You're reading from MLOps with Red Hat OpenShift

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Published inJan 2024

PublisherPackt

ISBN-139781805120230

Edition1st Edition

Concepts

Machine Learning

Authors (2):

Ross Brigoli

Faisal Masood

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Start with updating the frontend code with the HTTP address for face-detection-app as in the refreshFaceCounter and takepicture functions. Keep in mind that your URL will be different.

Save and load the HTML file into your browser. The browser will throw a warning that the application is trying to capture video feed; allow the application to access the video feed. You will get a screen like the one shown in Figure 7.23.

Figure 7.23 – Application UI capturing video and inferencing

The web page captures the video stream from your laptop camera and displays it in the top area of the page. The middle area shows the image capture every 250 milliseconds as configured on the web page, and the bottom counter displays the number of images captured.

You will notice that the counter is continuously incremented while the person sits in front of the camera. This means that every 250 milliseconds, an image has been captured and...

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MLOps with Red Hat OpenShift

Published in: Jan 2024Publisher: PacktISBN-13: 9781805120230

Authors (2)

Ross Brigoli

Ross Brigoli is a consulting architect at Red Hat, where he focuses on designing and delivering solutions around microservices architecture, DevOps, and MLOps with Red Hat OpenShift for various industries. He has two decades of experience in software development and architecture.
Read more about Ross Brigoli

Faisal Masood

Faisal Masood is a cloud transformation architect at AWS. Faisal's focus is to assist customers in refining and executing strategic business goals. Faisal main interests are evolutionary architectures, software development, ML lifecycle, CD and IaC. Faisal has over two decades of experience in software architecture and development.
Read more about Faisal Masood

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