# Yolo Detection 2026 Coral Tpu Macos

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

- Repository: https://github.com/SharpAI/DeepCamera (3124 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-09-17
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -g -a claude-code -y`
Codex: `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -g -a codex -y`
Cursor: `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -g -a cursor -y`
Gemini CLI: `npx skills add SharpAI/DeepCamera --skill yolo-detection-2026-coral-tpu-macos -g -a gemini-cli -y`

## Description

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

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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       │
└─────────────────────────────────────────────────────┘
```

1. Aegis writes camera frame JPEG to shared `/tmp/aegis_detection/` workspace
2. Sends `frame` event via stdin JSONL to the local Python instance
3. `detect.py` invokes PyCoral and executes natively on the mapped USB Edge TPU
4. 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

The rest: https://github.com/SharpAI/DeepCamera/blob/HEAD/skills/detection/yolo-detection-2026-coral-tpu-macos/SKILL.md