Frequently Asked Questions¶
Is VVAS open source?
Yes.
What type of licensing options are available for VVAS source code (package)?
VVAS Release has been covered by below mentioned licenses:
Apache License
Version 2.0
3-Clause BSD License
GNU GENERAL PUBLIC LICENSE
The MIT License
What platform and OS are compatible with VVAS?
VVAS is tested on PetaLinux for embedded platforms. For more information about supported platforms, refer to Platforms And Applications.
Which AI models are supported with VVAS?
The following models are supported for this release:
resnet50
resnet18
mobilenet_v2
inception_v1
ssd_adas_pruned_0_95
ssd_traffic_pruned_0_9
ssd_mobilenet_v2
ssd_pedestrian_pruned_0_97
plate detection
yolov3_voc_tf
yolov3_adas_pruned_0_9
refinedet_pruned_0_96
yolov2_voc
yolov2_voc_pruned_0_77
densebox_320_320
densebox_640_360
Semantic Segmentation
How do I enable models that are not officially supported?
Does this mean models not supported by Vitis AI? If the model is not in DPU deployable format, then it first needs to be converted into DPU deployable state. For this refer to Vitis AI 2.0 documentation.
What is the version of Vitis AI tool used for VVAS?
This VVAS release supports Vitis AI 2.0.
Is VVAS compatible with lower versions of Vitis AI tools, such as VAI 1.3?
No, it has dependencies on Vitis AI 2.0.
How can I change the model in the pipeline?
The model name to be used for inferencing has to be provided in the JSON file for dpuinfer. For more details, see DPU Infer.
Can the model be changed dynamically?
while a pipeline is running, the model details cannot change. To change the model’s details, stop the running pipeline, and then update the JSON file. Re-start the pipeline.
What types of input streams are supported?
H.264, H.265 encoded video streams
Raw video frames in NV12, BGR/RGB formats
Is receiving RTSP stream supported?
Receiving RTSP stream is supported by an open source plugin.
Is multi-stream processing supported (such as muletiple decode and detections)?
Yes, VVAS suports simultaneous execution of multiple instances of plugins to realize multistream decode and ML operations.
How do I develop kernel libraries
Refer to Acceleration s/w development guide.
Do I need FPGA design experience to develop video analytics applications with VVAS?
No. Using a platform that supports the required hardware/software components for the video analytics applications, you can directly use VVAS to realize your video analytics application with several reference solutions. Refer Platforms And Applications.
Is ROI-based encoding supported?
Yes. The ROI Plug-in that generates ROI data required for encoders.
Can I generate multiple outputs for a single input?
Yes. The vvas_xabrscaler
plug-in controls the multiscaler
kernel to generate up to 8 different resolutions for one input frame. This plugin, along with resize, can also do colorspace conversion.
Is audio analytics supported?
No.
Are there sample accelerated applications developed using VVAS?
Yes. There are sample accelerated platforms and applications provided that you can execute by following a few steps. Start at Platforms And Applications.
Is there support for multi-stage (cascading) network?
One can connect multipe instances of vvas_xdpuinfer
one after another to implement multi-stage cascading network and each ML instance will generate its own inference data separately. This is already supported in this release. However accumulation of inference data from several ML instances in a pipeline into a single meta data structure is not yet supported by plug-ins and this has to be done by the application.
How to debug VVAS application if there are any issues?
VVAS is based on GStreamer framework. It relies of debugging tools supported by GStreamer framework. For more details, you may refer to GStreamer Debugging Tools.
How do I check the throughput of VVAS application/pipeline?
Using GStreamer’s native fps display mechanism.
How do I compile and prune the model to be used?
Refer to Vitis AI 2.0 documentation.
How do I build plugins?
Refer to Building VVAS Plugins and Libraries.
What if I cannot find the information that i am looking for?
Contact support.