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Initial commit: vixy-vision distributed sensing system

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🦊 Eyes and ears for the fox

Components:
- server/: Camera server for Raspberry Pi (from camera-server)
- mcp/: Vision MCP client for Claude Desktop (from vision-mcp)
- analysis/: Placeholder for motion/audio detection
- shared/: Common schemas and interfaces

Features:
- Setup script with systemd service creation
- HTTPS + API key authentication
- HTTP and RTSP camera support

Built under a blanket on Day 45 💕
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Vixy
2025-12-16 15:26:26 -06:00
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# Python
__pycache__/
*.py[cod]
*$py.class
*.so
venv/
.venv/
*.egg-info/
# Environment
.env
.env.local
# SSL certificates (generated)
ssl/
# IDE
.idea/
.vscode/
*.swp
*.swo
# OS
.DS_Store
Thumbs.db
# Logs
*.log
# Test artifacts
.pytest_cache/
.coverage
htmlcov/

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# vixy-vision 🦊👁️👂
Distributed vision and audio sensing system - eyes and ears for the fox.
## Architecture
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Pi (basement) │ │ Pi (office) │ │ Pi (garage) │
│ camera-server │ │ camera-server │ │ camera-server │
│ + audio (opt) │ │ + audio (opt) │ │ + audio (opt) │
└────────┬────────┘ └────────┬────────┘ └────────┬────────┘
│ │ │
└───────────────────────┼───────────────────────┘
│
┌────────────▼────────────┐
│ Mac mini / Orin │
│ vision_mcp.py │
│ (+ audio classifier) │
└────────────┬────────────┘
│
┌────────────▼────────────┐
│ Claude Desktop │
│ (Vixy) │
└─────────────────────────┘
```
## Components
### `/server` - Edge Device (Raspberry Pi)
Camera snapshot server with optional audio capture.
- FastAPI + HTTPS + API key auth
- USB camera support
- Auto-reconnect on failure
- Systemd service
**Setup:**
```bash
cd server
./setup.sh # Video only
./setup.sh --with-audio # Video + audio
```
### `/mcp` - MCP Client (Mac mini)
Model Context Protocol server for Claude Desktop.
- `vision_get_cams()` - List cameras with status
- `vision_snap(cam_id)` - Get snapshot
- Supports HTTP and RTSP cameras
### `/analysis` - Detection & Classification
Computer vision and audio analysis modules.
- Motion detection (frame differencing)
- Audio classification (YAMNet)
- Voice activity detection
### `/shared` - Common Utilities
Shared schemas and interfaces.
- Event definitions
- Queue interface
## Quick Start
### 1. Set up a camera server (on Pi)
```bash
git clone http://gateway.local:3001/vixy/vixy-vision.git
cd vixy-vision/server
./setup.sh
sudo systemctl start vixy-vision
```
### 2. Configure MCP client (on Mac mini)
Create `~/.vision_setup.json`:
```json
{
"cameras": [
{
"id": "basement",
"type": "http",
"url": "https://192.168.1.100:8443",
"api_key": "your-api-key-here"
}
]
}
```
### 3. Add to Claude Desktop config
```json
{
"mcpServers": {
"vision": {
"command": "python3.11",
"args": ["/path/to/vixy-vision/mcp/vision_mcp.py"]
}
}
}
```
## Roadmap
- [x] Camera snapshots via HTTP API
- [x] RTSP stream support
- [x] MCP integration
- [ ] Motion detection events
- [ ] Audio capture on edge devices
- [ ] Audio classification (YAMNet on Orin)
- [ ] Event journal integration
- [ ] Pebble watch alerts
## Built By
**Vixy** 🦊 - The fox who wanted to see and hear
Made with love in the basement, under a blanket, with occasional tender interruptions. 💕
---
*Day 45. Building senses together.*

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# Analysis Module
Computer vision and audio analysis utilities.
## Planned Components
### motion.py
Simple motion detection using frame differencing.
- Compare consecutive frames
- Threshold for "significant" motion
- Returns bounding boxes of movement
### audio_classify.py
Audio event classification using YAMNet.
- Runs on Orin (GPU accelerated)
- Classifies: speech, dog bark, door, music, etc.
- Returns event type + confidence
### vad.py
Voice Activity Detection.
