VisionixAI

Zone-Based Computer Vision Automation

Smart actions through visual presence detection.

VisionixAI is a computer vision platform for detecting presence in room zones and triggering automated responses — no sensors, no hardware dependencies.

Project Structure

• cli/ — Node.js CLI tool for interacting with the system
• ml-core/ — Python-based computer vision core

Quick Start (Production Install)

Prerequisites

• Node.js (for CLI)
• Python 3.7+ and pip (for ML core)

Global Install (Recommended)

npm install -g @visionix/cli

This will:

• Install the CLI globally as visionix
• Automatically install all required Python dependencies (OpenCV, MediaPipe, etc.)
• Write detailed install logs to ~/visionix_postinstall.log

Note: Python dependency installation may take several minutes depending on your internet speed.

Local Development/Testing

cd cli
npm install
npm pack
npm install -g ./visionix-cli-*.tgz

Manual Python Dependency Install (if needed)

If the postinstall step fails, run:

pip3 install -r cli/ml-core/requirements.txt

Usage

Usage

Analyze a video file

visionix analyze path/to/video.mp4

Or, if not linked globally:

node cli/bin/visionix.js analyze path/to/video.mp4

What to expect

• The CLI will show a spinner/progress indicator while analyzing.
• On success, you'll see a completion message.
• On error, you'll get a clear message and troubleshooting hints.

What happens?

• The CLI calls the Python ML core, which processes the video, divides it into zones, and prints ON/OFF triggers for each zone based on presence.

Troubleshooting

• Install stuck or fails?
  • Check ~/visionix_postinstall.log for detailed logs.
  • Ensure Python 3 and pip are installed and available in your PATH.
  • Try installing Python dependencies manually (see above).
  • On Windows, ensure Python was installed with "Add Python to PATH" enabled or run py -3 -m pip install -r cli/ml-core/requirements.txt.
• Input video not found?
  • Double-check the path you provide to visionix analyze.
• Permission errors?
  • Try running the install with elevated permissions (e.g., sudo).
• Still stuck?
  • Open an issue and attach your visionix_postinstall.log.

Development

• Add new features to ml-core/app.py and expose them via the CLI.
• See ml-core/README.md for ML core details.

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Logs:

• All install logs are written to ~/visionix_postinstall.log for easy debugging.

Testing Locally:

• Use npm pack and npm install -g ./visionix-cli-*.tgz to test the full install process as a user would experience it.

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Additional Notes:

• The installer logs the current working directory, log file path, and entry/exit of major steps.
• Long-running operations use timeouts to avoid hangs; re-run if interrupted.