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kleinicke/ply-visualizer

kleinicke/ply-visualizer

3D Visualizer View, compare and inspect point clouds, meshes, gaussian splats, depth maps and disparity images in your editor or browser — with Rust and WebAssembly doing the heavy decoding, so files with millions of points open in seconds.
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add ply-visualizer -- npx -y ply-visualizer
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
21 ★ · kleinicke/ply-visualizer · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 21 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 kleinicke/ply-visualizer;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

3D Visualizer

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

View, compare and inspect point clouds, meshes, gaussian splats, depth maps and
disparity images in your editor or browser — with Rust and WebAssembly doing the
heavy decoding, so files with millions of points open in seconds.
Highlights
- Open large point clouds quickly, including files with millions of points
- Decode the demanding formats in Rust/WebAssembly — LAS, LAZ, E57 and TIFF —
alongside Rust geometry kernels for camera models and scan registration
- Compare multiple point clouds in one view and toggle them independently
- Convert depth and disparity images into point clouds
- Render gaussian splat reconstructions as sorted splats or center point clouds
- Inspect meshes as surfaces, wireframes, points and normals
- Use Eye-Dome Lighting and brightness correction for clearer uncolored geometry
- Measure distances and adjust camera, rotation center and view parameters
- Use the shared viewer on the website
- Try the local
Python package and command-line viewer for 3D
files, NumPy/PyTorch arrays and inline local notebooks
(uv add 3d-visualizer)
- Connect AI agents through the local MCP server to
open scenes, control the camera and inspect rendered screenshots
Supported formats
| Type | Formats |
| ---------------------- | ---------------------------------------------------------------------------------------------- |
| Point clouds | PLY, XYZ, XYZN, XYZRGB, PCD, PTS, NPY, LAS, LAZ, E57, KITTI BIN, Stonex X3A/X3R (experimental) |
| Meshes | PLY, OBJ, STL, OFF, GLTF, GLB, FBX, DAE (Collada), 3DS |
| Gaussian splats | 3DGS PLY, SPZ, SPLAT, KSPLAT, SOG |
| Depth/disparity images | TIFF, PNG, PFM, NPY, NPZ |
| 3D Body Poses | JSON pose data (experimental) |
| Camera Profiles | JSON pose data (experimental) |
Model animation playback and remote URL loading are supported; see
model details and
remote files.
Because .bin and .json are generic extensions, neither is opened with the 3D
Visualizer by default. For KITTI BIN, use **Open With...** or right-click and
choose **Open with 3D Visualizer**. For a supported JSON pose, right-click and
choose **Load JSON as 3D Pose**.
Features
Depth and Disparity to Point Cloud
Convert depth or disparity images into point clouds. Projection settings include
fx, fy, cx, cy, camera distortion models, mono depth scale and bias, PNG
int16 scale and disparity offset.
Eye-Dome Lighting
Use Eye-Dome Lighting to improve depth perception, especially for uncolored
point clouds.
Multiple Point Clouds
Load multiple point clouds into the same view, toggle them independently and
switch between them with Shift-click.
Mesh Inspection
Inspect mesh files with controls for surface, wireframe, points and normals.
This is useful when checking geometry, topology or exported reconstruction
results without leaving the editor.
Gaussian Splatting
Open 3D Gaussian Splatting reconstructions (3DGS PLY, SPZ, SPLAT, KSPLAT, SOG)
and render them as real sorted splats via Spark, or as a
point cloud of the gaussian centers with colors derived from the
spherical-harmonics coefficients. Switch per file with the **✨ Splats** button
in the Files panel. Measurement and picking keep working on the gaussian centers
来源
awesome · https://github.com/kleinicke/ply-visualizer
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