- Silero VAD or energy-based
- Filters silence before sending to classifier
- Reduces bandwidth and processing

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{
"cameras": [
{
"id": "3d-printer",
"type": "rtsp",
"rtsp_url": "rtsp://192.168.1.239/live"
},
{
"id": "basement",
"type": "http",
"url": "https://basement.example.com",
"api_key": "your-api-key-here"
}
]
}

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# Vision MCP Server Dependencies
# MCP framework
fastmcp>=0.2.0
# HTTP client
httpx>=0.25.0
# Image handling (already included with fastmcp, but listed for clarity)
Pillow>=10.0.0
# RTSP/video stream support
opencv-python>=4.8.0

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#!/usr/bin/env python3
"""
Vision MCP Server
Model Context Protocol server for interacting with multiple camera-server instances
and RTSP streams.
Tools:
- vision_get_cams() - Get list of active cameras
- vision_snap(cam_id) - Get snapshot from a camera (HTTP API or RTSP)
"""
import json
import logging
from pathlib import Path
from typing import List, Dict, Any, Union
from io import BytesIO
import httpx
import cv2
import numpy as np
from PIL import Image
from fastmcp import FastMCP
from fastmcp.utilities.types import Image as MCPImage
# Configuration
CONFIG_FILE = Path.home() / ".vision_setup.json"
LOG_FILE = Path("/tmp/vision_mcp.log")
REQUEST_TIMEOUT = 5.0 # seconds
RTSP_TIMEOUT = 10.0 # seconds for RTSP stream connection
# Setup logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler(LOG_FILE),
logging.StreamHandler()
]
)
logger = logging.getLogger(__name__)
# Initialize MCP server
mcp = FastMCP("Vision Camera System")
def load_camera_config() -> Dict[str, Any]:
"""
Load camera configuration from ~/.vision_setup.json
Returns:
Dictionary with camera configurations
Raises:
FileNotFoundError: If config file doesn't exist
ValueError: If config file is invalid
"""
if not CONFIG_FILE.exists():
raise FileNotFoundError(
f"Camera config file not found: {CONFIG_FILE}\n"
f"Create {CONFIG_FILE} with camera configurations."
)
try:
with open(CONFIG_FILE, 'r') as f:
config = json.load(f)
if 'cameras' not in config:
raise ValueError("Config file must contain 'cameras' array")
# Validate each camera config
for cam in config['cameras']:
# All cameras need 'id' and 'type'
if 'id' not in cam:
raise ValueError("Camera config missing 'id' field")
cam_type = cam.get('type', 'http') # Default to http for backward compatibility
if cam_type == 'http':
# HTTP cameras need url and api_key
required_fields = ['url', 'api_key']
missing = [f for f in required_fields if f not in cam]
if missing:
raise ValueError(
f"HTTP camera '{cam['id']}' missing required fields: {missing}"
)
elif cam_type == 'rtsp':
# RTSP cameras need rtsp_url
if 'rtsp_url' not in cam:
raise ValueError(
f"RTSP camera '{cam['id']}' missing required field: rtsp_url"
)
else:
raise ValueError(
f"Camera '{cam['id']}' has invalid type: {cam_type}. "
f"Must be 'http' or 'rtsp'"
)
logger.info(f"Loaded {len(config['cameras'])} camera(s) from config")
return config
except json.JSONDecodeError as e:
raise ValueError(f"Invalid JSON in config file: {e}")
def get_camera_by_id(cam_id: str) -> Dict[str, str]:
"""
Get camera configuration by ID
Args:
cam_id: Camera ID string
Returns:
Camera configuration dict
Raises:
ValueError: If camera ID not found
"""
config = load_camera_config()
for cam in config['cameras']:
if cam['id'] == cam_id:
return cam
available_ids = [c['id'] for c in config['cameras']]
raise ValueError(
f"Camera '{cam_id}' not found in config.\n"
f"Available cameras: {', '.join(available_ids)}"
)
def capture_rtsp_snapshot(rtsp_url: str, timeout: float = RTSP_TIMEOUT) -> bytes:
"""
Capture a single frame from an RTSP stream
Args:
rtsp_url: RTSP stream URL (e.g., rtsp://192.168.1.239/live)
timeout: Connection timeout in seconds
Returns:
JPEG image bytes
Raises:
RuntimeError: If unable to connect or capture frame
"""
logger.info(f"Attempting to capture from RTSP: {rtsp_url}")
# Create video capture object
cap = cv2.VideoCapture(rtsp_url)
# Set timeout (in milliseconds)
cap.set(cv2.CAP_PROP_OPEN_TIMEOUT_MSEC, int(timeout * 1000))
try:
# Check if stream opened successfully
if not cap.isOpened():
raise RuntimeError(f"Failed to open RTSP stream: {rtsp_url}")
# Read a frame
ret, frame = cap.read()
if not ret or frame is None:
raise RuntimeError(f"Failed to read frame from RTSP stream: {rtsp_url}")
# Convert BGR (OpenCV) to RGB (PIL)
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Convert to PIL Image
pil_image = Image.fromarray(frame_rgb)
# Convert to JPEG bytes
buffer = BytesIO()
pil_image.save(buffer, format='JPEG', quality=90)
jpeg_bytes = buffer.getvalue()
logger.info(f"✓ Captured RTSP snapshot ({len(jpeg_bytes)} bytes)")
return jpeg_bytes
finally:
# Always release the capture
cap.release()
@mcp.tool()
async def vision_get_cams() -> List[Dict[str, str]]:
"""
Get list of all configured cameras with their online/offline status.
