Agent skill

Yolo Detection 2026 Coral Tpu macOS

Google Coral Edge TPU — real-time object detection natively (macOS / Linux)

MITAuto-check passedAI & LLM Engineering

Install Yolo Detection 2026 Coral Tpu macOS

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ 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-coral-tpu-macos .claude/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .claude/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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

$skill-installer install https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos

Type 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.

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-coral-tpu-macos .agents/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .agents/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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.

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-coral-tpu-macos .cursor/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .cursor/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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

$ gemini skills install https://github.com/SharpAI/DeepCamera.git --path skills/detection/yolo-detection-2026-coral-tpu-macos

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-coral-tpu-macos .gemini/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .gemini/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos

Installs 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).

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ 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-coral-tpu-macos .github/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .github/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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.

skills CLI

$ npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install SharpAI/DeepCamera yolo-detection-2026-coral-tpu-macos --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-coral-tpu-macos .opencode/skills/yolo-detection-2026-coral-tpu-macos && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "yolo-detection-2026-coral-tpu-macos" agent skill from https://github.com/SharpAI/DeepCamera/tree/master/skills/detection/yolo-detection-2026-coral-tpu-macos into .opencode/skills/yolo-detection-2026-coral-tpu-macos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "yolo-detection-2026-coral-tpu-macos", 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.

Facts

Skill name: yolo-detection-2026-coral-tpu-macos
GitHub stars: 3.1k
Token cost: ~1.2k tokens
SKILL.md length: 221 words
Files: 81 (incl. scripts)
Skills in repo: 15
Repo updated: Sep 17, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Google Coral Edge TPU — real-time object detection natively (macOS / Linux)

Works in 4 steps: Aegis writes camera frame JPEG to shared… → Sends frame event via stdin JSONL to the… → detect.py invokes PyCoral and executes… → …
Tasks that involve Computer vision
SKILL.md covers Requirements, How It Works, Platform Setup and Performance, plus 2 more sections
Runs Shell scripts from its folder

What it does

Yolo Detection 2026 Coral Tpu macOS is an agent skill from SharpAI/DeepCamera. Google Coral Edge TPU — real-time object detection natively (macOS / Linux)

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 81 other files, including scripts (for example `.travis.yml`, `CODE_OF_CONDUCT.md` and `CONTRIBUTING.md`).

It sits in AI & LLM Engineering, covering Computer vision. It works with macOS, Linux and Python. 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.

When your agent uses it

Tasks that involve Computer vision

Example prompts

“/yolo-detection-2026-coral-tpu-macos”

Requirements

Python 3
A Bash shell
Docker

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Aegis writes camera frame JPEG to shared /tmp/aegis_detection/ workspace
Sends frame event via stdin JSONL to the local Python instance
detect.py invokes PyCoral and executes natively on the mapped USB Edge TPU
Returns detections event via stdout JSONL

What it can do on your machine

Read from SKILL.md and the folder at commit 933dcc7. It shows what the files ask for, not the result of running them.

Tool permissions
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.
Runs code
Ships 1 file in scripts/ (Shell, from the files we listed), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Yolo Detection 2026 Coral Tpu macOS loads about 1.2k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 221 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~28
When it runs · the whole SKILL.md, loaded when a task matches: ~1.2k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from SharpAI/DeepCamera at commit 933dcc7, republished under its MIT licence (© SharpAI). 221 words, ~1,249 tokens.

Download SKILL.mdSave it as .claude/skills/yolo-detection-2026-coral-tpu-macos/SKILL.md (or your agent's skills folder). This skill also uses 80 other files; get the full folder from GitHub.

name: yolo-detection-2026-coral-tpu-macos
description: Google Coral Edge TPU — real-time object detection natively (macOS / Linux)
version: 1.0.0
icon: assets/icon.png
entry: scripts/detect.py
deploy.linux: deploy.sh
deploy.macos: deploy.sh
runtime: python
requirements.platforms: linux, macos
category: detection
mutex: detection

Coral TPU Object Detection

Real-time object detection natively utilizing the Google Coral Edge TPU accelerator on your local hardware. Detects 80 COCO classes (person, car, dog, cat, etc.) with ~4ms inference on 320x320 input.

Requirements

Python 3.9–3.13

How It Works

┌─────────────────────────────────────────────────────┐
│ Host (Aegis-AI)                                     │
│   frame.jpg → /tmp/aegis_detection/                 │
│   stdin  ──→ ┌──────────────────────────────┐       │
│              │ Native Python Environment     │       │
│              │   detect.py                   │       │
│              │   ├─ loads _edgetpu.tflite     │       │
│              │   ├─ reads frame from disk     │       │
│              │   └─ runs inference on TPU    │       │
│   stdout ←── │   → JSONL detections          │       │
│              └──────────────────────────────┘       │
│   USB ──→ Native System USB / edgetpu drivers       │
└─────────────────────────────────────────────────────┘

Aegis writes camera frame JPEG to shared /tmp/aegis_detection/ workspace
Sends frame event via stdin JSONL to the local Python instance
detect.py invokes PyCoral and executes natively on the mapped USB Edge TPU
Returns detections event via stdout JSONL

Platform Setup

Linux

bash

# Uses the official apt-get google-coral packages natively
./deploy.sh

macOS

bash

# Downloads and installs the libedgetpu OS payload framework inline
./deploy.sh

Important Deployment Notice: The updated deploy.sh script will natively halt execution and prompt you securely for your OS sudo password to securely register the USB drivers (libedgetpu) system-wide. If you refuse the prompt, it gracefully outputs the exact terminal instructions for you to configure it manually.

