• The goal was to build and train Machine Learning Models for Image Object Classification and OCR analysis. The Ankercloud team developed two Machine Learning models to meet the outcome using AWS Sagemaker.
• The primary Model was developed mainly for pre-processing, object recognition & classification and creation of bounding boxes. The secondary Model was developed to perform Optical Character Recognition on the core blocks.
• The developed machine learning model detects wooden or plastic blocks known as core blocks within the images of core trays and calculates a bounding box.  It also identifies and classifies any written marking on the core rock itself and calculates a bounding box. It  then performs OCR on the core blocks to record what text values are written. Lastly, the model creates a JSON object with the bounding box information (box center, dimensions) and retrieved text so that it can be related back to the images.
• We have used Amazon S3 to store data for training. Amazon SageMaker Notebooks and Amazon Sagemaker Training Instances to train the model and save the latest model to Amazon S3. It is accessed from the Amazon SageMaker Inference endpoints. We also created a ML-Ops pipeline which includes steps for pre-processing, training, evaluation, conditional evaluation, and model registration using Amazon Sagemaker tools.

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