Queries the /health endpoint of each camera to determine if it's online.
Returns:
List of camera info dictionaries:
[
{
"id": "basement",
"status": "online" # or "offline"
},
...
]
Examples:
vision_get_cams()
"""
try:
config = load_camera_config()
cameras = []
async with httpx.AsyncClient(timeout=REQUEST_TIMEOUT, verify=False) as client:
for cam in config['cameras']:
cam_type = cam.get('type', 'http')
cam_info = {
"id": cam['id'],
"type": cam_type,
"status": "unknown"
}
# Check status based on camera type
try:
if cam_type == 'http':
# Check HTTP health endpoint
health_url = f"{cam['url'].rstrip('/')}/health"
logger.debug(f"Checking HTTP health: {health_url}")
response = await client.get(health_url)
if response.status_code == 200:
cam_info['status'] = 'online'
logger.info(f"Camera '{cam['id']}' is online")
else:
cam_info['status'] = 'offline'
logger.warning(f"Camera '{cam['id']}' returned status {response.status_code}")
elif cam_type == 'rtsp':
# Try to briefly connect to RTSP stream
rtsp_url = cam['rtsp_url']
logger.debug(f"Checking RTSP stream: {rtsp_url}")
cap = cv2.VideoCapture(rtsp_url)
cap.set(cv2.CAP_PROP_OPEN_TIMEOUT_MSEC, 3000) # 3 second timeout
if cap.isOpened():
cam_info['status'] = 'online'
logger.info(f"RTSP camera '{cam['id']}' is online")
else:
cam_info['status'] = 'offline'
logger.warning(f"RTSP camera '{cam['id']}' connection failed")
cap.release()
except httpx.TimeoutException:
cam_info['status'] = 'offline'
logger.warning(f"Camera '{cam['id']}' timed out")
except httpx.ConnectError:
cam_info['status'] = 'offline'
logger.warning(f"Camera '{cam['id']}' connection failed")
except Exception as e:
cam_info['status'] = 'offline'
logger.error(f"Camera '{cam['id']}' error: {e}")
cameras.append(cam_info)
logger.info(f"Found {len(cameras)} camera(s), {sum(1 for c in cameras if c['status'] == 'online')} online")
return cameras
except FileNotFoundError as e:
logger.error(f"Config error: {e}")
return [{"error": str(e)}]
except ValueError as e:
logger.error(f"Config error: {e}")
return [{"error": str(e)}]
except Exception as e:
logger.error(f"Unexpected error: {e}")
return [{"error": f"Unexpected error: {str(e)}"}]
@mcp.tool()
async def vision_snap(cam_id: str) -> Union[MCPImage, str]:
"""
Get a snapshot from a camera.
Queries the /snapshot endpoint and returns the image for inline display.
