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v0.7.1-beta
Pre-release
Pre-release
Intel® Deep Learning Streamer Pipeline Server Release v0.7.1
Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Server, formerly known as Video Analytics Serving, is a python package and microservice for deploying hardware optimized media analytics pipelines. It supports pipelines defined in GStreamer* or FFmpeg* media frameworks and provides APIs to discover, start, stop, customize and monitor pipeline execution. Intel® DL Streamer Pipeline Server is based on Intel® DL Streamer and FFmpeg Video Analytics.
What's Changed
Title | Description |
---|---|
Product name change | Video Analytics Serving is now called Intel® Deep Learning Streamer Pipeline Server as it is part of the Intel® DL Streamer product suite. |
Breaking API change: Pipeline instances are now uuid strings | Pipeline instances created by different services can now be uniquely identified. Applications that depended on pipeline instances being integer values must be updated to handle strings. |
What's New
Title | Description |
---|---|
Kubernetes Load Balancing Sample | Show how to use MicroK8s with the HAProxy load balancer to distribute work across pods in a cluster |
REST API endpoint to list all pipeline instances | Endpoint GET /pipelines/status returns all pipeline instances as an array of status objects. |
REST API status and stop endpoints no longer require pipeline name and version | The following endpoints have been added.
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VA Client enhancements | The following features have been added to support the Kubernetes sample.
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What's Fixed
Description | Issue |
---|---|
Prevent pipeline instances from resetting | #58 |
REST API for status and stop ignores pipeline name and version | #92 |
EdgeX sample fails when run from behind a proxy | #97 |
REST service fails to start due to soft_unicode import error | #101 |
Known Issues
Known issues can be found as GitHub issues. If you encounter defects in functionality, please submit an issue.
Description | Issue |
---|---|
Docker build fails if directory name contains spaces | #38 |
Models can be picked up from previous build | #71 |
Difficult to get normalized coordinates for spatial analytics parameters | #87 |
Some public models from Open Model Zoo do not produce inference results | #89 |
Pipeline failure in some multi-GPU systems | #98 |
Intermittent 30s delay in pipeline start during multi-stream sessions | #104 |
Kubernetes deployment fails if no_proxy contains * | #105 |
VA Client reports incorrect average fps across multiple streams | #106 |
Tested Base Images
Supported base images are listed in the Building Intel(R) DL Streamer Pipeline Server document.
* Other names and brands may be claimed as the property of others.