With Amazon Rekognition, you can identify thousands of objects (such as bike, telephone, building), and scenes (such as parking lot, beach, city). When analyzing video, you can also identify specific activities such as “delivering a package” or “playing soccer”.
In the first part of this lab, we will be using Amazon Rekognition Image API, DetectLabel to recognize objects in an image. The second part uses Amazon Rekognition Video API, StartLabelDetection to identify objects/labels within an MP4 video. It is an asynchronous API. Once we start the detection, we can periodically call GetLabelDetection to monitor the status. However, it is highly recommended to check out the Notification Channel feature which allows you to receive a SNS notification when the detection job is completed instead of periodically polling the status of the detection.
To run this lab, you need to have prerequisite section completed.
Click on the 1-object-detection.ipynb notebook.
Follow the instruction in the notebook to understand how you can detect objects and scenes using Amazon Rekognition.
In order to execute each cell, click on the “Run” button at the top or press “Shift+Enter”.
Make sure you use “conda_python3” kernel and execute all cells in order.