Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models.
AWS Deeplens specifications:
- Camera – 4MP (1080p) camera using MJPEG, H.264 encoding
- Video Output – micro HDMI port
- Audio – 3.5mm audio jack, and HDMI audio
- Connectivity – Dual band WiFi
- USB – 2x USB 2.0 ports
- Misc – Power button; camera, WiFi and power status LEDs; reset pinhole
- Power Supply – TBD
- Dimensions – 168 x 94 x 47 mm
- Weight – 296.5 grams
The camera can not only do inference, but also train deep learning models using Amazon infrastructure. Performance wise, the camera can infer 14 images/second on AlexNet, and 5 images/second on ResNet 50 for batch size of 1.
But if you want to make your own project, a typical workflow would be as follows:
- Train a deep learning model using Amazon SageMaker
- Optimize the trained model to run on the AWS DeepLens edge device
- Develop an AWS Lambda function to load the model and use to run inference on the video stream
- Deploy the AWS Lambda function to the AWS DeepLens device using AWS Greengrass
- Wire the edge AWS Lambda function to the cloud to send commands and receive inference output
This steps are explained in details on Amazon blog.
Intel also published a press release explaining how they are involved in the project:
DeepLens uses Intel-optimized deep learning software tools and libraries (including the Intel Compute Library for Deep Neural Networks, Intel clDNN) to run real-time computer vision models directly on the device for reduced cost and real-time responsiveness.
Developers can start designing and creating AI and machine learning products in a matter of minutes using the preconfigured frameworks already on the device. Apache MXNet is supported today, and Tensorflow and Caffe2 will be supported in 2018’s first quarter.
Jean-Luc started CNX Software in 2010 as a part-time endeavor, before quitting his job as a software engineering manager, and starting to write daily news, and reviews full time later in 2011.