Image recognition is becoming more and more popular today. But if you don’t want to handle all the underlying details (building and training a machine learning model, etc.), then Rekognition is for you. With Rekognition, you just pass in an image (or video), and it does all the work of figuring out what’s in the image.
In this short hands-on tutorial, we’ll create an S3 bucket and upload images to it. Then using the AWS SDK (Python) in Cloud9, we’ll write some simple code to retrieve the images and detect what they are.
The code used in the demo can be found here: https://docs.google.com/document/d/1we-ozSdAFUBRDgLO-3YcI65TkJ0h4xZzhjESXjKkKHM/edit?usp=sharing
00:00 – Overviewing Rekognition and how we’ll be using it for image recognition
01:14 – Creating an S3 bucket and uploading images to use with Rekognition
02:05 – Using the AWS SDK (Python) Rekognition code to detect_labels for the images in S3 (using Cloud9 IDE)
04:06 – Reviewing the label results for the car image
05:10 – Reviewing the label results for the person image
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