Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) Tesla T4
• DeepStream Version Deepstream v5.0
• TensorRT Version TensorRT 7.0
• CUDA Version 10.2
• NVIDIA GPU Driver Version (valid for GPU only) GPU Driver 440.100
• Docker Image I am using deepstream docker image from NGC
I am running a modified version of deepstream-test5 example on 2 rtsp stream from camera. With only PrimaryGIE, the application run smoothly at around 30fps each (perf-measurement). I want to implement a simple custom model that I have deserialized to .engine model as a SecondaryGIE, and get output as tensor-metadata.
The deepstream app compile without fail, and when running the app, pipeline was created successfully. However, while at first the fps is around 25~30, gradually this measurement will reach 0.0, and will not go up. Some of the times this happen right after starting pipeline, while some other times this may happen after 10~30mins of running deepstream.
I have changed the config file as well as adding a bit of code into deepstream_test5_app_main.c to get tensor-metadata (which I learn from deepstream_infer_tensor_meta example). In the config file for secondaryGIE, I disable classifier-async-mode, since I need the tensor metadata often, and have noticed that turning this on allow deepstream to run with no problem also.
I have include all files that I have modify in the drive, including my model engine. In deepstream_test5_app_main.c I only added a bit in function generate_event_msg_meta (from around line 526): https://drive.google.com/drive/folders/1ZfSFGEoobICD6O685w4WLckf-Um7VKhC?usp=sharing
Is there some sort of performance issue or memory issue with the SecondaryGIE? Or is there simply something wrong with my config properties?