Download Protection Blue Iris: Unlocking Custom Model Detection

In recent updates, the writing modules of CodeProject.AI server have undergone significant improvements. This includes enhancements for Blue Iris users who rely on custom model detection. In this article, we will delve into the details of these changes and provide guidance on how to unlock the disabled Blue Iris settings.

Improved Custom Model Detection for Blue Iris Users

For those using custom model detection with Blue Iris, a new setup script has been introduced to copy standard model files into the specified custom model directory. This ensures that CodeProject.AI server is aware of the available models and can utilize them accordingly. The setup script also ensures that the necessary Python packages are in place.

Enhanced Support for NVIDIA CUDA and Apple M1/M2 GPUs

CodeProject.AI Server now supports NVIDIA CUDA and Apple M1/M2 GPUs, with support for these devices needing to be set up during installation. This means that users will need to enable GPU support at install time, which can be done by running the installer.

Improved Performance and Image Handling on Linux

The latest update includes improvements in image handling on Linux platforms, with multi-threaded ONNX support now available. Additionally, performance enhancements have been made for Object Detection modules, ensuring faster and more accurate results.

New Setup and Install Scripts

The setup process has been streamlined with new, simplified scripts that make it easier to install and run CodeProject.AI Server natively on the Raspberry Pi using VSCode.

Optional YOLO 3.1 Object Detection Module for Older GPUs

For users with older GPUs, an optional YOLO 3.1 Object Detection module is now available, providing enhanced performance and detection capabilities.

Module Registry and Download Protection

The new Module Registry allows users to download and install modules at runtime via the dashboard, ensuring seamless integration with CodeProject.AI Server. Additionally, download protection for Blue Iris has been improved, ensuring that users can access custom model detection without compromising security.

Troubleshooting Common Issues

For those experiencing issues with Blue Iris or CodeProject.AI Server, a comprehensive guide to troubleshooting common problems is available on the official documentation page. This includes solutions for issues related to GPU support, module installation, and more.

In conclusion, the latest updates to CodeProject.AI Server have brought significant improvements to custom model detection for Blue Iris users, enhanced support for NVIDIA CUDA and Apple M1/M2 GPUs, and streamlined setup processes. With these changes, users can expect improved performance, faster detection times, and increased flexibility in their AI-powered applications.

References:

* 'CodeProject.AI Server Documentation'

* 'How to Train a Custom YOLOv5 Model to Detect Objects'

* 'Solutions for Common Issues with Blue Iris and CodeProject.AI Server'

Download protection blue iris