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README.md

Wyzely Detect

Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices

Features

  • Recognize objects
  • Recognize faces
  • Send notifications to your phone (or other devices) using ntfy
  • Optionally, run headless with Docker
  • Either use a webcam or an RTSP feed

Prerequisites

Poetry/Python

  • Camera, either a webcam or a Wyze Cam
    • All RTSP feeds should work, however.
  • Python 3.10 or 3.11
  • Poetry

Docker

  • A Wyze Cam
    • Any other RTSP feed should work, as mentioned above
  • Docker
  • Docker Compose

What's not required

  • A Wyze subscription

Usage

Installation

  1. Clone this repo with git clone https://github.com/slashtechno/wyze-face-recognition.git
  2. cd into the cloned repository
  3. Then, either install with Poetry or run with Docker

Docker

  1. Modify to docker-compose.yml to achieve desired configuration
  2. Run in the background with `docker compose up -d

Poetry

  1. poetry install
  2. poetry run -- wyzely-detect

Configuration

The following are some basic CLI options. Most flags have environment variable equivalents which can be helpful when using Docker.

  • For face recognition, put images of faces in subdirectories ./faces (this can be changed with --faces-directory)
    • Keep in mind, on the first run, face rec
  • By default, notifications are sent for all objects. This can be changed with one or more occurrences of --detect-object to specify which objects to detect
    • Currently, all classes in the COCO dataset can be detected
  • To specify where notifications are sent, specify a ntfy URL with --ntfy-url
  • To configure the program when using Docker, edit docker-compose.yml and/or set environment variables.
  • For further information, use --help

How to uninstall

  • If you used Docker, run docker-compose down --rmi all in the cloned repository
  • If you used Poetry, just delete the virtual environment and then the cloned repository