Performance

Input Size	Inference	On-chip	Notes
320x320	~4ms	100%	Fully on TPU, best for real-time
640x640	~20ms	Partial	Some layers on CPU (model segmented)

Cooling: The USB Accelerator aluminum case acts as a heatsink. If too hot to touch during continuous inference, it will thermal-throttle. Consider active cooling or clock_speed: standard.

Protocol

Same JSONL as yolo-detection-2026:

Skill → Aegis (stdout)

jsonl

{"event": "ready", "model": "yolo26n_edgetpu", "device": "coral", "format": "edgetpu_tflite", "tpu_count": 1, "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": 4.1, "p50": 3.9, "p95": 5.2}}}

Bounding Box Format

[x_min, y_min, x_max, y_max] — pixel coordinates (xyxy).

Installation

Linux / macOS

bash

./deploy.sh

The deployer builds the local Python virtual environment and installs the Edge TPU runtime. No Docker required.

Files

SKILL.md and 80 other files (scripts) in skills/detection/yolo-detection-2026-coral-tpu-macos of SharpAI/DeepCamera.

SKILL.md
.gitignore
.travis.yml
CODE_OF_CONDUCT.md
CONTRIBUTING.md
Contributions.md
LICENSE
README.md
_config.yml
config.yaml
deploy-linux.sh
deploy-macos.sh
deploy.sh
docker-compose.yml
docker/Dockerfile
docker/README.md
docker/compile.sh
docker/docker-compose.yml
docker_out.log
driver
… and 61 more

Open the folder on GitHubat commit 933dcc7

Compare with similar skills

Yolo Detection 2026 Coral Tpu macOS 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.

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Remote Hostslibnativeapi/nativeapi	166	—	~1.3k	Automated safety check: Pass	MIT	today
Crossreviewcoddy-project/coddy-agent	168	—	~3.3k	Automated safety check: Pass	MIT	today

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Questions about Yolo Detection 2026 Coral Tpu macOS

What does Yolo Detection 2026 Coral Tpu macOS do?

Google Coral Edge TPU — real-time object detection natively (macOS / Linux). Yolo Detection 2026 Coral Tpu macOS is an agent skill from SharpAI/DeepCamera.

When should I use Yolo Detection 2026 Coral Tpu macOS?

Yolo Detection 2026 Coral Tpu macOS fits situations like: tasks that involve Computer vision.

How do I install Yolo Detection 2026 Coral Tpu macOS in Claude Code?

Run `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a claude-code`. Or copy the skill folder (skills/detection/yolo-detection-2026-coral-tpu-macos in SharpAI/DeepCamera) into .claude/skills/yolo-detection-2026-coral-tpu-macos in your project. Claude Code loads it when a task matches its description.

How do I install Yolo Detection 2026 Coral Tpu macOS in Codex?

Run `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -a codex`. Or copy the skill folder (skills/detection/yolo-detection-2026-coral-tpu-macos in SharpAI/DeepCamera) into .agents/skills/yolo-detection-2026-coral-tpu-macos in your project. Codex loads it when a task matches its description.

Can I use Yolo Detection 2026 Coral Tpu macOS in Cursor, Gemini CLI or GitHub Copilot?

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-coral-tpu-macos -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-coral-tpu-macos, .gemini/skills/yolo-detection-2026-coral-tpu-macos, .github/skills/yolo-detection-2026-coral-tpu-macos and .opencode/skills/yolo-detection-2026-coral-tpu-macos in your project.

What does Yolo Detection 2026 Coral Tpu macOS need to run?

Going by SKILL.md and its folder, Yolo Detection 2026 Coral Tpu macOS needs a shell for the scripts in its folder. Our summary lists: Python 3; A Bash shell; Docker.

Does Yolo Detection 2026 Coral Tpu macOS access the network?

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.

Is Yolo Detection 2026 Coral Tpu macOS safe to install?

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.

What licence does Yolo Detection 2026 Coral Tpu macOS use?

Yolo Detection 2026 Coral Tpu macOS is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Yolo Detection 2026 Coral Tpu macOS use?

About 1.2k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Yolo Detection 2026 Coral Tpu macOS?

Skills that share tags, products or a category with Yolo Detection 2026 Coral Tpu macOS: Local Asr (ysyecust/lecture-to-notes, 273 stars), Re AI Model (dslsdzc/rev-skills, 135 stars), Apple Container Test Runner (RustPython/RustPython, 22k stars) and Remote Hosts (libnativeapi/nativeapi, 166 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Yolo Detection 2026 Coral Tpu macOS?

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.

Install Yolo Detection 2026 Coral Tpu macOS

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Coral TPU Object Detection

Requirements

How It Works

Platform Setup

Linux

macOS

Performance

Protocol

Skill → Aegis (stdout)

Bounding Box Format

Installation

Linux / macOS

Files

Compare with similar skills

Similar skills

More from SharpAI/DeepCamera

Related

Questions about Yolo Detection 2026 Coral Tpu macOS