登录 注册
其他
16,441
Stars
2,568
Forks
205
Watchers
240
Open Issues
MIT
许可证
Python
语言
2018-03-04
创建时间
2026-11-05
最近更新

项目能做什么

基于频率响应自动进行耳机均衡(EQ)调节的工具。
来源:AI 基于仓库事实生成 · 内容以仓库实际 README 为准

使用说明 查看原始 README 原仓库文档

中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
# AutoEq
AutoEq is a tool for automatically equalizing headphones.

Go to **[autoeq.app](https://autoeq.app)** to get started.

This Github repository now mainly serves developers. The contributions of this project are:
* Web application for easily equalize and tweak headphone frequency responses without needing to install anything
* Library for working with (headphone) frequency responses and optimizing parametric equalizers
* [PyPi package](https://pypi.org/project/autoeq/) for installing the library on your projects
* Collection of headphone [measurements](./measurements) as numerical data from
[oratory1990](https://www.reddit.com/r/oratory1990/wiki/index/list_of_presets/),
[crinacle](https://crinacle.com),
[Innerfidelity](https://www.stereophile.com/content/innerfidelity-headphone-measurements),
[Rtings](https://www.rtings.com/headphones/1-5/graph) and legacy
headphone.com measurements (which are not the same as what the company produces today).
* Collection of different headphone frequency response [targets](./targets) as numerical data
* Pre-computed equalizer settings in [results](./results), although these should not be used by normal users since
**[autoeq.app](https://autoeq.app)** exists

![Sennheiser HD 800](./results/oratory1990/over-ear/Sennheiser%20HD%20800/Sennheiser%20HD%20800.png)

*Sennheiser HD 800 equalization results plotted*

### Updates
**2023-10-29** AutoEq version 4.0.0. Improved and unified naming conventions across the project. Cleaned up obsolete
files and reorganized directory structure. Completely reworked database management tools.

**2022-05-14** Web application. Reorganized measurements and results.

**2022-10-30** Restructured the project and published in PyPi. Source code moved under [autoeq](./autoeq) directory and 
command line usage changed from `python autoeq.py` to `python -m autoeq` with underscores `_` replaced with hyphens `-`
in the parameter names. 

**2022-09-18** Parametric eq optimizer reworked. The new optimizer supports shelf filters, has a powerful configuration
system, run 10x faster, has limits for Fc, Q and gain value ranges and treats +10 kHz range as average value instead of
trying to fix it precisely.

## Usage
AutoEq produces settings for basically all types of equalizer apps but does not do the equalization itself. You'll need
a different app for that. Go to **[autoeq.app](https://autoeq.app)** and select your equalizer app of choice. Quick
instructions for importing the produced settings will be shown there.

## Command Line Use
In addition to the web application, AutoEq can be used from command line (terminal). This is advanced use mainly
intended for developers. The following instructions apply for command line and Python interface use.

### Installing
- Download and install Git: https://git-scm.com/downloads. When installing Git on Windows, use Windows SSL verification
instead of Open SSL or you might run into problems when installing project dependencies.
- Download and install 64-bi
阅读完整原文

项目深度分析 AI 生成

跨平台一键式系统级校准客户端 (Desktop/Mobile)

产品构想AutoEq本身仅输出参数而无法直接作为系统均衡器运行。封装底层AutoEq算法与数据库,打造集成了虚拟声卡驱动/系统音频劫持的一站式均衡播放应用,免除用户手动导入第三方EQ工具的繁琐流程。
核心功能自动识别耳机型号并一键载入最优曲线、内置轻量系统音频滤波引擎、多模式音效(游戏、人声、低音增强、Harman曲线切换)
目标用户小白影音爱好者、游戏玩家、Mac/Windows日常耳机用户
难度/周期高 · 3-6个月 · 成本:开发设备与平台开发者账号费用(如Apple Developer、Windows驱动签名)、日常带宽成本
收费模式买断制独立软件(如$19.99/买断)或订阅制增值服务(云端最新耳机预设同步)
竞争风险跨平台系统音频底层API适配难度大(如macOS虚拟声卡驱动权限);市场已有SoundSource、EqualizerAPO等传统工具竞争
依据 已验证事实

耳机测量数据与均衡算法云端 API (B2B SaaS)

产品构想将仓库庞大的耳机测量数据库(oratory1990、crinacle等整合数据)与目标曲线拟合算法封装为标准 RESTful API / SDK,面向音乐播放器、流媒体软件或耳机硬件App提供云端EQ配置查询与生成服务。
核心功能按耳机品牌型号查询频响曲线与参数化EQ建议、根据目标曲线实时计算biquad/FIR滤波器系数、云端测量数据持续同步更新
目标用户流媒体播放器开发者、音频APP厂商、蓝牙耳机伴侣App团队
难度/周期中等 · 1-2个月 · 成本:轻量云服务器(CPU密集型但计算量小,成本低)
收费模式按API调用量计费的阶梯订阅制(SaaS Tier)或企业年费授权
竞争风险第三方测量数据(如oratory1990、crinacle)的商用版权与授权合规风险(尚需验证的假设)
依据 数据支持的判断

个性化听感校准与定制化音效调优服务 (Web端增值)

产品构想在Web端(类似autoeq.app)增加基于网页端听音测试(测听用户自身听力衰减曲线)并与耳机硬件频响曲线叠加计算,生成专属于个人的听觉补偿校准文件(支持导出到Qudelix 5K、MiniDSP等发烧硬件)。
核心功能纯网页端听力测听向导、个性化听力损失补偿算法与耳机靶线融合、针对主流硬件EQ(PEQ/FIR/Convolution脉冲响应)的一键格式导出
目标用户Hi-Fi耳机发烧友、有轻度听力衰减的音乐爱好者、音频极客
难度/周期中等 · 1-3个月 · 成本:Web托管与静态加速服务器成本(极低)
收费模式增值导出功能付费(单次解锁或高级会员制);发烧硬件联盟分销(如耳放、蓝牙接收器)
竞争风险听力测试受限于回放环境和音量校准,结果偏差可能影响听感体验
依据 AI推测
AI 基于仓库公开数据分析生成,含推测成分,不构成收益承诺。
报告会保存到 个人中心

竞品与相似项目 GitHub Search 真实检索

相似项目数据正在完善中,暂不展示(避免误导)

项目优势与风险

技术成熟度创建于 2018-03-04,近 30 天仍在推送
社区活跃Star 16,441 / Fork 2,568 / Issue 240(数据支持,可自行核实)
许可证MIT
主要风险上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价

安装与使用

此项目未提供 Docker 镜像,安装步骤以原仓库 README 为准(涉及依赖安装与环境配置,对新手门槛较高)。