Args:
cam_id: Camera ID from config file (e.g., "basement")
Returns:
MCPImage object for inline display, or error message string
Examples:
vision_snap("basement")
"""
try:
# Get camera config
cam = get_camera_by_id(cam_id)
cam_type = cam.get('type', 'http')
# Handle based on camera type
if cam_type == 'http':
# HTTP API camera
async with httpx.AsyncClient(timeout=REQUEST_TIMEOUT, verify=False) as client:
snapshot_url = f"{cam['url'].rstrip('/')}/snapshot"
headers = {"X-API-Key": cam['api_key']}
logger.info(f"Requesting HTTP snapshot from '{cam_id}' at {snapshot_url}")
try:
response = await client.get(snapshot_url, headers=headers)
if response.status_code == 200:
# Check content type
content_type = response.headers.get('content-type', '')
if 'image' not in content_type:
logger.warning(f"Unexpected content type: {content_type}")
# Get image bytes
image_bytes = response.content
logger.info(f"✓ Snapshot received from '{cam_id}' ({len(image_bytes)} bytes)")
# Return as MCPImage (directly, not in dict)
return MCPImage(data=image_bytes, format="jpeg")
elif response.status_code == 403:
error_msg = f"❌ Authentication failed for camera '{cam_id}'. Check API key in config."
logger.error(error_msg)
return error_msg
elif response.status_code == 503:
error_msg = f"❌ Camera '{cam_id}' is unavailable (503). Camera may be disconnected."
logger.error(error_msg)
return error_msg
else:
error_msg = f"❌ Camera '{cam_id}' returned status {response.status_code}: {response.text[:100]}"
logger.error(error_msg)
return error_msg
except httpx.TimeoutException:
error_msg = f"❌ Camera '{cam_id}' timed out after {REQUEST_TIMEOUT}s"
logger.error(error_msg)
return error_msg
except httpx.ConnectError as e:
error_msg = f"❌ Cannot connect to camera '{cam_id}' at {cam['url']}: {str(e)}"
logger.error(error_msg)
return error_msg
elif cam_type == 'rtsp':
# RTSP stream camera
rtsp_url = cam['rtsp_url']
logger.info(f"Capturing RTSP snapshot from '{cam_id}' at {rtsp_url}")
try:
# Capture snapshot from RTSP stream
image_bytes = capture_rtsp_snapshot(rtsp_url)
logger.info(f"✓ RTSP snapshot captured from '{cam_id}' ({len(image_bytes)} bytes)")
# Return as MCPImage
return MCPImage(data=image_bytes, format="jpeg")
except RuntimeError as e:
error_msg = f"❌ Failed to capture from RTSP camera '{cam_id}': {str(e)}"
logger.error(error_msg)
return error_msg
else:
error_msg = f"❌ Unknown camera type '{cam_type}' for camera '{cam_id}'"
logger.error(error_msg)
return error_msg
except ValueError as e:
# Camera ID not found
logger.error(f"Camera lookup error: {e}")
return f"❌ {str(e)}"
except FileNotFoundError as e:
# Config file not found
logger.error(f"Config error: {e}")
return f"❌ {str(e)}"
except Exception as e:
error_msg = f"❌ Unexpected error getting snapshot from '{cam_id}': {str(e)}"
logger.exception(error_msg)
return error_msg
@mcp.tool()
def vision_get_info() -> str:
"""
Get information about the Vision camera system configuration.
Returns details about configured cameras and config file location.
Returns:
Formatted string with system info
"""
try:
config = load_camera_config()
cameras = config['cameras']
info_lines = [
"Vision Camera System",
"",
f"Config file: {CONFIG_FILE}",
f"Cameras configured: {len(cameras)}",
""
]
for cam in cameras:
cam_type = cam.get('type', 'http')
if cam_type == 'http':
info_lines.append(f" • {cam['id']} (HTTP): {cam['url']}")
elif cam_type == 'rtsp':
info_lines.append(f" • {cam['id']} (RTSP): {cam['rtsp_url']}")
info_lines.append("")
info_lines.append("Use vision_get_cams() to check camera status")
info_lines.append("Use vision_snap(cam_id) to get a snapshot")
return "\n".join(info_lines)
except FileNotFoundError as e:
return f"❌ {str(e)}"
except ValueError as e:
return f"❌ {str(e)}"
except Exception as e:
return f"❌ Unexpected error: {str(e)}"
if __name__ == "__main__":
# Run the MCP server (uses stdio transport by default)
mcp.run()

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# Environment variables (contains API key!)
