Skip to content


Release Notes

Release 2.2 Beta

  • An entirely new Windows installer offering more installation options and a smoother upgrade experience from here on.
  • New macOS and Ubuntu native installers, for x64 and arm64 (including Raspberry Pi)
  • A new installation SDK for making module installers far easier
  • Improved installation feedback and self-checks
  • Coral.AI support for Linux, macOS (version 11 and 12 only) and Windows

Release 2.1 Beta

  • Improved Raspberry Pi support. A new, fast object detection module with support for the Coral.AI TPU, all within an Arm64 Docker image
  • All modules can now be installed / uninstalled (rather than having some modules fixed and uninstallble).
  • Installer is streamlined: Only the server is installed at installation time, and on first run we install Object Detection (Python and .NET) and Face Processing (which can be uninstalled).
  • Reworking of the Python module SDK. Modules are new child classes, not aggregators of our module runner.
  • Reworking of the modulesettings file to make it simpler and have less replication
  • Improved logging: quantity, quality, filtering and better information
  • Addition of 2 modules: ObjectDetectionTFLite for Object Detection on a on Raspberry Pi using Coral, and Cartoonise for some fun
  • Improvements to half-precision support checks on CUDA cards
  • Modules are now versioned and our module registry will now only show modules that fit your current server version.
  • Various bug fixes
  • Shared Python runtimes now in runtimes.
  • All modules moved from the AnalysisLayer folder to the modules folder
  • Tested on CUDA 12 (Note: ALPR and OCR do not run on CUDA 12)

Release 2.0 Beta

  • New Downloadable module system
  • Re-introduction of PyTorch 1.7 YOLO module for older GPUs
  • .NET 7

Release 1.6.0.0 Beta

  • Optimised RAM use
  • Ability to enable / disable modules and GPU support via the dashboard
  • REST settings API for updating settings on the fly
  • Apple M1/M2 GPU support
  • Async processes and logging for a performance boost
  • Breaking: the CustomObjectDetection is now part of ObjectDetectionYolo

Release 1.5.6.2 Beta

  • Docker Nvidia GPU support
  • Further performance improvements
  • cuDNN install script to help with NVidia driver and toolkit installation
  • Bug fixes

Release 1.5.6 Beta

  • NVidia GPU support for Windows
  • Perf improvements to Python modules
  • Work on the Python SDK to make creating modules easier
  • Dev installers now drastically simplified for those creating new modules
  • Added SuperResolution as a demo module

Release 1.5 Beta

  • Support for custom models

Release 1.3.x Beta

  • Refactored and improved setup and module addition system
  • Introduction of modulesettings.json files
  • New analysis modules

Release 1.2.x Beta

  • Support for Apple Silicon for development mode
  • Native Windows installer
  • Runs as Windows Service
  • Run in a Docker Container
  • Installs and Builds using VSCode in Linux (Ubuntu), macOS and Windows, as well as Visual Studio on Windows
  • General optimisation of the download payload sizes

Previous

  • We started with a proof of concept on Windows 10+ only. Installs we via a simple BAT script, and the code has is full of exciting sharp edges. A simple dashboard and playground are included. Analysis is currently Python code only
  • Version checks are enabled to alert users to new versions
  • A new .NET implementation scene detection using the YOLO model to ensure the codebase is platform and tech stack agnostic
  • Blue Iris integration completed