BrainFrame v0.28.1 is released!

Announcements
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We’re all excited to announce the latest release of BrainFrame v0.28.1!

Updating

If you’ve already installed BrainFrame, simply run:

brainframe update

Then download an updated version of the client here.

If you haven’t installed BrainFrame, then follow our installation instructions.

Changes

Features:

  • :tada: The BrainFrame client now has support for limiting the number of streams that are viewed. The client will now only show 5 streams, and will load streams dynamically when the user clicks on one. This allows the client to run on underpowered computers, even if the server is running 100+ streams.
  • :tada: Added support for iGPU on OpenVINO Capsules (disabled by default, will be enabled by default in v0.29 release). Read below for more information on how to enable it.
  • :tada: Upgraded the capsule system to use Tensorflow 2! (Specifically, 2.5.0). All capsules are forwards compatible.

Performance

  • Improved API data throughput for the /api/streams/statuses API
  • Upgraded BrainFrame docker images from Cuda 10 to Cuda 11. No changes in the host system should be necessary.
  • GStreamer improvements:
    • Added support for OpenCL
    • Reduce memory usage when using NVCODEC
  • Reduced memory usage of journal microservice by ~3x

Bug Fixes:

  • Fix a memory leak that occurs when deleting streams
  • Fix freezes that happen on the /api/streams/statuses API which could cause timeout errors on the client

How to use iGPU with OpenVINO Capsules

This feature is currently in beta. Here’s how to use it!

# 1. Stop the BrainFrame server
brainframe compose down

# 2. Add an environment variable telling BrainFrame to allow iGPU
echo OPENVINO_DEVICE_PRIORITY=GPU,CPU >> $(brainframe info install_path)/.env

# 3. Start BrainFrame
brainframe compose up -d

# 4. View logs, and look for the log "Loading capsule ___ onto devices GPU
brainframe compose logs -f core

Make sure you have an OpenVINO capsule installed, to test this feature.

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