize_image_by_longest_edge, save_video


def parse_args():
    """解析命令行参数"""
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--wan_model_dir",
        type=str,
        default="./models/Wan2.1-I2V-14B-720P",
        help="Wan I2V 14B模型目录"
    )
    parser.add_argument(
        "--fantasytalking_model_path",
        type=str,
        default="./models/fantasytalking_model.ckpt",
        help="FantasyTalking模型路径"
    )
    parser.add_argument(
        "--wav2vec_model_dir",
        type=str,
        default="./models/wav2vec2-base-960h",
        help="Wav2Vec模型目录"
    )
    parser.add_argument(
        "--image_path",
        type=str,
        default="./assets/images/woman.png",
        help="输入图像路径"
    )
    parser.add_argument(
        "--audio_path",
        type=str,
        default="./assets/audios/woman.wav",
        help="输入音频路径"
    )
    parser.add_argument(
        "--prompt",
        type=str,
        default="A woman is talking.",
        help="提示词"
    )
    parser.add_argument(
        "--output_dir",
        type=str,
        default="./output",
        help="输出目录"
    )
    parser.add_argument(
        "--image_size",
        type=int,
        default=512,
        help="图像尺寸"
    )
    parser.add_argument(
        "--audio_scale",
        type=float,
        default=1.0,
        help="音频条件注入权重"
    )
    parser.add_argument(
        "--prompt_cfg_scale",
        type=float,
        default=5.0,
        help="提示词CFG比例"
    )
    parser.add_argument(
        "--audio_cfg_scale",
        type=float,
        default=5.0,
        help="音频CFG比例"
    )
    parser.add_argument(
        "--max_num_frames",
        type=int,
        default=81,
        help="最大帧数"
    )
    parser.add_argument(
        "--num_inference_steps",
        type=int,
        default=30,
        help="推理步数"
    )
    parser.add_argument(
        "--seed",
        type=int,
        default=1247,
        help="随机种子"
    )
    parser.add_argument(
        "--fps",
        type=int,
        default=24,
        help="帧率"
    )
    parser.add_argument(
        "--num_persistent_param_in_dit",
        type=int,
        default=3_000_000_000,  # 16GB GPU优化
        help="DiT中持久参数数量，用于VRAM管理"
    )
    
    return parser.parse_args()


def load_models(args):
    """加载模型"""
    print("正在加载模型...")
    
    # 在完整版本中，这里会加载实际的模型
    # model_manager = ModelManager(device="cpu")
    # model_manager.load_models([...])
    # pipe = WanVideoPipeline.from_model_manager(model_manager, torch_dtype=torch.bfloat16, device="cuda")
    
    # 模拟模型加载
    pipe = None
    fantasytalking = None
    wav2vec_processor = None
    wav2vec = None
    
    print("模型加载完成（演示模式）")
    return pipe, fantasytalking, wav2vec_processor, wav2vec


def main(args, pipe, fantasytalking, wav2vec_processor, wav2vec):
    """主推理函数"""
    print(f"输入图像: {args.image_path}")
    print(f"输入音频: {args.audio_path}")
    print(f"提示词: {args.prompt}")
    
    # 创建输出目录
    os.makedirs(args.output_dir, exist_ok=True)
    
    # 在完整版本中，这里会执行实际的推理
    print("开始推理...")
    
    # 模拟输出路径
    current_time = datetime.now().strftime("%Y%m%d_%H%M%S")
    output_path = f"{args.output_dir}/output_{current_time}.mp4"
    
    print(f"输出将保存到: {output_path}")
    print("推理完成（演示模式）")
    
    return output_path


if __name__ == "__main__":
    args = parse_args()
    pipe, fantasytalking, wav2vec_processor, wav2vec = load_models(args)
    main(args, pipe, fantasytalking, wav2vec_processor, wav2vec)