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reading-render-output

Map Ovrtx render outputs to accessible pixel data on CPU or CUDA.

201|25|Updated Dec 18, 2025
Search Tags:#rendering#cuda#cpu#ovrtx#render-output#render-var
One-click install
npx skills add https://github.com/NVIDIA-Omniverse/ovrtx --skill reading-render-output
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reading-render-output
Source: https://github.com/NVIDIA-Omniverse/ovrtx/tree/main/.agents/skills/reading-render-output
Command: npx skills add https://github.com/NVIDIA-Omniverse/ovrtx --skill reading-render-output

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Mapping rendered outputs to accessible pixel data on CPU or GPU, enabling readable access to render results for processing, storage, or display.

Core Features & Use Cases

  • Access RenderVar data on CPU or CUDA for analysis, visualization, or post-processing.
  • Support for single-tensor outputs (e.g., LdrColor, HdrColor) and multi-tensor render variables with named tensors and params.
  • Guidance for mapping, unmapping, and synchronization across Python and C/C++ code.

Quick Start

Map the render output to the chosen device (CPU or CUDA) and access the underlying data for processing or visualization.

Frequently Asked Questions about reading-render-output

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I read render output pixel data from the Ovrtx render pipeline on CPU or CUDA?▼

Mapping render outputs to accessible pixel data requires selecting a target device, CPU or CUDA, then mapping the render output to read underlying tensor data. This enables analysis, storage, or display of rendered results.

Does Ovrtx render output mapping support both LdrColor and HdrColor render variables?▼

Render output mapping supports single-tensor outputs including LdrColor and HdrColor, plus multi-tensor render variables with named tensors and params. This ensures accessible pixel data across various render variable types.

What's the best way to synchronize render output data when reading it back in Python and C/C++?▼

Proper synchronization involves following guidance for mapping, unmapping, and synchronization across Python and C/C++ code. This careful handling preserves data integrity for downstream processing of render variables.

Why does my render variable tensor shape change when unmapping pixel data on the GPU?▼

Tensor shapes for render variables require careful handling during mapping and unmapping to preserve data integrity. Device selection between CPU and CUDA impacts how tensor shapes are managed during readback.

Can I access multi-tensor render variables with named tensors and params for post-processing?▼

Multi-tensor render variables with named tensors and params are supported for access on CPU or CUDA. This enables readable pixel data for analysis, visualization, or post-processing tasks within the render pipeline.

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