Hello all,
Description
I am testing objectDetector_Yolo from deepstream-6.0/sources/, my goal is to test the model latency using different input sizes for the trt engine, as expected the latency increases if I reduce the input image size, however I noticed that this is not the case for the engine file.
Below you’ll find the input sizes I have tried and the engine file I got from TensorRT.
Input Size | Engine file size (MB) | Deepstream FPS | gst-launch FPS |
---|---|---|---|
416x416 | 289 | 19 | 6.4 |
384x384 | 289 | 22 | 7.4 |
352x352 | 133 | 27 | 9.0 |
320x320 | 132 | 30 | 10.8 |
288x288 | 121 | – | – |
256x256 | 288 | – | – |
224x224 | 176 | – | – |
Is there any reason why the engine file decreases and then increases again ?
Does the engine file size has an impact on the % of GPU that will be used by the application ?
Environment
TensorRT Version: 8.2.1.8
Deepstream: 6.0
GPU Type: Jetson TX2NX
Jetpack: 4.62.2 [L4T 32.7.2]
CUDA Version: 10.2
CUDNN Version: 8.2.1.32
Operating System + Version: Ubuntu 18.04
Baremetal or Container (if container which image + tag): Baremetal
Steps To Reproduce
After following the instructions from the README file in /opt/nvidia/deepstream/deepstream-6.0/sources/objectDetector_FasterRCNN/ I change the width in height in yolov3.cfg with the values from the above table and finally, I run:
$ deepstream-app -c deepstream_app_config_yoloV3.txt