Build computer vision pipelines with OpenCV on Google Axion
Introduction
Understand OpenCV on Google Axion C4A
Create a firewall rule for OpenCV browser visualization
Create a Google Axion C4A Arm virtual machine
Build OpenCV pipelines on Google Axion
Use machine learning models with OpenCV on Google Axion
Next Steps
Build computer vision pipelines with OpenCV on Google Axion
Who is this for?
This is an introductory topic for DevOps engineers, software developers, and AI practitioners who want to build and run computer vision pipelines on SUSE Linux Enterprise Server (SLES) Arm64 using OpenCV, process images and videos, visualize outputs in real time, and integrate ML models.
What will you learn?
After completing this Learning Path, you'll be able to perform the following tasks:
- Install and configure OpenCV on Google Cloud C4A Axion Arm64 virtual machines (VMs).
- Build image processing pipelines using OpenCV.
- Develop video processing pipelines with real-time frame updates.
- Visualize OpenCV outputs in the browser using an HTTP server.
- Integrate OpenCV pipelines with machine learning models.
Prerequisites
Before starting, you'll need the following prerequisites:
- A Google Cloud Platform (GCP) account with billing enabled
- Basic familiarity with Python and Linux command line
- Understanding of basic image and video processing concepts
Summary
This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
You’ll build browser-based computer-vision pipelines with OpenCV on a Google Cloud C4A Axion VM. First, you’ll provision a SUSE Linux VM, open port
8000, and prepare a Python 3.11 virtual environment. Then, you’ll create image and video pipelines that process frames and serve updated output through an HTTP server. Finally, you’ll add a machine learning model, stream its visual predictions, and validate the output from the VM’s external IP address.