# deepstream-generate-pipeline

Builds gst-launch-1.0 commands for DeepStream from a described task. Use it for video or image inference, tracking, streaming, and output handling.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 771 installs · ★ 3735
- Author: NVIDIA
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/NVIDIA/skills/tree/HEAD/skills/deepstream-generate-pipeline/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/deepstream-generate-pipeline

## What it does

The skill asks for the pipeline source, stream count, inference mode, tracker, sink, platform, and transforms. It then retrieves a ready-to-run `gst-launch-1.0` pipeline with BM25 search across more than 270 verified DeepStream pipelines.

Its files include `scripts/generate_pipeline.py` for retrieval and `scripts/validate_pipeline.py` for syntax, element, property, and live-parse checks. It covers local video and images, RTSP streams, USB cameras, test patterns, `nvinfer`, `nvinferserver`, plus NvDCF, IOU, NvSORT, and DeepSORT trackers.

You need Python 3.8+, DeepStream SDK at `/opt/nvidia/deepstream/deepstream/`, and `gst-launch-1.0` with `gst-inspect-1.0` on `PATH`. It requires an x86 dGPU or aarch64 with Jetson or SBSA, so check the target environment first.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill deepstream-generate-pipeline -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/deepstream-generate-pipeline/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/deepstream-generate-pipeline/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill deepstream-generate-pipeline -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/deepstream-generate-pipeline/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill deepstream-generate-pipeline -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/deepstream-generate-pipeline/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install NVIDIA/skills deepstream-generate-pipeline
```

2. **Manually: put the files in place**
- File: `.github/skills/deepstream-generate-pipeline/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill deepstream-generate-pipeline -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/NVIDIA/skills --path skills/deepstream-generate-pipeline
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/deepstream-generate-pipeline/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill deepstream-generate-pipeline -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/NVIDIA/skills/tree/HEAD/skills/deepstream-generate-pipeline/SKILL.md

## When to use it
- build a pipeline for local-video inference
- configure detection and tracking for RTSP streams
- save processed output as MP4, H264, or images
- apply rotation, cropping, or resizing
- validate GStreamer elements and properties

## Example prompts
- Build a pipeline to run inference on an image.
- Create a detection pipeline with NvDCF tracking for 4 RTSP streams and display the output.
- Generate a `gst-launch-1.0` pipeline that processes a video and saves the result as MP4.

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From the same set: [nvidia/skills](https://affpapa.org/en/nevibecode/by/nvidia/skills.md) — 194 cards

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