---
title: GLPN Single-View Depth → Point Cloud → Mesh
emoji: 🧱
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
python_version: "3.10"
pinned: true
models:
  - vinvino02/glpn-nyu
tags:
  - depth-estimation
  - 3d-reconstruction
  - point-cloud
  - mesh
  - open3d
  - trimesh
  - transformers
  - gradio
  - single-view
  - computer-vision
---

# Single-View Depth → Point Cloud → Mesh (GLPN + Open3D)

This Space predicts depth from a single RGB image using **GLPN (NYU)**, back-projects to a point cloud, reconstructs a mesh (Ball Pivoting with Poisson fallback), and exports `PLY` and `GLB`.

## How to use
1. Upload one RGB image (indoor works best).
2. Click **Run**.
3. Inspect **Input vs Depth**, **Mesh Preview** (if available), and the **Interactive 3D (GLB)** viewer.
4. Download artifacts from the **Downloads** panel.

## Outputs
- `input_vs_depth.png` – side-by-side original and depth (meters, contrast-clipped)
- `point_cloud.ply` – colorized point cloud
- `mesh.ply` – triangle mesh
- `mesh.glb` – mesh for web viewers, Gradio `Model3D`, and downstream tools
- `mesh_preview.png` – headless snapshot (may be absent in some environments)

## Notes
- **OpenMP warnings fixed** by setting safe thread env vars at the top of `app.py`.
- GPU is optional. The app auto-selects CUDA if available.
- If GLB doesn’t render: check **Logs / Status**. The exporter is skipped if the mesh is empty.
- For crisper meshes, try higher-texture images with clear geometry and lighting.