- A deep learning-enabled camera for developers
- A wireless-enabled camera integrated with AWS Cloud
- Capable of delivering 100GFLOPS of computing power (1 billion operations per second)
- Contains sample projects at launch to get you started
- Optimized for Apache MXNet, TensorFlow, and Caffe
- Integrates with Amazon Rekognition for advanced image analysis
Common use cases
- Developing computer vision applications such as:
- Face Detection
- Activity Detection
- Object Detection
- Bird Classification
- Artistic Style Transfer
AWS DeepLens needs 3 AWS services to create a project:
- Amazon SageMaker
- Train/validate custom or pre-trained models
- AWS Lambda
- Capturing inference
- Displaying output
- AWS IoT Greengrass
- Deploys application project and Lambda runtime to AWS DeepLens
- Handles software and configuration updates
AWS DeepLens Device Library
- awscam module
- Runs inference code based on a project’s model.
- mo module
- Converts Caffe, Apache MXNet, or TensorFlow deep-learning model artifacts into AWS DeepLens model artifacts.
- Provides optimizations for AWS DeepLens model artifacts.
- DeepLens_Kinesis_Video module
- Can send video feeds from the AWS DeepLens device to Amazon Kinesis Video Streams.
Note: If you are studying for the AWS Certified Machine Learning Specialty exam, we highly recommend that you take our AWS Certified Machine Learning – Specialty Practice Exams and read our Machine Learning Specialty exam study guide.