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README.md
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README.md
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# SFX-Library-Automation 🎧
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**基于 Ollama 本地大模型与 Python 的音效库整理工具集：自动汉化文件名、目录名，及多线程压缩瘦身。**
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## ✨ 功能特性 (Features)
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这是我为了整理几百 GB 英文音效库而编写的三个 Python 脚本，旨在解决“英文文件名难检索”和“WAV文件占用空间大”的痛点。
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1. **🤖 智能汉化文件名 (`translate_sfx.py`)**
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* 使用本地 Ollama API (推荐 Gemma/Llama3) 进行翻译。
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* 理解音效术语 (如 `Whoosh` -> `嗖嗖声`, `Impact` -> `撞击`)。
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* **格式**：`【中文翻译】原始英文名.wav`，保留原文以便对照。
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* 支持断点续传（跳过已汉化文件）。
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2. **📂 智能汉化文件夹 (`translate_folders.py`)**
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* 采用 Bottom-Up (倒序) 逻辑，安全处理多层级嵌套目录。
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* 智能识别并跳过已包含中文的目录，保护根目录结构。
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3. **⚡ 多线程音频压缩 (`wav_to_mp3.py`)**
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* 利用 `concurrent.futures` 跑满 CPU 核心。
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* 实测 16 线程下，处理 500+ 文件仅需 20多秒。
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* 推荐 **320kbps MP3**，在缩减 75% 体积的同时保留高频细节。
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* **安全模式**：只有在 MP3 生成且校验成功后，才询问是否删除原 WAV。
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## 🚀 快速开始 (Quick Start)
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### 依赖
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* Python 3.x
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* `pip install requests`
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* [Ollama](https://ollama.com/) (运行中, 默认端口 11434)
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* [FFmpeg](https://ffmpeg.org/) (需添加到环境变量或放置在脚本同级目录)
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### 使用
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1. 启动 Ollama: `ollama run gemma3:12b` (或其他模型)
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2. 运行脚本: `python translate_sfx.py`
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3. 拖入文件夹路径，按提示操作即可。建议先选择 **模式1 (模拟/Dry Run)** 查看效果。
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---
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*Made with ❤️ for Sound Designers & Editors.*
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128
translate_folders.py
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translate_folders.py
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import os
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import requests
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import sys
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# ================= 配置区域 =================
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MODEL_NAME = "gemma3:12b"
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OLLAMA_API_URL = "http://localhost:11434/api/chat"
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# 翻译缓存
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translation_cache = {}
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# ===========================================
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def get_translation(text, model):
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if text in translation_cache:
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return translation_cache[text]
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system_prompt = (
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"You are a professional translator for Audio/Video asset libraries. "
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"Translate the category/folder name into concise Simplified Chinese. "
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"Rules: 1. Only output the Chinese translation. 2. Do not explain. "
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"3. Keep terms like 'SFX', 'BGM', 'Foley' accurate."
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)
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payload = {
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"model": model,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": f'Translate folder name: "{text}"'}
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],
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"stream": False,
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"options": {"temperature": 0.1}
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}
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try:
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response = requests.post(OLLAMA_API_URL, json=payload, timeout=60)
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if response.status_code == 200:
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translated_text = response.json()['message']['content'].strip()
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# 清洗特殊字符
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for char in '<>:"/\|?*\'"“”。':
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translated_text = translated_text.replace(char, '')
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if translated_text:
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translation_cache[text] = translated_text
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return translated_text
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except:
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pass
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return None
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def is_already_chinese(text):
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"""只要包含任意一个中文字符，就认为是中文命名的"""
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for char in text:
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if '\u4e00' <= char <= '\u9fff':
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return True
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return False
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def process_folder_renaming():
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while True:
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target_dir = input("\n请拖入(或粘贴)要处理文件夹的【根目录路径】: ").strip().strip('"').strip("'")
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if os.path.exists(target_dir):
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break
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print("❌ 路径不存在，请重试。")
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print("\n请选择模式:")
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print("1. 仅模拟 (推荐先看一眼)")
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print("2. 直接执行")
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is_dry_run = input("请输入数字 (默认1): ").strip() != '2'
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if not is_dry_run:
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print("\n>>> ⚠️ 警告：即将修改文件夹名称！ <<<")
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count = 0
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success_count = 0
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skipped_chinese_count = 0
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print(f"\n正在扫描并分析目录结构 (倒序模式)...")
