2026 最新 AI 漫剧本地部署深度教程｜基于 ComfyUI 私有化 AI 视频生成、解决帧闪烁与角色漂移工程方案

# 查看显卡CUDA支持情况
nvidia-smi
# 查看Python版本，确认是3.10.x
python --version
# 查看git版本
git --version
# 升级pip
python -m pip install --upgrade pip

# 创建项目文件夹
mkdir D:\ai_comic_project
cd D:\ai_comic_project
# 获取ComfyUI源码
git clone ComfyUI源码目录
cd ComfyUI
# 使用国内镜像安装依赖
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

cd custom_nodes
git clone ComfyUI管理器源码目录
git clone VideoHelperSuite视频套件源码目录
git clone ComfyUI_IPAdapter_plus源码目录
git clone ImpactPack源码目录
git clone KJNodes源码目录
git clone FaceDetailer相关节点源码目录

python main.py --cuda-malloc --enable-insecure-extension-access

@echo off
echo ===== AI漫剧模型批量部署脚本 =====
set "COMFY_ROOT=D:\ai_comic_project\ComfyUI"
:: 移动SDXL/FLUX大模型
move "D:\model_store\base\*.safetensors" "%COMFY_ROOT%\models\checkpoints\"
:: IPAdapter特征模型
move "D:\model_store\ipadapter\*.safetensors" "%COMFY_ROOT%\models\ipadapter\"
:: LoRA画风、角色模型
move "D:\model_store\lora\*.safetensors" "%COMFY_ROOT%\models\loras\"
:: VAE模型
move "D:\model_store\vae\*.safetensors" "%COMFY_ROOT%\models\vae\"
echo 模型文件迁移完成
pause

import requests
import json
import time
import gc
import torch
import os
# 全局显存优化环境变量，针对8G显卡优化
os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True,max_split_size_mb:128"
torch.backends.cudnn.benchmark = True
API_URL = "http://127.0.0.1:8188"
WORKFLOW_PATH = "./stable_comic_workflow.json"
SCENARIO_FILE = "./script_scenes.txt"
OUTPUT_DIR = "./comic_output"
if not os.path.exists(OUTPUT_DIR):
    os.makedirs(OUTPUT_DIR)
def free_gpu_resource():
    """释放显存、内存碎片"""
    gc.collect()
    torch.cuda.empty_cache()
def get_task_history(prompt_id):
    """查询任务是否完成"""
    try:
        resp = requests.get(f"{API_URL}/history", timeout=120)
        history_data = resp.json()
        return prompt_id in history_data
    except Exception as e:
        print(f"查询任务异常: {e}")
        time.sleep(3)
        return False
def submit_workflow(workflow_json):
    """提交工作流到ComfyUI接口"""
    payload = {"prompt": workflow_json}
    resp = requests.post(f"{API_URL}/prompt", json=payload, timeout=300)
    result = resp.json()
    return result["prompt_id"]
def load_scene_list():
    """读取分镜剧本文件，每行一条分镜提示词"""
    scene_list = []
    with open(SCENARIO_FILE, "r", encoding="utf-8") as f:
        for line in f.readlines():
            line = line.strip()
            if len(line) > 0:
                scene_list.append(line)
    return scene_list
def modify_workflow_prompt(workflow, positive_prompt):
    """动态替换工作流正向提示词，适配不同分镜"""
    for node_id, node_data in workflow.items():
        if "positive" in node_data["inputs"]:
            node_data["inputs"]["positive"] = positive_prompt
    return workflow
if __name__ == "__main__":
    print("【AI漫剧本地批量量产系统｜工程稳定模式启动】")
    # 加载基础工作流模板
    base_workflow = json.load(open(WORKFLOW_PATH, "r", encoding="utf-8"))
    scenes = load_scene_list()
    print(f"一共读取到 {len(scenes)} 条分镜")
    for idx, scene_text in enumerate(scenes):
        print(f"\n===== 正在渲染第{idx+1}/{len(scenes)}分镜 =====")
        current_workflow = modify_workflow_prompt(base_workflow, scene_text)
        pid = submit_workflow(current_workflow)
        print(f"任务ID：{pid}，等待推理完成")
        # 循环等待任务结束
        while not get_task_history(pid):
            time.sleep(2)
        
        free_gpu_resource()
        print(f"分镜{idx+1}渲染完成，显存已回收")
    
    print("\n========== 全部AI漫剧分镜推理任务执行完毕 ==========")

:: 进入输出目录
cd D:\ai_comic_project\ComfyUI\comic_output
:: 24fps无损H.264视频合成
ffmpeg -framerate 24 -i frame_%04d.png -c:v libx264 -preset slow -crf 18 -pix_fmt yuv420p comic_episode.mp4
:: 追加音频（配音）到漫剧视频
ffmpeg -i comic_episode.mp4 -i voice_audio.wav -c copy comic_final.mp4
:: 帧混合防抖处理，降低画面微闪烁
ffmpeg -i comic_episode.mp4 -filter:v tblend=all_mode=average -c:a copy comic_smooth.mp4

import subprocess
import time
def get_gpu_info():
    result = subprocess.check_output(
        ["nvidia-smi", "--query-gpu=memory.used,memory.total", "--format=csv,noheader,nounits"],
        encoding="utf-8"
    )
    used, total = result.strip().split(", ")
    return int(used), int(total)
if __name__ == "__main__":
    print("GPU显存监控程序，按Ctrl+C退出")
    while True:
        mem_used, mem_total = get_gpu_info()
        usage_rate = mem_used / mem_total * 100
        print(f"已使用显存: {mem_used} MB / {mem_total} MB，占用率: {usage_rate:.2f}%")
        time.sleep(3)

def parse_script_to_scene(raw_script_path, out_path):
    scenes = []
    with open(raw_script_path, "r", encoding="utf-8") as f:
        lines = f.readlines()
    for line in lines:
        line = line.strip()
        if not line:
            continue
        # 清洗特殊符号，适配扩散模型提示词
        clean_text = line.replace("\n","").replace("\r","")
        # 追加稳定性约束词
        prompt = f"{clean_text},国漫风格，固定角色面部，稳定光影，无闪烁，清晰线条，2D漫剧，高质量"
        scenes.append(prompt)
    with open(out_path,"w",encoding="utf-8") as f:
        for s in scenes:
            f.write(s + "\n")
    print(f"分镜处理完成，共{len(scenes)}条分镜保存到{out_path}")
if __name__ == "__main__":
    parse_script_to_scene("./raw_script.txt", "./script_scenes.txt")

# 卸载冲突torch版本
pip uninstall torch torchvision torchaudio
# 安装适配CUDA11.8的torch
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118