Object detection for video surveillance


Watsor detects objects in video stream using deep learning-based approach. Intended primarily for surveillance it works in sheer real-time analysing the most recent frame to deliver fastest reaction against a detected threat.

What it does

  • Performs smart detection based on artificial neural networks significantly reducing false positives in video surveillance.
  • Capable to limit detection zones using mask image with alpha channel.
  • Supports multiple hardware accelerators such as The Coral USB Accelerator and Nvidia CUDA GPUs to speed up detection algorithms.
  • Reports the detected objects via MQTT protocol primarily for integration with HomeAssistant.
  • Allows to control video decoder using the commands published over MQTT.
  • Broadcasts video stream with rendered object detections in MPEG-TS and Motion JPEG formats over HTTP.
  • Captures video from any source and encodes video with rendered object detections in any format supported by FFmpeg.

Being applicable in CCTV, Watsor also suits other areas, where object detection in video stream is required.

Watsor on GitHub

Check out how to deploy Watsor to Jetson Nano


Looks very interesting and I will give it a try (may take some time though as my “things i wanna try” list is quite long).

Really like the MQTT support as I use another home automation system which supports this as well.

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