Agent skill · NVIDIA
deepstream-import-vision-model
Use this skill to bring a supported object-detection vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark, and PDF report. Object detection models only.
What it needs
About 7k tokens when loaded.
What this skill does
DeepStream Import Vision Model When this skill is active, read the relevant reference document before starting each phase. Do not rely on memory — reference documents contain exact script paths, bash variable conventions, log filename contracts, and critical parsing rules. Current scope: Object detection models only. Fail fast on classification, segmentation, or other architectures detected in config.json. Model choice — always offer two options Before preflight, browsing, downloads, or file creation, present exactly these two choices. Do not start with only an open-ended model-source prompt. If the user's request already clearly selects a model, confirm the matching choice instead of asking redundantly. 1. Default model (recommended) Use the validated Hugging Face RT-DETR model: 2. Custom object-detection model Ask for one supported source: Hugging Face model ID (organization/model) or full model URL. NVIDIA NGC catalog model URL including its version. Explain that the skill currently rejects classification, segmentation, and other non-detection architectures after inspecting config.json. Do not invent or silently substitute a model when the custom source is missing or unsupported. For a dry run, present the same two choices and simulate discovery, build, benchmark, and report stages without browsing, downloading, launching Docker, writing files, or starting processes. Pipeline Overview Step Phase Reference What it does ------ ------- ----------- -------------- 1–3 Model Acquire references/model-acquire.md Browse HF/NGC, detect format, download ONNX or export SafeTensors 4–5 Engine Build references/engine-build.md Build dynamic TRT engine, run trtexec BS=1 and BS=MAXBS 6–7 DS Pipeline references/pipeline-run.md Custom bbox parser, nvinfer config, single-stream + multi-stream benchmarks 8 Report references/report-generation.md 5 charts, HTML, PDF benchmark report Run the full pipeline autonomously without pausing for confirmation at each step. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/deepstream-import-vision-model