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Using AWS Rekognition and Python to Identify Objects / Text in Images


In this video, we'll use AWS Rekognition to identify driver's licenses using machine learning but without having to write any ML code.

Quick Jump: Demo Video

I recently had some client work where we needed to identify if a specific object existed within an image that a user uploaded. From there I discovered AWS Rekognition and here’s a quick introduction and demo of using it.

In the working example we go over how it works in the AWS console and then review a few lines of Python but you can absolutely apply this with any programming language since we’re just calling out to AWS Rekognition using the AWS SDK.

Demo Video


  • 0:47 – Demo of using AWS Rekognition in the AWS console
  • 1:49 – Uploading custom images to evaluate driver’s licenses
  • 4:40 – Extracting specific text out of a driver’s license
  • 5:25 – One way to apply this in a real web application
  • 7:07 – Writing a little Python script to upload images to AWS Rekognition
  • 9:05 – It’s $1 to process 1,000 images or $0.001 dollar per image
  • 9:38 – How the Python script works to get the image’s labels
  • 11:10 – Extracting text out of an uploaded image with the Python script
  • 11:55 – You can also train it with custom rules without writing machine learning code

What are you using AWS Rekognition on? Let me know below.

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