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# topdown=False 确保先处理最里面的子文件夹
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for root, dirs, files in os.walk(target_dir, topdown=False):
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for dirname in dirs:
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# 【核心保护机制】
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# 如果文件夹名字里已经有中文，直接跳过，并在控制台显示灰色/提示信息
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if is_already_chinese(dirname):
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# 这里为了不刷屏，只在 dry_run 或者特定情况下打印，或者只计数
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# 既然你担心根目录被改，我们可以把跳过的信息打印出来让你放心
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# print(f"[跳过-已含中文] {dirname}")
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skipped_chinese_count += 1
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continue
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count += 1
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print(f"[{count}] 正在思考: {dirname} ...", end="\r")
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cn_name = get_translation(dirname, MODEL_NAME)
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padding = " " * 40
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if cn_name:
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new_dirname = f"【{cn_name}】{dirname}"
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old_path = os.path.join(root, dirname)
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new_path = os.path.join(root, new_dirname)
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if is_dry_run:
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print(f"[模拟] {dirname} -> 【{cn_name}】{dirname}{padding}")
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else:
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try:
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os.rename(old_path, new_path)
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print(f"[成功] {new_dirname}{padding}")
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success_count += 1
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except Exception as e:
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print(f"[失败] {dirname}: {e}{padding}")
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print("\n" + "-"*30)
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print(f"✅ 完成！")
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print(f" - 翻译并重命名: {success_count} 个文件夹")
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print(f" - 智能避开已汉化目录: {skipped_chinese_count} 个")
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def main():
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print("=== 子目录智能汉化工具 (保护根目录版) ===")
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print(f"当前模型: {MODEL_NAME}")
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while True:
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process_folder_renaming()
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if input("\n🔄 是否继续处理其他位置？(y/n): ").lower() != 'y':
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break
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if __name__ == "__main__":
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main()
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translate_sfx.py
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translate_sfx.py
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import os
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import requests
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import json
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import sys
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# ================= 配置区域 =================
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# 你的 Ollama 模型名称
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MODEL_NAME = "gemma3:12b"
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# Ollama API 地址
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OLLAMA_API_URL = "http://localhost:11434/api/chat"
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# 需要处理的文件后缀
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EXTENSIONS = ('.wav', '.mp3', '.flac', '.aiff', '.ogg', '.m4a')
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# 翻译缓存 (保留在内存中，处理下一个文件夹时如果有重复词，速度会飞快)
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translation_cache = {}
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# ===========================================
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def get_translation_via_requests(filename, model):
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"""使用 requests 直接调用 Ollama 接口"""
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if filename in translation_cache:
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return translation_cache[filename]
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system_prompt = (
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"You are a professional translator for Audio Sound Effects (SFX) libraries. "
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"Your task is to translate English filenames into concise Simplified Chinese. "
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"Rules: 1. Only output the Chinese translation. 2. Do not explain. 3. Keep technical terms accurate (e.g., 'Whoosh' -> '嗖嗖声')."
