seeed-projects/seeed-jetson-developtool/cvedia-setup
Claude Code and agent skill by seeed-projects/seeed-jetson-developtool
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Install and run CVEDIA-RT AI inference engine on NVIDIA Jetson for pre-built computer vision applications (crowd estimation, drone detection, vehicle counting, etc.). Requires JetPack 5.1 and a CVEDIA account.
Install
npx vskill@latest install seeed-projects/seeed-jetson-developtool/cvedia-setupSKILL.md
CVEDIA-RT on NVIDIA Jetson
CVEDIA-RT is a modular, cross-platform AI inference engine with pre-loaded applications: crowd estimation, drone detection, fall detection, lane occupancy, vehicle type counter, package detection, and more.
Hardware: NVIDIA Jetson device (tested with reComputer J4012) Software: JetPack 5.1 with all SDK components, internet connection Account: CVEDIA (free sign-up at rt.cvedia.com)
Execution model
Run one phase at a time. After each phase:
- If output contains
[STOP]→ stop immediately, consult the failure decision tree - If output ends with
[OK]→ tell the user "Phase N complete" and proceed
Phase 1 — prerequisites check (~30 s)
[OK] when JetPack 5.1+ with SDK components confirmed. [STOP] if JetPack version is incompatible.
Phase 2 — download CVEDIA-RT (human action + ~5 min)
- Visit https://rt.cvedia.com/ and sign in (or create account)
- Click Download under "NVIDIA Jetson"
- Select "Docker (Recommended)" to download the tar.gz installer
Transfer the file to the Jetson device.
[OK] when tar.gz file is on the Jetson.
Phase 3 — install CVEDIA-RT (~3 min)
Respond to installer prompts as needed.
[OK] when installation completes without errors.
Phase 4 — run CVEDIA-RT (~1 min)
With internet (first run, downloads models):
Without internet (after first online run):
Expected: CVEDIA-RT application opens with pre-loaded solutions.
[OK] when the application UI is visible.
Phase 5 — explore applications (~5 min)
- Click on a solution category (e.g. intelligent-transportation-systems)
- Click the run button next to a solution (e.g. lane-occupancy)
- Wait for model and video files to download
- Configure video source: gear icon → Edit Source → select camera/file → Save Instance
- Stop and restart the application for changes to take effect
[OK] when inference results are visible on the video feed.
Failure decision tree
| Symptom | Action | |
|---|---|---|
install.sh fails | Verify Docker is installed with nvidia runtime. Check JetPack version. | |
run.sh hangs or crashes | Check Docker logs. Ensure sufficient disk space and memory. | |
| Application won't start offline | Must run each solution at least once with internet first. | |
| Video source not working | Stop application, reconfigure source, restart. Check camera connectivity. | |
| Low FPS / poor performance | Ensure JetPack SDK components are installed. Check GPU utilization with tegrastats. |
Reference files
references/source.body.md— Original Seeed wiki with screenshots and application examples
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingseeed_jetson_develop/skills/openclaw/cvedia-setup/SKILL.md
Popularity
- Repository stars
- 57
- Repository forks
- 8
- 7-day trend score
- 0
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