Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) : Jetson
• DeepStream Version 5.0 DP
• JetPack Version (valid for Jetson only) 4.4 dev kit
• TensorRT Version : 7.1.3.0
Hi guys,
In your opinion, Is it possible to use deep stream for custom app? for example : face recognition
That’s mean I want to use decode multi-stream and one detector of deep stream for face detection, but for face recognition, the deep stream doesn’t support any model for this task, I want to know How I can integrated the face rec system to deep steam? I want to get outputs like counting and coordinates of deep stream, Is it possible?
@LoveNvidia
Face recognition can be understood as a classification task.
DeepStream pipeline supports detection + classification scenarios.
You can find a sample of such pipeline in <where_ds_is_installed>/deepstream-5.0/sources/apps/sample_apps/deepstream-test2
You right, But for face recognition I need also search in database for persons, I need to get similarity for feeded images in database, for this problem How do I do? How I can to add the search of persons codes into deepstream system?
@LoveNvidia
You can do that. But DS pipeline is data buffer driven so it is susceptible to any disturbance of other jobs & executions if they are synchronized. You should try to make these extra operations asynchronized to minimize negative effects to performances.
@ersheng
You mean is that I need to write custom gstreamer plugin for extra operation and then I need to add into pipeline? after face rec(classification) plugin? If so, How I can to see what’s the classification outputs in pipeline?
and in the gstreamer concept every plugin has srouce and sink pads, right? sink pad is input or output of plugin?
@LoveNvidia
I did not mean you should add a new gsteamer plugin to do this. I mean any extra operation like file & network reading/writing or database update/query may affect pipeline performance if these operations are synchronized. Any async implementation is okay.