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)
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user_prompt = f'Translate this filename: "{filename}"'
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payload = {
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"model": model,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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],
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"stream": False,
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"options": {
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"temperature": 0.1
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}
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}
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try:
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response = requests.post(OLLAMA_API_URL, json=payload, timeout=60)
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response.raise_for_status()
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result_json = response.json()
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translated_text = result_json['message']['content'].strip()
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invalid_chars = '<>:"/\|?*\'"“”。'
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for char in invalid_chars:
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translated_text = translated_text.replace(char, '')
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if not translated_text:
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return None
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translation_cache[filename] = translated_text
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return translated_text
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except Exception as e:
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# 这里不打印网络报错细节，以免刷屏，只返回None跳过
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return None
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def is_already_chinese(text):
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"""检查文件名里是否已经包含中文"""
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for char in text:
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if '\u4e00' <= char <= '\u9fff':
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return True
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return False
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def process_folder():
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"""单个文件夹处理流程"""
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# 1. 获取路径
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while True:
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target_dir = input("\n请拖入(或粘贴)你要处理的【文件夹路径】: ").strip()
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target_dir = target_dir.strip('"').strip("'") # 去除引号
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if os.path.exists(target_dir):
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break
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else:
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print("❌ 错误：路径不存在，请重新输入。")
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# 2. 选择模式
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print("\n请选择模式:")
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print("1. 仅模拟 (只打印不修改)")
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print("2. 直接执行 (修改文件名)")
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mode_choice = input("请输入数字 (默认1): ").strip()
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is_dry_run = True
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if mode_choice == '2':
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is_dry_run = False
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print("\n>>> ⚠️ 警告：即将开始【真实修改】文件名！ <<<")
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else:
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print("\n>>> 🛡️ 模拟模式：不会修改任何文件 <<<")
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# 3. 扫描与处理
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count = 0
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success_count = 0
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print(f"\n正在扫描目录: {target_dir} ...\n")
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for root, dirs, files in os.walk(target_dir):
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for file in files:
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if file.lower().endswith(EXTENSIONS):
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old_name_with_ext = file
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name_part, ext_part = os.path.splitext(old_name_with_ext)
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if is_already_chinese(name_part):
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continue
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count += 1
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# 动态显示进度
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print(f"[{count}] 正在思考: {name_part} ...", end="\r")
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cn_name = get_translation_via_requests(name_part, MODEL_NAME)
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padding = " " * 30 # 用于覆盖之前的打印内容
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if cn_name:
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# 格式：【中文】英文.wav
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new_name_with_ext = f"【{cn_name}】{old_name_with_ext}"
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old_path = os.path.join(root, old_name_with_ext)
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new_path = os.path.join(root, new_name_with_ext)
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if is_dry_run:
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print(f"[模拟] {name_part} -> 【{cn_name}】{padding}")
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else:
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try:
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os.rename(old_path, new_path)
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print(f"[成功] {new_name_with_ext}{padding}")
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success_count += 1
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except Exception as e:
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print(f"[失败] {e}{padding}")
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else:
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# 如果翻译失败，不需要刷屏，静默跳过或简单提示
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pass
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print("\n" + "-"*30)
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print(f"✅ 本次任务完成！扫描: {count} 个，成功重命名: {success_count} 个。")
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def main():
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print("=============================================")
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print(" 音效文件名智能翻译工具 (Gemma + Ollama)")
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print("=============================================")
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print(f"当前模型: {MODEL_NAME}")
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while True:
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process_folder()
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# 循环询问
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print("\n" + "="*30)
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choice = input("🔄 是否继续处理其他目录？(y/n): ").strip().lower()
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if choice == 'y':
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print("\n" * 2) # 空两行，视觉上分隔
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continue
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else:
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print("\n👋 再见！")
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break
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if __name__ == "__main__":
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try:
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main()
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except KeyboardInterrupt:
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print("\n\n用户强制停止，程序退出。")
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156
wav_to_mp3.py
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156
wav_to_mp3.py
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import os
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import subprocess
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import concurrent.futures
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import time
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import sys
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# ================= 配置区域 =================
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# 目标码率: '192k' 或 '320k' (推荐 320k)
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BITRATE = '320k'
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# 并发线程数 (根据你的CPU核心数自动设定，也可以手动填数字，比如 4)
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MAX_WORKERS = os.cpu_count()
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# ===========================================
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def check_ffmpeg():
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"""检查 ffmpeg 是否可用"""
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try:
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subprocess.run(["ffmpeg", "-version"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True)
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return True
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except (subprocess.CalledProcessError, FileNotFoundError):
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return False
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def convert_single_file(file_info):
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"""单个文件转换逻辑"""
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wav_path, mp3_path = file_info
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# 如果 MP3 已经存在且大小不为0，跳过
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if os.path.exists(mp3_path) and os.path.getsize(mp3_path) > 0:
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return "skipped"
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# 调用 ffmpeg 转换
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# -i 输入
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# -b:a 码率
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# -map_metadata 0 保留元数据
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# -y 覆盖输出
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# -v error 静默模式，只报错
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cmd = [
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"ffmpeg", "-i", wav_path,
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"-codec:a", "libmp3lame",
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"-b:a", BITRATE,
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"-map_metadata", "0",
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"-y", "-v", "error",
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mp3_path
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]
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try:
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result = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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if result.returncode == 0:
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return "success"
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else:
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return f"error: {result.stderr.decode('utf-8', errors='ignore')}"
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except Exception as e:
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return f"exception: {str(e)}"
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def main():
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print("=============================================")
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print(f" WAV 转 MP3 批量压缩工具 (多线程版)")
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print(f" 目标码率: {BITRATE}")
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print("=============================================")
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if not check_ffmpeg():
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print("❌ 错误：找不到 ffmpeg。")
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print("请下载 ffmpeg.exe 并将其放到本脚本同一目录下，或者添加到系统环境变量。")
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return
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target_dir = input("\n请拖入要压缩的文件夹路径: ").strip().strip('"').strip("'")
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if not os.path.exists(target_dir):
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print("路径不存在。")
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return
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# 1. 扫描所有 wav 文件
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print(f"\n正在扫描 WAV 文件...")
