Training models using Satellite imagery on Amazon Rekognition Custom Labels

How to access Sentinel-2 imagery

  • Use one of the browsers mentioned on the page https://registry.opendata.aws/sentinel-2/
  • Download imagery from the Amazon S3 bucket directly. Amazon S3 is a storage service that provides scalable and secure access for downloading and uploading data.

Find Sentinel-2 scene

Download image bands

Prepare False Color Sentinel-2 image

How to train and run Amazon Rekognition model

Create and label Dataset

  1. Create dataset
  2. Choose “Upload images from your computer”
  3. On the dataset page click “Add images”
  4. On the pop-up window, click Choose Files and choose files from your computer. Then click “Upload images”
  5. Create labels “active field”, “semi-active field”, “non-active field”
  6. Click “Start labeling”, choose images, and then click “Draw bounding box”
  7. On the new page, you can now choose labels and then draw rectangles for each label. After you’ve finished labeling you can switch to a different image or click “Done”.

Train and run the model

  1. On the projects page click “Create Project”
  2. On the project page choose “Train new model”
  3. Choose the dataset which we just created and then choose “Split training dataset” for the test dataset. Then click “Train”.
  4. Once the model is trained you can start making predictions.

Visualize the result

Conclusion

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I'm a senior machine learning engineer at Instrumental, where I work on analytical models for the manufacturing industry, and AWS Machine Learning Hero.

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Rustem Feyzkhanov

Rustem Feyzkhanov

I'm a senior machine learning engineer at Instrumental, where I work on analytical models for the manufacturing industry, and AWS Machine Learning Hero.

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