DeepCamera
Enrichment pendingOpen-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 — watches, understand
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Full report- Maintenance
- Active (23d since push)
- As of today · Source: github_public_v1
- Provenance
- Not a fork · Organization account
- As of today · Source: github_public_v1
- Security (OSV)
- No lockfile
- As of today · Source: none
Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.
Overview
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 — watches, understands, remembers & guards your home via Telegram, Discord or Slack. Pluggable AI skills. OpenAI, Google, Anthropic or local AI. Runs on Mac Mini & AI PC.
Capability facts
- Languages
- javascript
Source: github.language · Jul 11, 2026
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README
🚀 Getting Started with SharpAI Aegis
The easiest way to run DeepCamera's AI skills. Aegis connects everything — cameras, models, skills, and you.
- 📷 Connect cameras in seconds — add RTSP/ONVIF cameras, webcams, or iPhone cameras for a quick test
- 🤖 Built-in local LLM & VLM — llama-server included, no separate setup needed
- 📦 One-click skill deployment — install skills from the catalog with AI-assisted troubleshooting
- 🔽 One-click HuggingFace downloads — browse and run Qwen, DeepSeek, SmolVLM, LLaVA, MiniCPM-V
- 📊 Find the best VLM for your machine — benchmark models on your own hardware with HomeSec-Bench
- 💬 Talk to your guard — via Telegram, Discord, or Slack. Ask what happened, tell it what to watch for, get AI-reasoned answers with footage.
Hardware Acceleration
The shared env_config.py auto-detects your GPU and converts the model to the fastest native format — zero manual setup:
| Your Hardware | Optimized Format | Runtime | Speedup vs PyTorch |
|---|---|---|---|
| NVIDIA GPU (RTX, Jetson) | TensorRT .engine | CUDA | 3-5x |
| Apple Silicon (M1–M4) | CoreML .mlpackage | ANE + GPU | ~2x |
| Intel (CPU, iGPU, NPU) | OpenVINO IR .xml | OpenVINO | 2-3x |
| AMD GPU (RX, MI) | ONNX Runtime | ROCm | 1.5-2x |
| Any CPU | ONNX Runtime | CPU | ~1.5x |
| Google Coral USB Accelerator | Edge TPU .tflite | ai-edge-litert + libedgetpu | ~4ms flat |