Difference between revisions of "DeepLens - deep learning enabled video camera"

Latest revision as of 22:45, 30 March 2023

YouTube search... ...Google search

Hardware Specifications

4 megapixel resolution (1080p Video)
8GB of RAM
16GB of internal storage
A 32GB SD card
Wi-Fi connectivity
A micro HDMI port
1/8" audio port
2 USB ports
5v power supply
The CPU is a dual-core Atom E3930. DeepLens comes with an Intel HD Graphics 500 chip; so a graphics processing unit (GPU) is included too. This chip has 12 “execution units” capable of running 7 threads each [single instruction, multiple data (SIMD) architecture]. 84 “cores” - over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time. Processor Technical Specifications

@@ Line 1: / Line 1: @@
-[http://www.youtube.com/results?search_query=amazon+deeplens YouTube search...]
+{{#seo:
+|title=PRIMO.ai
+|titlemode=append
+|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
+}}
+[https://www.youtube.com/results?search_query=amazon+deeplens YouTube search...]
+[https://www.google.com/search?q=amazon+deeplens+deep+machine+learning+ML ...Google search]
-* [http://aws.amazon.com/deeplens/ Product page...]
+* [[Amazon | Amazon AWS]]
-* [http://www.slideshare.net/AmazonWebServices/aws-deeplens-workshop-building-computer-vision-applications AWS DeepLens Workshop: Building Computer Vision Applications]
+* [https://aws.amazon.com/deeplens/ Product page...]
+* [[Getting Started & Project: Object Detection]]
+* [[More DeepLens Projects]]
+* [[Video/Image]]
 https://docs.aws.amazon.com/deeplens/latest/dg/images/deeplens-hiw-general.png
-== 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
-* [https://aws.amazon.com/iot/ 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]]
-* [http://en.wikipedia.org/wiki/SoftAP SoftAP] - software enabled access point
-* [http://www.ubuntu.com/ Ubuntu] - operating system
-== Frameworks ==
-* [[TensorFlow]]
-* [[Caffe / Caffe2]]
-* [[MXNet]]
-* [[gluon]]
-https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2017/11/30/DeepLens-Flow-1.gif
-== I just got my DeepLens! ==
-* [http://aws.amazon.com/deeplens/resources/ DeepLens Developer Resources]
-** [http://aws.amazon.com/getting-started/tutorials/configure-aws-deeplens/ Configure Your New AWS DeepLens]
-** [http://aws.amazon.com/getting-started/tutorials/build-deeplens-project-sagemaker/?trk=gs_card Build an AWS DeepLens Project]
-** [http://aws.amazon.com/getting-started/tutorials/create-deploy-project-deeplens/?trk=gs_card Creating and Deploying an AWS DeepLens Project]
-** [http://aws.amazon.com/getting-started/tutorials/extend-deeplens-project/?trk=gs_card Extending Your AWS DeepLens Project]
-* [http://blog.kloud.com.au/2018/02/27/aws-deeplens-part-1-getting-the-deeplens-online/ Part 1 - Getting Online | SAMZAKKOUR @ Kloud]
-* [http://www.lynda.com/Amazon-Web-Services-tutorials/Setting-up-your-AWS-DeepLens/706932/737910-4.html Lynda.com Setting up your AWS DeepLens]
-<youtube>j0DkaM4L6n4</youtube>
-<youtube>nINqpklf7Eo</youtube>
-== Learn More ==
-* [http://blog.soracom.io/aws-deeplens-meets-soracom-fc121858cd70 AWS DeepLens meets SORACOM; cellular enabled cloud-connectivity-as-a-service platform]
 <youtube>RhEVld4GwzU</youtube>
 <youtube>BqHWG2CUDg4</youtube>
-<youtube>qRJwvo94-Ko</youtube>
-<youtube>5m7eSTSwpk4</youtube>
 <youtube>bTLMU9z_hes</youtube>
-<youtube>bSrpk1xQHB4</youtube>
 <youtube>Vw-bX1RRZGQ</youtube>
-<youtube>xzFwySJYRoE</youtube>
+<youtube>qRJwvo94-Ko</youtube>
-<youtube>PbQO3-jYkGo</youtube>
-<youtube>cTsCMTxEPHs</youtube>
-== Projects ==
+https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2017/11/30/DeepLens-Flow-1.gif
-[http://www.youtube.com/results?search_query=deeplens+project+community+challenge YouTube search...]
-* [http://docs.aws.amazon.com/deeplens/latest/dg/deeplens-templated-projects-overview.html AWS Project Templates]
-* [http://aws.amazon.com/deeplens/community-projects/ Collection of AWS DeepLens Community Projects]
-<youtube>usvcA2Ibajs</youtube>
-<youtube>ScYKqja-jdc</youtube>
-<youtube>fLjYKyRDDu0</youtube>
-<youtube>dTXbIzhq_po</youtube>
-<youtube>BbFAm7lcnUU</youtube>
-<youtube>5DDRvRHZ1Qs</youtube>
-<youtube>wnTvVB1ojPk</youtube>
-<youtube>5VAKcQtoELo</youtube>
-<youtube>SZTo7CqOjvU</youtube>
-<youtube>tu7TmUQoj6s</youtube>
-* [http://github.com/aws-samples/aws-ml-vision-end2end aws-ml-vision-end2end -  Jupyter Notebook tutorials walking through deep learning Frameworks (MXNet, Gluon) to Platforms (SageMaker, DeepLens) for common CV use-cases | GitHub]
+== Hardware Specifications ==
-* [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]
-== Processor ==
+* 4 megapixel resolution (1080p [[Video/Image|Video]])
+* 8GB of RAM
+* 16GB of internal storage
+* A 32GB SD card
+* Wi-Fi connectivity
+* A micro HDMI port
+* 1/8" audio port
+* 2 USB ports
+* 5v power supply
+* The CPU is a [https://ark.intel.com/products/96486/Intel-Atom-x5-E3930-Processor-2M-Cache-up-to-1_80-GHz dual-core Atom E3930]. DeepLens comes with an [https://www.notebookcheck.net/Intel-HD-Graphics-500.182723.0.html Intel HD Graphics 500 chip]; so a graphics processing unit ([https://en.wikipedia.org/wiki/Graphics_processing_unit GPU]) is included too. This chip has 12 “execution units” capable of running 7 threads each [single instruction, multiple data ([https://en.wikipedia.org/wiki/SIMD SIMD]) architecture]. 84 “cores” - over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD [[Video/Image|video]] for real time. [https://software.intel.com/sites/default/files/managed/c5/9a/The-Compute-Architecture-of-Intel-Processor-Graphics-Gen9-v1d0.pdf Processor Technical Specifications]
-With over 100 GFLOPS of compute power on the device, it can process deep learning predictions on HD video for real time.
-* [http://software.intel.com/sites/default/files/managed/c5/9a/The-Compute-Architecture-of-Intel-Processor-Graphics-Gen9-v1d0.pdf Processor Technical Specifications]
 <youtube>suQnh1TvGHw</youtube>
-<youtube>TS4ShpBHr_g</youtube>
-== SSH ==
-* [http://www.deeplearning.team Deep Learning Team | Jovon Weathers]
-<youtube>2eKjcLsBH6E</youtube>
-<youtube>HozP1t3usPM</youtube>

Difference between revisions of "DeepLens - deep learning enabled video camera"

Latest revision as of 22:45, 30 March 2023

Hardware Specifications

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