Difference between revisions of "DeepLens - deep learning enabled video camera"
(→Processor) |
|||
| Line 84: | Line 84: | ||
* [http://aws.amazon.com/blogs/machine-learning/deploy-gluon-models-to-aws-deeplens-using-a-simple-python-api/ Deploy Gluon models to AWS DeepLens using a simple Python API] | * [http://aws.amazon.com/blogs/machine-learning/deploy-gluon-models-to-aws-deeplens-using-a-simple-python-api/ Deploy Gluon models to AWS DeepLens using a simple Python API] | ||
| − | == | + | == Processo |
| − | |||
| − | |||
With over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time. | With over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time. | ||
Revision as of 20:38, 23 June 2018
Contents
Integrated Components/Technologies
- Lex - conversational interfaces using voice and text
- SageMaker - build, train, and deploy
- Polly - text to speech
- Rekognition - video analysis service
- Kinesis - collect, process, and analyze real-time, streaming data
- Lambda - run code without managing servers
- AWS IoT Services Overview
- Internet of Things (IoT) Core - process and route those messages to AWS endpoints
- AWS IoT Button
- Greengrass - connected devices can run AWS Lambda functions, keep device data in sync
- Intel® Compute Library for Deep Neural Networks (clDNN) & OpenVINO - deep learning primitives for computer vision
- Simple Queue Service (SQS) - message queuing
- Simple Notification Service (SNS) - pub/sub messaging and mobile notifications
- DynamoDB - NoSQL database
- Simple Storage Service (S3) - object storage
- Management Console - manage web services
- Deep Learning (DL) Amazon Machine Image (AMI) - DLAMI
- SoftAP - software enabled access point
- Ubuntu - operating system
Frameworks
I just got my DeepLens!
- Part 1 - Getting Online | SAMZAKKOUR @ Kloud
- Lynda.com Setting up your AWS DeepLens
- AWS DeepLens meets SORACOM; cellular enabled cloud-connectivity-as-a-service platform
Learn More
Projects
- aws-ml-vision-end2end - Jupyter Notebook tutorials walking through deep learning Frameworks (MXNet, Gluon) to Platforms (SageMaker, DeepLens) for common CV use-cases | GitHub
- Deploy Gluon models to AWS DeepLens using a simple Python API
== Processo With over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time.
SSH
