docs: make Chinese README the default

README.md

@@ -1,3 +1,9 @@
+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/rerun-io/rerun) · [上游 README](https://github.com/rerun-io/rerun/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
 <h3 align="center">
   <a href="https://www.rerun.io/">
     <img width="1000" height="200" alt="Banner with Rerun logo" src="https://static.rerun.io/d0f5443d4803cac65c73fcc064936c09f5e7f208_rerun_banner.png" />
@@ -13,28 +19,28 @@
   <a href="https://discord.gg/Gcm8BbTaAj">                              <img alt="Rerun Discord"  src="https://img.shields.io/discord/1062300748202921994?label=Rerun%20Discord"> </a>
 </h3>
 
-# The data layer for physical AI
+# 物理 AI 的数据层
 
-Log, query, visualize, and stream to training on shared columnar storage built for multimodal data.
+在专为多模态数据构建的共享列式存储上记录、查询、可视化，并流式传输至训练。
 
-**What it does:** Rerun ingests multi-rate, multimodal data (images, point clouds, transforms, time series, joint states, video) from many sources and formats (robot logs, human-data rigs, sim, web video; MCAP, rrd, LeRobot). The built-in viewer renders everything in sync, in realtime: scrub episodes, compare sensors side-by-side, watch CV pipelines run live. The same data is queryable with [dataframes](https://rerun.io/docs/howto/query-and-transform/get-data-out) or SQL, and streams directly into training. Built in Rust on column-chunk storage purpose-built for multi-rate physical data. SDKs in Python, Rust, and C++.
+**功能概述：** Rerun 摄取多速率、多模态数据（图像、点云、变换、时间序列、关节状态、视频），来源和格式多样（机器人日志、人体数据采集设备、仿真、网络视频；MCAP、rrd、LeRobot）。内置查看器可实时同步渲染一切：拖动回放片段、并排对比传感器、实时观看 CV 流水线运行。同一批数据可通过 [dataframes](https://rerun.io/docs/howto/query-and-transform/get-data-out) 或 SQL 查询，并直接流式传输到训练中。基于 Rust 构建，采用专为多速率物理数据设计的列块（column-chunk）存储。提供 Python、Rust 和 C++ SDK。
 
-**Quickstart:** `pip install rerun-sdk` — log your first multimodal data and see it in the viewer in under 2 minutes.
+**快速入门：** `pip install rerun-sdk` — 在 2 分钟内记录你的第一条多模态数据，并在查看器中看到它。
 
-* [Run the Rerun Viewer in your browser](https://www.rerun.io/viewer)
-* [Read about what Rerun is and who it is for](https://www.rerun.io/docs/overview/what-is-rerun)
+* [在浏览器中运行 Rerun Viewer](https://www.rerun.io/viewer)
+* [了解 Rerun 是什么以及面向哪些用户](https://www.rerun.io/docs/overview/what-is-rerun)
 
-### Use cases
-- Ingest robot logs, egocentric/UMI rigs, sim, and web video into one substrate
-- Run CV pipelines (SLAM, hand tracking, motion retargeting) as table edits
-- Query raw, intermediate, and derived data with dataframes or SQL
-- Visualize multi-rate, multimodal sequences across the pipeline
-- Stream dataset mixes directly to training — no export jobs, no stale copies
+### 使用场景
+- 将机器人日志、第一人称/UMI 采集设备、仿真和网络视频摄入同一底层存储
+- 将 CV 流水线（SLAM、手部追踪、动作重定向）作为表编辑运行
+- 使用 dataframes 或 SQL 查询原始、中间和派生数据
+- 在整条流水线中可视化多速率、多模态序列
+- 将数据集混合直接流式传输到训练 — 无需导出任务，无需陈旧副本
 
-### Data types
-Multi-rate, multimodal, spatial: images, point clouds, time series, tensors, transforms, joint states, video. Preserved end-to-end.
+### 数据类型
+多速率、多模态、空间数据：图像、点云、时间序列、张量、变换、关节状态、视频。端到端完整保留。
 
