OpenVINO — real-time object detection via Docker (NCS2, Intel GPU, CPU)
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvino --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .claude/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .claude/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvinoType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvino --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .agents/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .agents/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvino --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .cursor/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .cursor/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/SharpAI/DeepCamera.git --path skills/detection/yolo-detection-2026-openvino--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvino --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .gemini/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .gemini/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvinoInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .github/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .github/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install SharpAI/DeepCamera yolo-detection-2026-openvino --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/SharpAI/DeepCamera.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/detection/yolo-detection-2026-openvino .opencode/skills/yolo-detection-2026-openvino && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "yolo-detection-2026-openvino" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-openvino into .opencode/skills/yolo-detection-2026-openvino/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-openvino", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
yolo-detection-2026-openvinoOpenVINO — real-time object detection via Docker (NCS2, Intel GPU, CPU)
Yolo Detection 2026 Openvino is an agent skill from SharpAI/DeepCamera. OpenVINO — real-time object detection via Docker (NCS2, Intel GPU, CPU)
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts (for example `config.yaml`, `deploy.sh` and `docker-compose.yml`).
It sits in AI & LLM Engineering, covering Computer vision and Containers. It works with Docker. The repository describes itself as: Open-Source AI Camera Skills Platform, AI NVR & CCTV Surveillance. Local VLM video analysis with Qwen, DeepSeek, SmolVLM, LLaVA, YOLO26. LLM-powered agentic security camera agent… The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 933dcc7. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (Python, Batch and Shell), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Yolo Detection 2026 Openvino loads about 1.3k tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 212 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from SharpAI/DeepCamera at commit 933dcc7, republished under its MIT licence (© SharpAI). 212 words, ~1,325 tokens.
.claude/skills/yolo-detection-2026-openvino/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.Real-time object detection using Intel OpenVINO runtime. Runs inside Docker for cross-platform support. Supports Intel NCS2 USB stick, Intel integrated GPU, Intel Arc discrete GPU, and any x86_64 CPU.
┌─────────────────────────────────────────────────────┐
│ Host (Aegis-AI) │
│ frame.jpg → /tmp/aegis_detection/ │
│ stdin ──→ ┌──────────────────────────────┐ │
│ │ Docker Container │ │
│ │ detect.py │ │
│ │ ├─ loads OpenVINO IR model │ │
│ │ ├─ reads frame from volume │ │
│ │ └─ runs inference on device │ │
│ stdout ←── │ → JSONL detections │ │
│ └──────────────────────────────┘ │
│ USB ──→ /dev/bus/usb (NCS2) │
│ DRI ──→ /dev/dri (Intel GPU) │
└─────────────────────────────────────────────────────┘/tmp/aegis_detection/ volumeframe event via stdin JSONL to Docker containerdetect.py reads frame, runs inference via OpenVINOdetections event via stdout JSONLyolo-detection-2026 — Aegis sees no difference# Intel GPU and NCS2 auto-detected via /dev/dri and /dev/bus/usb
# Docker uses --device flags for direct device access
./deploy.sh# Docker Desktop USB/IP handles NCS2 passthrough
# CPU fallback always available
./deploy.sh# Docker Desktop 4.35+ with USB/IP support
# Or WSL2 backend with usbipd-win for NCS2
.\deploy.batShips without a pre-compiled model by default. On first run, detect.py will auto-download yolo26n.pt and export to OpenVINO IR format. To pre-export:
# Runs on any platform (unlike Edge TPU compilation)
python scripts/compile_model.py --model yolo26n --size 640 --precision FP16| Device | Flag | Precision | ~Speed |
|---|---|---|---|
| Intel NCS2 | MYRIAD | FP16 | ~15ms |
| Intel iGPU | GPU | FP16/INT8 | ~8ms |
| Intel Arc | GPU | FP16/INT8 | ~4ms |
| Any CPU | CPU | FP32/INT8 | ~25ms |
| Auto | AUTO | Best | Auto |
Same JSONL as yolo-detection-2026:
{"event": "ready", "model": "yolo26n_openvino", "device": "GPU", "format": "openvino_ir", "classes": 80}
{"event": "detections", "frame_id": 42, "camera_id": "front_door", "objects": [{"class": "person", "confidence": 0.85, "bbox": [100, 50, 300, 400]}]}
{"event": "perf_stats", "total_frames": 50, "timings_ms": {"inference": {"avg": 8.1, "p50": 7.9, "p95": 10.2}}}[x_min, y_min, x_max, y_max] — pixel coordinates (xyxy).