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tasks = []
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wav_files_list = [] # 用于后续统计和删除
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for root, dirs, files in os.walk(target_dir):
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for file in files:
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if file.lower().endswith(".wav"):
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wav_path = os.path.join(root, file)
|
||||
# 构造 MP3 路径 (同目录下，后缀变 .mp3)
|
||||
mp3_path = os.path.splitext(wav_path)[0] + ".mp3"
|
||||
|
||||
tasks.append((wav_path, mp3_path))
|
||||
wav_files_list.append(wav_path)
|
||||
|
||||
total_files = len(tasks)
|
||||
if total_files == 0:
|
||||
print("没有找到 WAV 文件。")
|
||||
return
|
||||
|
||||
print(f"找到 {total_files} 个 WAV 文件，准备开始转换...")
|
||||
print(f"火力全开，使用 {MAX_WORKERS} 个线程并发处理...")
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# 2. 多线程执行转换
|
||||
success_count = 0
|
||||
skipped_count = 0
|
||||
error_count = 0
|
||||
|
||||
with concurrent.futures.ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
|
||||
# 提交任务
|
||||
future_to_file = {executor.submit(convert_single_file, task): task for task in tasks}
|
||||
|
||||
# 处理结果进度条
|
||||
finished = 0
|
||||
for future in concurrent.futures.as_completed(future_to_file):
|
||||
result = future.result()
|
||||
finished += 1
|
||||
|
||||
if result == "success":
|
||||
success_count += 1
|
||||
elif result == "skipped":
|
||||
skipped_count += 1
|
||||
else:
|
||||
error_count += 1
|
||||
# 如果出错，打印出错的文件名
|
||||
wav_p = future_to_file[future][0]
|
||||
print(f"\n[失败] {os.path.basename(wav_p)} -> {result}")
|
||||
|
||||
# 简单的进度显示
|
||||
print(f"进度: {finished}/{total_files} | 成功: {success_count} | 跳过: {skipped_count} | 失败: {error_count}", end="\r")
|
||||
|
||||
end_time = time.time()
|
||||
duration = end_time - start_time
|
||||
|
||||
print(f"\n\n转换完成！耗时: {duration:.2f} 秒")
|
||||
|
||||
# 3. 清理旧文件询问
|
||||
if success_count > 0 or skipped_count > 0:
|
||||
print("="*40)
|
||||
print("【清理阶段】")
|
||||
print(f"转换已完成。你现在的文件夹里同时存在 .wav 和 .mp3 文件。")
|
||||
choice = input(f"⚠️ 是否删除原有的 {len(wav_files_list)} 个 WAV 文件以释放空间？(输入 'DELETE' 确认): ").strip()
|
||||
|
||||
if choice == 'DELETE':
|
||||
print("正在删除 WAV 源文件...")
|
||||
deleted_num = 0
|
||||
for wav_p in wav_files_list:
|
||||
try:
|
||||
# 再次确认对应的 MP3 真的存在，防止误删
|
||||
mp3_p = os.path.splitext(wav_p)[0] + ".mp3"
|
||||
if os.path.exists(mp3_p) and os.path.getsize(mp3_p) > 0:
|
||||
os.remove(wav_p)
|
||||
deleted_num += 1
|
||||
else:
|
||||
print(f"[跳过删除] 对应的 MP3 不存在或大小异常: {wav_p}")
|
||||
except Exception as e:
|
||||
print(f"[删除失败] {wav_p}: {e}")
|
||||
print(f"清理完毕！共删除了 {deleted_num} 个 WAV 文件。")
|
||||
else:
|
||||
print("已保留 WAV 原文件。")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user