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图像、视频与音频数据分析与数据处理开发者工具 automixbit-perfectdesktop-appflutterfosslastfm
1,123
Stars
28
Forks
6
Watchers
4
Open Issues
待补全
许可证
Dart
语言
2026-09-10
创建时间
2026-11-09
最近更新

项目能做什么

基于 WinUI 的跨平台 YouTube Music 客户端,支持无损播放和发烧级音频功能。
来源:基于仓库元数据 · 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)
<div align="center">

<img src="LastWave_Desktop_v7_1440p.png" alt="LastWave Desktop Banner" width="100%" style="border-radius: 16px;" />

<h1>LastWave</h1>

**Simple Desktop YouTube Music client with WinUI, Bit-Perfect playback, Automix, Lossless addons & advanced audiophile features.**

<br/>

<p align="center">
  <a href="https://t.me/clashprojects" target="_blank"><img src="docs/badges/btn_telegram_support.svg" alt="Telegram Support" height="42" /></a>
  <a href="https://t.me/MaterialYouApp" target="_blank"><img src="docs/badges/btn_telegram_channel.svg" alt="Telegram Channel" height="42" /></a>
  <a href="https://discord.gg/DmyM2p2fMe" target="_blank"><img src="docs/badges/btn_discord.svg" alt="Discord Community" height="42" /></a>
</p>

</div>

---

## Overview

LastWave Desktop is a fast, native desktop YouTube Music client with modern WinUI styling for Windows, Linux, and macOS. It delivers high-fidelity audio playback and a fluid interface that adapts to your music.

For audio lovers, LastWave Desktop packs Bit-Perfect audio output, Lossless FLAC addon support, 15-band parametric equalizer, smooth Automix transitions, Spotify Canvas & integration, and real-time synchronized lyrics, all in a lightweight desktop application.

---

## Features

<table>
  <tr>
    <td width="50%" valign="top">

#### Playback
- Stream any track or video from YouTube Music
- Background audio playback & system media controls
- High-res audio downloads with embedded metadata & `.lrc` lyrics
- Download & cache for offline listening
- Skip silence & sleep timer

</td>
    <td width="50%" valign="top">

#### Audio
- Bit-Perfect audio output (direct hardware bypass)
- Lossless FLAC addon support (up to 24-bit Hi-Res)
- 15-band Parametric Equalizer & AutoEQ presets
- Smart Automix transitions & smooth crossfade
- Audio normalization (ReplayGain / LUFS)
- Real-time tempo & pitch control

</td>
  </tr>
  <tr>
    <td width="50%" valign="top">

#### Lyrics & Discovery
- Live millisecond-synchronized lyrics (LRCLIB)
- Lyrics romanization for non-Latin scripts (Japanese, Korean, etc.)
- Multi-language lyrics translation
- Spotify Canvas & animated video backgrounds
- Personalized quick picks, mood radios & genre discovery
- Search songs, albums, artists, videos, and playlists

</td>
    <td width="50%" valign="top">

#### Library & Account
- Full library management & offline cached library
- Spotify Integration (Account login, Liked Songs sync & deep links)
- Import public playlists from Spotify & Apple Music
- YouTube Music account login & bidirectional sync
- Local & cloud playlists with custom reordering
- Custom audio tag editing & cover art selection

</td>
  </tr>
  <tr>
    <td width="50%" valign="top">

#### Social
- Listen together with friends in real-time
- Built-in Last.fm scrobbler with background tracking
- Safe Discord Rich Presence with live album art
- Export and share lyrics as aesthetic quote cards

</td>
    <td width="50%" valign="top">

#### Interfac
阅读完整原文

项目深度分析 规则生成(AI 未配置)

综合评分 59.6 分。该项目在“个人可实施性”维度得 45 分,“付费可能性”维度得 40.0 分,差异化空间 100.0 分(评分依据见评分卡)。

将 LastWave-Desktop 改造为垂直场景 SaaS

产品构想保留核心能力,针对某一类用户(如某行业团队)做托管版,收取月费。
目标用户有该需求的中小团队 / 独立站长
难度/周期中 · 2~4 周(MVP)
收费模式订阅制(如 ¥29~99/月)
竞争风险需验证付费意愿;注意许可证合规
依据 数据支持的判断:许可证与关键词显示存在商用与付费场景

面向细分需求的二次开发产品

产品构想基于 LastWave-Desktop 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。
目标用户该细分场景用户
难度/周期中 · 2~6 周
收费模式买断制 / 订阅制 / 广告
竞争风险细分需求规模需验证
依据 AI 推测:基于项目主题标签的判断
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
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 2026-09-10,近 30 天仍在推送,发布过 9 个 Release
社区活跃Star 1,123 / Fork 28 / Issue 4(数据支持,可自行核实)
许可证未检测到(需人工确认)
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)。