./deploy.shThe deployer builds the Docker image locally, probes for OpenVINO devices, and sets the runtime command. No packages pulled from external registries beyond Docker base images and pip dependencies.
© SharpAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 11 other files (scripts) in skills/detection/yolo-detection-2026-openvino of SharpAI/DeepCamera.
Open the folder on GitHubat commit 933dcc7
Yolo Detection 2026 Openvino next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Yolo Detection 2026 Openvino this skillSharpAI/DeepCamera | 3.1k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Metro AI App Recipeopen-edge-platform/edge-ai-suites | 140 | — | ~4.4k | Automated safety check: Notes | Apache-2.0 | |
| Safactory WorkflowsAI45Lab/SAfactory | 236 | — | ~1.8k | Automated safety check: Pass | None | |
| Docker Agent Rundocker/skills | 552 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Opik Local Dev Environmentcomet-ml/opik | 22k | — | ~734 | Automated safety check: Pass | Apache-2.0 | |
| Generate Nemo Gym Envadithya-s-k/FineEnvs | 461 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 |
open-edge-platform/edge-ai-suites
Stand up a complete, ready-to-run computer-vision analytics stack on Intel hardware with one Docker Compose command — point it at your video sources and an OpenVINO/ONNX model to get live annotated…
AI45Lab/SAfactory
Integrate a benchmark or custom environment into SAfactory using fixed adapter templates and local contract tests, optionally run Docker/RJob evaluation, or prepare GRPO/RL training.
docker/skills
A skill your agent uses when running a Docker Agent with docker agent run, choosing a safety/approval mode, using the --sandbox isolation flag, setting up aliases, or troubleshooting a run (missing…
comet-ml/opik
Starts, rebuilds, and troubleshoots the Opik local dev stack, including an optional Comet Platform integration mode for the Opik team.
adithya-s-k/FineEnvs
Builds a NeMo Gym (NVIDIA) variant of an RL environment. An agent skill from adithya-s-k/FineEnvs.
NVIDIA/cosmos-framework
Diagnose and fix Cosmos3 environment, installation, and runtime errors.
SharpAI/DeepCamera
AI-assisted dataset annotation with COCO export — bbox, SAM2, DINOv3 methods
SharpAI/DeepCamera
Real-time depth map privacy transforms using Depth Anything v2 (CoreML + PyTorch)
SharpAI/DeepCamera
Interactive click-to-segment using Segment Anything 2 — AI-assisted labeling for Annotation Studio
SharpAI/DeepCamera
YOLO 2026 — state-of-the-art real-time object detection. An agent skill from SharpAI/DeepCamera.
SharpAI/DeepCamera
Google Coral Edge TPU — real-time object detection natively (macOS / Linux)
SharpAI/DeepCamera
Google Coral Edge TPU — real-time object detection natively via Windows WSL
Works with
Categories
OpenVINO — real-time object detection via Docker (NCS2, Intel GPU, CPU). Yolo Detection 2026 Openvino is an agent skill from SharpAI/DeepCamera.
Yolo Detection 2026 Openvino fits situations like: tasks that involve Computer vision; tasks that involve Containers.
Run `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a claude-code`. Or copy the skill folder (skills/detection/yolo-detection-2026-openvino in SharpAI/DeepCamera) into .claude/skills/yolo-detection-2026-openvino in your project. Claude Code loads it when a task matches its description.
Run `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a codex`. Or copy the skill folder (skills/detection/yolo-detection-2026-openvino in SharpAI/DeepCamera) into .agents/skills/yolo-detection-2026-openvino in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-openvino -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/yolo-detection-2026-openvino, .gemini/skills/yolo-detection-2026-openvino, .github/skills/yolo-detection-2026-openvino and .opencode/skills/yolo-detection-2026-openvino in your project.
Going by SKILL.md and its folder, Yolo Detection 2026 Openvino needs Python, Windows cmd and a shell for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; A Bash shell; Docker.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Yolo Detection 2026 Openvino is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Yolo Detection 2026 Openvino: Metro AI App Recipe (open-edge-platform/edge-ai-suites, 140 stars), Safactory Workflows (AI45Lab/SAfactory, 236 stars), Docker Agent Run (docker/skills, 552 stars) and Opik Local Dev Environment (comet-ml/opik, 22k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
SharpAI (a GitHub organization) maintains it in SharpAI/DeepCamera, which has 3,092 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 17, 2026.
Source: SharpAI/DeepCamera on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