-### A short taste
+### 快速体验
 ```py
 import rerun as rr  # pip install rerun-sdk
 
@@ -62,115 +68,115 @@ rr.log("path/to/points", rr.Points3D(positions, colors=colors))
   </picture>
 </p>
 
-## Getting started
+## 入门指南
 * [**C++**](https://www.rerun.io/docs/getting-started/data-in/cpp)
-* [**Python**](https://www.rerun.io/docs/getting-started/data-in/python): `pip install rerun-sdk` or on [`conda`](https://github.com/conda-forge/rerun-sdk-feedstock)
+* [**Python**](https://www.rerun.io/docs/getting-started/data-in/python): `pip install rerun-sdk` 或 [`conda`](https://github.com/conda-forge/rerun-sdk-feedstock)
 * [**Rust**](https://www.rerun.io/docs/getting-started/data-in/rust): `cargo add rerun`
 
-### Installing the Rerun Viewer binary
-To stream log data over the network or load our `.rrd` data files you also need the `rerun` binary.
-It can be installed with `pip install rerun-sdk` or with `cargo install rerun-cli --locked --features nasm` (see note below).
-Note that only the Python SDK comes bundled with the Viewer whereas C++ & Rust always rely on a separate install.
+### 安装 Rerun Viewer 二进制程序
+若要通过网络流式传输日志数据或加载我们的 `.rrd` 数据文件，你还需要 `rerun` 二进制程序。
+可通过 `pip install rerun-sdk` 或 `cargo install rerun-cli --locked --features nasm` 安装（见下方说明）。
+请注意，只有 Python SDK 自带 Viewer，而 C++ 和 Rust 始终需要单独安装。
 
-**Note**: the `nasm` Cargo feature requires the [`nasm`](https://github.com/netwide-assembler/nasm) CLI to be installed and available in your path.
-Alternatively, you may skip enabling this feature, but this may result in inferior video decoding performance.
+**说明**：`nasm` Cargo 功能要求已安装 [`nasm`](https://github.com/netwide-assembler/nasm) CLI，并在 PATH 中可用。
+你也可以选择不启用该功能，但这可能导致视频解码性能下降。
 
-You should now be able to run `rerun --help` in any terminal.
+现在你应该可以在任意终端中运行 `rerun --help`。
 
 
-### Documentation
-- 📚 [High-level docs](https://rerun.io/docs)
-- ⏃ [Loggable Types](https://www.rerun.io/docs/reference/types)
-- ⚙️ [Examples](https://rerun.io/examples)
-- 📖 [Code snippets](./docs/snippets/INDEX.md)
-- 🌊 [C++ API docs](https://ref.rerun.io/docs/cpp)
-- 🐍 [Python API docs](https://ref.rerun.io/docs/python)
-- 🦀 [Rust API docs](https://docs.rs/rerun/)
-- ⁉️ [Troubleshooting](https://www.rerun.io/docs/overview/installing-rerun/troubleshooting)
+### 文档
+- 📚 [高层文档](https://rerun.io/docs)
+- ⏃ [可记录类型（Loggable Types）](https://www.rerun.io/docs/reference/types)
+- ⚙️ [示例](https://rerun.io/examples)
+- 📖 [代码片段](./docs/snippets/INDEX.md)
+- 🌊 [C++ API 文档](https://ref.rerun.io/docs/cpp)
+- 🐍 [Python API 文档](https://ref.rerun.io/docs/python)
+- 🦀 [Rust API 文档](https://docs.rs/rerun/)
+- ⁉️ [故障排除](https://www.rerun.io/docs/overview/installing-rerun/troubleshooting)
 
 
-### Agent skills
-This repo ships a set of agent skills that help coding agents write Rerun code.
+### Agent 技能
+本仓库提供一组 agent 技能，帮助编码 agent 编写 Rerun 代码。
 
-Install them into your agent with the `skills` CLI:
+使用 `skills` CLI 将其安装到你的 agent 中：
 
