v2.6.2

• You can now select, at install time, which modules you wish to have initially installed
• Some modules (Coral, Yolov8) now allow you to download individual models at runtime via the dashboard.
• A new generative AI module (Llama LLM Chatbot)
• A standardised way to handle (in code) modules that run long processes such as generative AI
• Debian support has been improved
• Small UI improvements to the dashboard
• Some simplification of the modulesettings files
• The inclusion, in the source code, of template .NET and Python modules (both simple and long process demos)
• Improvements to the Coral and ALPR modules (thanks to Seth and Mike)
• Docker CUDA 12.2 image now includes cuDNN
• Install script fixes
• Added Object Segmentation to the YOLOv8 module

v2.5.1

• Lots of Javascript updates so if you see weirdness try Ctrl+F5
• The module listing now shows module version history if you click the version number
• Benchmark has been updated to use the custom models of the currently active object detection module
• The Info button on the dashboard now includes a status data dump from the module. For things like object detectors, it will include a dictionary of labels / counts so you can see what's being detected. For longer running modules such as training it will include the training status. This is here to enable better UI features in the future
• Lots of bug fixes, but specifically there was a script issue affecting module installs, and a modulesettings issue affecting the YOLOv5 6.2 module, as well as the SuperResolution module.
• The Coral module now includes multi-TPU support that is still a little fragile. An update is coming in the next few days

v2.5.0

• Dynamic Explorer UI: Each module now supplies its own UI for the explorer
• Support for sound audition modules in the explorer
• Improved dashboard
• Updated module settings schema that includes module author and original project acknowledgement
• Installer fixes
• Improved Jetson support
• Windows on Arm support

v2.2.4

• Improved support for Windows, Ubuntu, macOS (Intel and Apple Silicon), as well as improvements to allow support for ROCm and Jetson
• 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
• Fix to remove chunking in order to allow HTTP1.1 access to the API (Blue Iris fix)
• Various bug fixes

v2.1.0

• 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

v2.0.5

New module architecture, downloadable modules, RaspberryPi support and assorted memory leaks fixed.

v1.6.8

• Improved multi-thread support for ONNX on .NET
• improved image handling for MacOS/Linux
• Added support for sideloading modules
• Better arm64 support
• General cleanups

v1.6.0.0

• 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

v1.5.6.2

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

v1.5.6

• nVidia GPU support!
• 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