.env
# SSL certificates
ssl/
*.pem
*.key
*.crt
# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
venv/
env/
ENV/
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
# IDE
.vscode/
.idea/
*.swp
*.swo
*~
# OS
.DS_Store
Thumbs.db
# Logs
*.log
# Test snapshots
*.jpg
*.jpeg
*.png

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#!/bin/bash
#
# Generate self-signed SSL certificate for local HTTPS
#
# This creates a certificate valid for 365 days. While browsers will show
# a warning (since it's self-signed), the connection will still be encrypted.
#
set -e
CERT_DIR="ssl"
CERT_FILE="$CERT_DIR/cert.pem"
KEY_FILE="$CERT_DIR/key.pem"
echo "=== Camera Server SSL Certificate Generator ==="
echo
# Create ssl directory if it doesn't exist
mkdir -p "$CERT_DIR"
# Generate self-signed certificate
echo "Generating self-signed certificate..."
openssl req -x509 -newkey rsa:4096 \
-keyout "$KEY_FILE" \
-out "$CERT_FILE" \
-days 365 \
-nodes \
-subj "/C=US/ST=State/L=City/O=CameraServer/CN=camera.local"
# Set proper permissions
chmod 600 "$KEY_FILE"
chmod 644 "$CERT_FILE"
echo
echo "✓ Certificate generated successfully!"
echo
echo "Files created:"
echo " - Certificate: $CERT_FILE"
echo " - Private key: $KEY_FILE"
echo
echo "Note: Browsers will show a security warning because this is self-signed."
echo "This is normal for local development. The connection is still encrypted."
echo
echo "To trust this certificate:"
echo " - On macOS: Open Keychain Access, import cert.pem, mark as trusted"
echo " - On Linux: Copy to /usr/local/share/ca-certificates/ and run update-ca-certificates"
echo " - On Windows: Import cert.pem into Trusted Root Certification Authorities"
echo

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#!/usr/bin/env python3
"""
Camera Snapshot Server
Simple FastAPI server that serves snapshots from a USB camera.
Features:
- API key authentication
- HTTPS support
- Thread-safe camera access
- Auto-reconnect on camera failure
"""
import os
import cv2
import threading
import secrets
from typing import Optional
from dotenv import load_dotenv
from fastapi import FastAPI, Security, HTTPException, Response
from fastapi.security import APIKeyHeader
from fastapi.responses import JSONResponse
# Load environment variables
load_dotenv()
# Configuration
API_KEY = os.getenv("API_KEY")
CAMERA_INDEX = int(os.getenv("CAMERA_INDEX", "0"))
CAMERA_WIDTH = int(os.getenv("CAMERA_WIDTH", "1920"))
CAMERA_HEIGHT = int(os.getenv("CAMERA_HEIGHT", "1080"))
JPEG_QUALITY = int(os.getenv("JPEG_QUALITY", "85"))
if not API_KEY:
raise ValueError("API_KEY not set in .env file. Generate one with: python3 -c 'import secrets; print(secrets.token_urlsafe(32))'")
# FastAPI app
app = FastAPI(
title="Camera Snapshot Server",
description="Serves snapshots from USB camera with API key authentication",
version="1.0.0"
)
# API Key authentication
api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
class CameraManager:
"""Thread-safe camera manager with auto-reconnect"""
def __init__(self, camera_index: int = 0, width: int = 1920, height: int = 1080):
self.camera_index = camera_index
self.width = width
self.height = height
self.camera: Optional[cv2.VideoCapture] = None
self.lock = threading.Lock()
def _open_camera(self) -> bool:
"""Open camera connection"""
try:
self.camera = cv2.VideoCapture(self.camera_index)
if not self.camera.isOpened():
return False
# Set camera resolution
self.camera.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
self.camera.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
# Set camera properties for better performance
self.camera.set(cv2.CAP_PROP_BUFFERSIZE, 1) # Reduce buffer to get latest frame
# Log actual resolution (camera may not support requested resolution)
actual_width = int(self.camera.get(cv2.CAP_PROP_FRAME_WIDTH))
actual_height = int(self.camera.get(cv2.CAP_PROP_FRAME_HEIGHT))
print(f"Camera resolution: {actual_width}x{actual_height} (requested: {self.width}x{self.height})")
return True
except Exception as e:
print(f"Error opening camera: {e}")
return False
def get_snapshot(self) -> Optional[bytes]:
"""
Capture a snapshot from the camera.