 ```sh
 npx skills add rerun-io/rerun
 ```
 
-The skills themselves live in [`skills/`](./skills) if you want to read them directly.
+如需直接阅读，技能文件位于 [`skills/`](./skills)。
 
 
-## Status
-We are in active development.
-There are many features we want to add, and the API is still evolving.
-_Expect breaking changes!_
+## 状态
+我们正处于积极开发中。
+还有许多功能计划添加，API 仍在演进。
+_预计会有破坏性变更！_
 
-Some shortcomings:
-* [The viewer slows down when there are too many entities](https://github.com/rerun-io/rerun/issues/7115)
-* [Multi-million point clouds can be slow](https://github.com/rerun-io/rerun/issues/1136)
+部分已知不足：
+* [实体过多时查看器会变慢](https://github.com/rerun-io/rerun/issues/7115)
+* [数百万点规模的点云可能较慢](https://github.com/rerun-io/rerun/issues/1136)
 
 
-## What is Rerun for?
+## Rerun 适用于什么场景？
 
-Rerun is built to help you understand and improve complex processes that include rich multimodal data, like 2D, 3D, text, time series, tensors, etc.
-It is used in many industries, including robotics, simulation, computer vision,
-or anything that involves a lot of sensors or other signals that evolve over time.
+Rerun 旨在帮助你理解和改进包含丰富多模态数据的复杂流程，例如 2D、3D、文本、时间序列、张量等。
+它广泛应用于机器人、仿真、计算机视觉等行业，
+或任何涉及大量随时间演化的传感器或其他信号的领域。
 
-### Example use case
-Say you're building a vacuum cleaning robot and it keeps running into walls. Why is it doing that? You need some tool to debug it, but a normal debugger isn't gonna be helpful. Similarly, just logging text won't be very helpful either. The robot may log "Going through doorway" but that won't explain why it thinks the wall is a door.
+### 示例用场景
+假设你正在开发一台吸尘机器人，它总是撞墙。为什么会这样？你需要某种调试工具，但普通调试器帮不上忙。同样，仅记录文本也作用有限。机器人可能记录「正在穿过门道」，但这无法解释它为何把墙当成门。
 
-What you need is a visual and temporal debugger, that can log all the different representations of the world the robots holds in its little head, such as:
+你需要的是一种可视化、时序化的调试器，能够记录机器人「小脑袋」里对世界的一切不同表征，例如：
 
-* RGB camera feed
-* depth images
-* lidar scan
-* segmentation image (how the robot interprets what it sees)
-* its 3D map of the apartment
-* all the objects the robot has detected (or thinks it has detected), as 3D shapes in the 3D map
-* its confidence in its prediction
-* etc
+* RGB 摄像头画面
+* 深度图像
+* 激光雷达扫描
+* 分割图像（机器人如何解读所见内容）
+* 公寓的 3D 地图
+* 机器人检测到（或自认为检测到）的所有物体，以 3D 形状呈现在 3D 地图中
+* 对其预测的置信度
+* 等等
 
-You also want to see how all these streams of data evolve over time so you can go back and pinpoint exactly what went wrong, when and why.
+你还希望看到这些数据流如何随时间演化，以便回溯并精确定位出了什么问题、何时发生以及原因。
 
-Maybe it turns out that a glare from the sun hit one of the sensors in the wrong way, confusing the segmentation network leading to bad object detection. Or maybe it was a bug in the lidar scanning code. Or maybe the robot thought it was somewhere else in the apartment, because its odometry was broken. Or it could be one of a thousand other things. Rerun will help you find out!
+也许最终发现是阳光眩光以错误方式照射了某个传感器，导致分割网络混淆并引发错误的物体检测。也可能是激光雷达扫描代码中的 bug。或者机器人以为自己位于公寓的其他位置，因为里程计出了问题。也可能是上千种其他原因之一。Rerun 会帮你找出答案！
 
-But seeing the world from the point of the view of the robot is not just for debugging - it will also give you ideas on how to improve the algorithms, new test cases to set up, or datasets to collect. It will also let you explain the brains of the robot to your colleagues, boss, and customers. And so on. Seeing is believing, and an image is worth a thousand words, and multimodal temporal logging is worth a thousand images :)
+但从机器人视角观察世界不仅用于调试 — 它还能启发你改进算法、设计新的测试用例或收集数据集。它还能让你向同事、老板和客户解释机器人的「大脑」。诸如此类。眼见为实，一图胜千言，而多模态时序日志的价值又胜过千张图像 :)
 
-While seeing and understanding your data is core to making progress in robotics, there is one more thing:
-You can also use the data you collected for visualization to create new datasets for training and evaluating the models and algorithms that run on your robot.
-Rerun provides query APIs to make it easy to extract clean datasets from your recording for exactly that purpose.
+虽然查看和理解数据是机器人领域取得进展的核心，还有一点也很重要：
+你还可以将用于可视化的采集数据，用来创建新的数据集，以训练和评估在机器人上运行的模型与算法。
+Rerun 提供查询 API，可轻松从你的录制数据中提取干净的数据集，正是为了这一目的。
 
-Of course, Rerun is useful for much more than just robots. Any time you have any form of sensors, or 2D or 3D state evolving over time, Rerun is a great tool.
+当然，Rerun 的用途远不止机器人。只要你拥有任何形式的传感器，或随时间演变的 2D/3D 状态，Rerun 都是一款出色的工具。
 
 ### Rerun vs. Rviz
 
-When coming from pure visualization tools like [RViz](https://docs.ros.org/en/rolling/Tutorials/Intermediate/RViz/RViz-Main.html), you might be used to seeing the latest data only.
-Rerun is more than a pure visualization solution, it provides a platform for multimodal data with a powerful visualizer, storage model and query engine (see also: [*"What is Rerun?"*](https://rerun.io/docs/overview/what-is-rerun)).
-In robotics, you can use Rerun e.g. to record test runs, manage and query training data, visually debug live streams or recordings (also from third-party formats like [MCAP](https://rerun.io/docs/howto/logging-and-ingestion/mcap)) and much more.
+若你习惯了 [RViz](https://docs.ros.org/en/rolling/Tutorials/Intermediate/RViz/RViz-Main.html), 等纯可视化工具，可能只会看到最新数据。
+Rerun 不仅仅是纯可视化方案，它提供了多模态数据平台，配备强大的可视化器、存储模型和查询引擎（另见：[*"What is Rerun?"*](https://rerun.io/docs/overview/what-is-rerun)).
+在机器人领域，你可以用 Rerun 例如记录测试运行、管理和查询训练数据、可视化调试实时流或录制（也包括 [MCAP](https://rerun.io/docs/howto/logging-and-ingestion/mcap)) 等第三方格式）等等。
 
-So while Rerun makes your data streams visualizable in the viewer, integrating Rerun logging into your robotics applications also opens up the door for leveraging Rerun's broader capabilities.
+因此，虽然 Rerun 能让你的数据流在查看器中可视化，将 Rerun 日志集成到机器人应用中，还能开启利用 Rerun 更广泛能力的大门。
 
-If you are only interested in visualization, the Rerun viewer has powerful features like the ability to go back in time thanks to its time-aware in-memory database.
-You can adjust the size of this buffer to your needs (see [here](https://rerun.io/docs/howto/visualization/limit-ram)), e.g. to a smaller size if you want to use Rerun as an RViz replacement in long-running or memory-constrained applications.
+如果你只对可视化感兴趣，Rerun 查看器拥有强大的功能，例如凭借其具备时间感知能力的内存数据库，可以回溯历史时间。
+你可以根据需求调整该缓冲区的大小（参见[此处](https://rerun.io/docs/howto/visualization/limit-ram)),，例如在长时间运行或内存受限的应用中，若想将 Rerun 用作 RViz 的替代方案，可将其调小。
 
 
-## Business model
-Rerun uses an open-core model. Everything in this repository will stay open source and free (both as in beer and as in freedom).
+## 商业模式
+Rerun 采用 open-core（开放核心）模式。本仓库中的所有内容将保持开源且免费（既指免费啤酒，也指自由使用）。
 
-We are also building Rerun Hub, a scalable catalog for robotic data.
-Right now that is only available for a few select design partners.
-[Click here if you're interested](https://rerun.io/pricing).
+我们还在构建 Rerun Hub，一个可扩展的机器人数据目录。
+目前它仅向少数精选的设计合作伙伴开放。
+[如有兴趣请点击此处](https://rerun.io/pricing).
 
-The Rerun open source project targets the needs of individual developers.
-The commercial product targets the needs specific to teams that build and run computer vision and robotics products.
+Rerun 开源项目面向个人开发者的需求。
+商业产品则面向构建和运行计算机视觉与机器人产品的团队所特有的需求。
 
-## How to cite Rerun
+## 如何引用 Rerun
 
-When using Rerun in your research, please cite it to acknowledge its contribution to your work. This can be done by
-including a reference to Rerun in the software or methods section of your paper.
+在研究中使用 Rerun 时，请引用它以认可其对你工作的贡献。你可以
+在论文的软件或方法部分加入对 Rerun 的引用。
 
-Suggested citation format:
+建议引用格式：
 
