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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
- Use mrlt8/docker-wyze-bridge to get RTSP feeds from Wyze Cams
Prerequisites
Python
- Camera, either a webcam or a Wyze Cam
- All RTSP feeds should work, however.
- Python 3.10 or 3.11
- Poetry (optional)
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
Cloning the repository is not required when installing from PyPi but is required when installing from source
- Clone this repo with
git clone https://github.com/slashtechno/wyzely-detect cdinto the cloned repository- Then, either install with Poetry or run with Docker
Docker
- Modify to
docker-compose.ymlto achieve desired configuration - Run in the background with `docker compose up -d
Installing from PyPi with pip
This assumes you have Python 3.10 or 3.11 installed
pip install wyzely-detect
a. You may need to usepip3instead ofpipwyzely-detect
Poetry
poetry installpoetry 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-objectto 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.ymland/or set environment variables. - For further information, use
--help
How to uninstall
- If you used Docker, run
docker-compose down --rmi allin the cloned repository - If you used Poetry, just delete the virtual environment and then the cloned repository