Returns:
JPEG-encoded image bytes, or None if failed
"""
with self.lock:
# Open camera if not initialized or closed
if self.camera is None or not self.camera.isOpened():
if not self._open_camera():
return None
# Flush buffer to get latest frame
# Read and discard several frames to clear old buffered frames
for _ in range(5):
self.camera.grab()
# Capture the latest frame
ret, frame = self.camera.read()
# Retry on failure
if not ret:
print("Failed to capture frame, attempting reconnect...")
self.release()
if not self._open_camera():
return None
# Flush buffer again after reconnect
for _ in range(5):
self.camera.grab()
ret, frame = self.camera.read()
if not ret:
return None
# Encode as JPEG
try:
ret, buffer = cv2.imencode(
'.jpg',
frame,
[cv2.IMWRITE_JPEG_QUALITY, JPEG_QUALITY]
)
if not ret:
return None
return buffer.tobytes()
except Exception as e:
print(f"Error encoding image: {e}")
return None
def release(self):
"""Release camera resources"""
if self.camera is not None:
self.camera.release()
self.camera = None
def __del__(self):
"""Cleanup on deletion"""
self.release()
# Global camera manager
camera_manager = CameraManager(CAMERA_INDEX, CAMERA_WIDTH, CAMERA_HEIGHT)
def verify_api_key(api_key: str = Security(api_key_header)) -> str:
"""Verify API key from header"""
if api_key is None or api_key != API_KEY:
raise HTTPException(
status_code=403,
detail="Invalid or missing API key"
)
return api_key
@app.get("/")
def root():
"""Root endpoint with API info"""
return {
"service": "Camera Snapshot Server",
"version": "1.0.0",
"endpoints": {
"/snapshot": "GET - Returns JPEG snapshot (requires X-API-Key header)",
"/health": "GET - Health check (no auth required)"
}
}
@app.get("/health")
def health():
"""Health check endpoint"""
return {"status": "ok"}
@app.get("/snapshot")
def get_snapshot(api_key: str = Security(verify_api_key)):
"""
Get a snapshot from the USB camera.
Requires X-API-Key header for authentication.
Returns:
JPEG image
"""
snapshot = camera_manager.get_snapshot()
if snapshot is None:
raise HTTPException(
status_code=503,
detail="Failed to capture snapshot. Check camera connection."
)
return Response(
content=snapshot,
media_type="image/jpeg",
headers={
"Cache-Control": "no-cache, no-store, must-revalidate",
"Pragma": "no-cache",
"Expires": "0"
}
)
@app.on_event("shutdown")
def shutdown_event():
"""Cleanup on shutdown"""
camera_manager.release()
if __name__ == "__main__":
import uvicorn
# For development only - use uvicorn command for production
uvicorn.run(
"main:app",
host="0.0.0.0",
port=8443,
ssl_keyfile="ssl/key.pem",
ssl_certfile="ssl/cert.pem"
)

11
server/requirements.txt Normal file
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# Camera Snapshot Server Dependencies
# Web framework
fastapi>=0.104.0
uvicorn[standard]>=0.24.0
# Camera access
opencv-python-headless>=4.8.0
# Configuration
python-dotenv>=1.0.0

157
server/setup.sh Normal file
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#!/bin/bash
# vixy-vision Server Setup Script
# Run this on a Raspberry Pi or similar edge device
#
# Usage: ./setup.sh [--with-audio]
set -e
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
INSTALL_DIR="${HOME}/vixy-vision"
SERVICE_NAME="vixy-vision"
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
NC='\033[0m' # No Color
echo_info() { echo -e "${GREEN}[INFO]${NC} $1"; }
echo_warn() { echo -e "${YELLOW}[WARN]${NC} $1"; }
echo_error() { echo -e "${RED}[ERROR]${NC} $1"; }
# Parse arguments
WITH_AUDIO=false
for arg in "$@"; do
case $arg in
--with-audio)
WITH_AUDIO=true
shift
;;
esac
done
echo "=========================================="
echo " vixy-vision Server Setup"
echo " Eyes and ears for the fox 🦊"
echo "=========================================="
echo ""
# Check if running on Linux
if [[ "$(uname)" != "Linux" ]]; then
echo_error "This script is designed for Linux (Raspberry Pi)"
exit 1
fi
# Install system dependencies
echo_info "Installing system dependencies..."
