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Amazon Rekognition

Image Detection and Recognition Powered by Deep Learning
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What is Amazon Rekognition?

Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications.
Amazon Rekognition is a tool in the Image Analysis API category of a tech stack.

Who uses Amazon Rekognition?

Companies
17 companies reportedly use Amazon Rekognition in their tech stacks, including Flitto, WebApp, and Armut.

Developers
47 developers on StackShare have stated that they use Amazon Rekognition.
Pros of Amazon Rekognition
4
Integrate easily with AWS
Decisions about Amazon Rekognition

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon Rekognition in their tech stack.

Harsh Solanki
Machine Learning Engineer at Quantiphi · | 3 upvotes · 12.1K views

We have to process the video stream to identify emotions. For which we need to use Amazon Rekognition/custom model on Amazon SageMaker. With Kinesis WebRTC Javascript SDK, currently, video can be streamed only into the kinesis signaling channel. Signaling channel data is available for streaming only and not processing (ML). So, how can we get real-time data for processing into Kinesis Streams from the frontend?

For streaming the video from frontend to backend into the Amazon Kinesis Video Streams for processing, we tested with Kinesis webRTC JavaScript SDK, and we are facing issues while implementing as mentioned above, so would Chime SDK serve as an alternative to this?

In Rekognition, "create-stream-processor" has a settings parameter. This currently only supports FaceSearch. We are looking to Detect and analyze faces. Is that possible with "create-stream-processor" in the Python SDK? Or do we have to use the Java SDK?

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Amazon Rekognition Alternatives & Comparisons

What are some alternatives to Amazon Rekognition?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
OpenCV
OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
Google Cloud Vision API
Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API.
Tesseract OCR
Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. Since 2006 it is developed by Google.
Tesseract.js
This library supports over 60 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browser and on a server with NodeJS.
See all alternatives

Amazon Rekognition's Followers
115 developers follow Amazon Rekognition to keep up with related blogs and decisions.