 ```bibtex
 @software{RerunSDK,
@@ -186,23 +192,23 @@ Suggested citation format:
 }
 ```
 
-Please replace "insert version number" with the version of Rerun you used and "insert date of usage" with the date(s)
-you used the tool in your research.
-This citation format helps ensure that Rerun's development team receives appropriate credit for their work and
-facilitates the tool's discovery by other researchers.
+请将 "insert version number" 替换为你所使用的 Rerun 版本，将 "insert date of usage" 替换为你在研究中
+使用该工具的日期。
+该引用格式有助于确保 Rerun 开发团队获得应有的认可，
+并便于其他研究者发现这一工具。
 
-# Development
+# 开发
 * [`ARCHITECTURE.md`](ARCHITECTURE.md)
 * [`CODE_OF_CONDUCT.md`](CODE_OF_CONDUCT.md)
 * [`CODE_STYLE.md`](CODE_STYLE.md)
 * [`CONTRIBUTING.md`](CONTRIBUTING.md)
 * [`BUILD.md`](BUILD.md)
-* [`rerun_py/README.md`](rerun_py/README.md) - instructions for Python SDK
-* [`rerun_cpp/README.md`](rerun_cpp/README.md) - instructions for C++ SDK
+* [`rerun_py/README.md`](rerun_py/README.md) - Python SDK 使用说明
+* [`rerun_cpp/README.md`](rerun_cpp/README.md) - C++ SDK 使用说明
 
 
-## Installing a pre-release Python SDK
+## 安装预发布版 Python SDK
 
-1. Download the correct `.whl` from [GitHub Releases](https://github.com/rerun-io/rerun/releases)
-2. Run `pip install rerun_sdk<…>.whl` (replace `<…>` with the actual filename)
-3. Test it: `rerun --version`
+1. 从 [GitHub Releases](https://github.com/rerun-io/rerun/releases) 下载正确的 `.whl`
+2. 运行 `pip install rerun_sdk<…>.whl`（将 `<…>` 替换为实际文件名）
+3. 测试：`rerun --version`