How to Install and Uninstall python36-azure-media-videoanalyzer-edge Package on openSuSE Tumbleweed

Last updated: November 22,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "python36-azure-media-videoanalyzer-edge" package

In this section, we are going to explain the necessary steps to install python36-azure-media-videoanalyzer-edge on openSuSE Tumbleweed


    
        
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                sudo zypper refresh
            
                    
    
    Copied


    
        
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                sudo zypper install
            
                        
                python36-azure-media-videoanalyzer-edge
            
                    
    
    Copied

2. Uninstall "python36-azure-media-videoanalyzer-edge" package

This is a short guide on how to uninstall python36-azure-media-videoanalyzer-edge on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python36-azure-media-videoanalyzer-edge
            
                    
    
    Copied

3. Information about the python36-azure-media-videoanalyzer-edge package on openSuSE Tumbleweed

Information for package python36-azure-media-videoanalyzer-edge:
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Repository : openSUSE-Tumbleweed-Oss
Name : python36-azure-media-videoanalyzer-edge
Version : 1.0.0b3-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 1,3 MiB
Installed : No
Status : not installed
Source package : python-azure-media-videoanalyzer-edge-1.0.0b3-1.1.src
Summary : Microsoft Azure Video Analyzer Edge SDK Library for Python
Description :
Azure Video Analyzer provides a platform to build intelligent video applications that span the edge and
the cloud. The platform offers the capability to capture, record, and analyze live video along with
publishing the results, video and video analytics, to Azure services in the cloud or the edge. It is
designed to be an extensible platform, enabling you to connect different video analysis edge modules
(such as Cognitive services containers, custom edge modules built by you with open-source machine
learning models or custom models trained with your own data) to it and use them to analyze live video
without worrying about the complexity of building and running a live video pipeline.
Use the client library for Video Analyzer Edge to:
* Simplify interactions with the Microsoft Azure IoT SDKs
* Programmatically construct pipeline topologies and live pipelines