Increment package version after release of com.azure azure-media-videoanalyzer-edge (Azure#25070)

Author: azure-sdk

eng/versioning/version_client.txt

@@ -139,7 +139,7 @@ com.azure:azure-storage-internal-avro;12.1.3;12.2.0-beta.3
 com.azure:azure-storage-perf;1.0.0-beta.1;1.0.0-beta.1
 com.azure:azure-storage-queue;12.11.3;12.12.0-beta.3
 com.azure:azure-template-perf;1.0.0-beta.1;1.0.0-beta.1
-com.azure:azure-media-videoanalyzer-edge;1.0.0-beta.4;1.0.0-beta.5
+com.azure:azure-media-videoanalyzer-edge;1.0.0-beta.5;1.0.0-beta.6
 com.azure:azure-verticals-agrifood-farming;1.0.0-beta.2;1.0.0-beta.3
 com.azure:perf-test-core;1.0.0-beta.1;1.0.0-beta.1
 com.microsoft.azure:spring-cloud-azure-appconfiguration-config-web;1.3.0;1.4.0-beta.1

sdk/videoanalyzer/azure-media-videoanalyzer-edge/CHANGELOG.md

@@ -1,5 +1,15 @@
 # Release History
 
+## 1.0.0-beta.6 (Unreleased)
+
+### Features Added
+
+### Breaking Changes
+
+### Bugs Fixed
+
+### Other Changes
+
 ## 1.0.0-beta.5 (2021-11-09)
 
 - Added device discovery and device detail request for ONVIF enabled devices.

sdk/videoanalyzer/azure-media-videoanalyzer-edge/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>com.azure</groupId>
   <artifactId>azure-media-videoanalyzer-edge</artifactId>
-  <version>1.0.0-beta.5</version> <!-- {x-version-update;com.azure:azure-media-videoanalyzer-edge;current} -->
+  <version>1.0.0-beta.6</version> <!-- {x-version-update;com.azure:azure-media-videoanalyzer-edge;current} -->
 
   <name>Azure Video Analyzer Edge client library for Java</name>
   <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 videos 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. You can then 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 (https://github.com/azure/azure-iot-sdks) and programmatically construct pipeline topologies and live pipelines.</description>