DT42 delivers a Christmas gift for the BerryNet community.

Now you can build your own smart camera more easily with BerryNet 2. Our team have been working on BerryNet project since we released it 6 months ago. You don’t have to wait for the shipment of Google AIY VisionKit, neither spend $249 for AWS DeepLens. Only one-step installation, BerryNet + Raspberry Pi + Movidius neural compute stick is the AI Kit for everyone.

Here are the new feature for BerryNet 2

* Support Movidius neural compute stick.

* Supports for USB, RPi, and Nest cameras in both snapshot and stream modes.

* Faster detection backend reducing inference time to ~40%.

* Documentations and tutorials including detection transfer learning (Wiki pages).

* Data collector for saving snapshots and inference results for data analysis.

* DLModelBox: model packaging and management toolkit

* IM client: LINE.

In the near future, we will provide an easy-to-use training tool — Epeuva for our users. On Epeuva, makers can create customized AI models with their own data without any coding effort. For example, you can create an application that can specific detects your own dog, or a raccoon detector that alerts you when raccoons are eating all your fruits in your backyard.

BerryNet now provides more powerful visual intelligence system that doesn’t require access to cloud, so that deep learning can be done locally on your devices. No need to wait for the shipment from Google or Amazon, with BerryNet, you can turn your camera into intelligence camera now.

Visit BerryNet on Github to try, only one step installation needed. Build it your own way, use AI to create more interesting applications.

[1]BerryNet Github

[2]BerryNet: Turn Raspberry Pi 3 Into Intelligent Gateway