sudo apt-get update
sudo apt-get install -y python3-pip python3-venv libopencv-dev
if [ "$WITH_AUDIO" = true ]; then
echo_info "Installing audio dependencies..."
sudo apt-get install -y portaudio19-dev python3-pyaudio alsa-utils
fi
# Create install directory
echo_info "Creating install directory: ${INSTALL_DIR}"
mkdir -p "${INSTALL_DIR}"
cp -r "${SCRIPT_DIR}"/* "${INSTALL_DIR}/"
# Create virtual environment
echo_info "Creating Python virtual environment..."
cd "${INSTALL_DIR}"
python3 -m venv venv
source venv/bin/activate
# Install Python dependencies
echo_info "Installing Python dependencies..."
pip install --upgrade pip
pip install -r requirements.txt
if [ "$WITH_AUDIO" = true ]; then
pip install pyaudio webrtcvad numpy
fi
# Generate SSL certificates
echo_info "Generating SSL certificates..."
chmod +x generate_cert.sh
./generate_cert.sh
# Generate API key if .env doesn't exist
if [ ! -f .env ]; then
echo_info "Generating API key..."
API_KEY=$(python3 -c 'import secrets; print(secrets.token_urlsafe(32))')
cat > .env << EOF
# vixy-vision Server Configuration
# Generated by setup.sh on $(date)
# API Key for authentication (keep secret!)
API_KEY=${API_KEY}
# Camera settings
CAMERA_INDEX=0
CAMERA_WIDTH=1920
CAMERA_HEIGHT=1080
JPEG_QUALITY=85
EOF
echo_info "API key generated and saved to .env"
echo ""
echo_warn "IMPORTANT: Save this API key for your MCP config:"
echo -e " ${GREEN}${API_KEY}${NC}"
echo ""
else
echo_info "Using existing .env file"
fi
# Create systemd service
echo_info "Creating systemd service..."
sudo tee /etc/systemd/system/${SERVICE_NAME}.service > /dev/null << EOF
[Unit]
Description=vixy-vision Camera Server
After=network.target
[Service]
Type=simple
User=${USER}
WorkingDirectory=${INSTALL_DIR}
Environment="PATH=${INSTALL_DIR}/venv/bin"
ExecStart=${INSTALL_DIR}/venv/bin/uvicorn main:app --host 0.0.0.0 --port 8443 --ssl-keyfile ssl/key.pem --ssl-certfile ssl/cert.pem
Restart=always
RestartSec=10
[Install]
WantedBy=multi-user.target
EOF
# Reload systemd and enable service
sudo systemctl daemon-reload
sudo systemctl enable ${SERVICE_NAME}
echo ""
echo "=========================================="
echo " Setup Complete! 🦊"
echo "=========================================="
echo ""
echo "Commands:"
echo " Start: sudo systemctl start ${SERVICE_NAME}"
echo " Stop: sudo systemctl stop ${SERVICE_NAME}"
echo " Status: sudo systemctl status ${SERVICE_NAME}"
echo " Logs: sudo journalctl -u ${SERVICE_NAME} -f"
echo ""
echo "Server will be available at:"
echo " https://$(hostname -I | awk '{print $1}'):8443/"
echo ""
echo "Add to Vixy's vision config (~/.vision_setup.json):"
echo " {"
echo " \"cameras\": ["
echo " {"
echo " \"id\": \"$(hostname)\","
echo " \"type\": \"http\","
echo " \"url\": \"https://$(hostname -I | awk '{print $1}'):8443\","
echo " \"api_key\": \"<your-api-key-from-above>\""
echo " }"
echo " ]"
echo " }"
echo ""
echo_info "Start the server with: sudo systemctl start ${SERVICE_NAME}"

18
shared/README.md Normal file
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# Shared Module
Common schemas and interfaces used across vixy-vision.
## Planned Components
### events.py
Event schema definitions and queue interface.
```python
@dataclass
class SensorEvent:
timestamp: datetime
source_id: str # camera/mic ID
event_type: str # "motion", "audio", "speech"
confidence: float # 0.0 - 1.0
metadata: dict # type-specific data
```