Rubik Pi3 how to get inference time object detection

Hi, I want to do a benchmark of the inferencing time of various YOLO models on the Rubik Pi3. I’m having trouble getting to the inference times. I send detections via appsink to a Python script that calculates the inference time based on the time difference between the sent detection buffers. The problem is that by not setting a frame-rate in the pipeline I always get an inference time of 33ms, regardless of the size of the model. On the other hand, when I increase the frame-rate, the inference time increases by a few ms. Is there any way to effectively get to the inference time to calculate FPS from the buffer information?
I am uploading my pipeline below:

“”"
qtimetamux name=metamux ! queue ! qtioverlay ! queue ! waylandsink sync=true fullscreen=false
qtiqmmfsrc name=qmmf camera=0 !
video/x-raw(memory:GBM),format=NV12 !
tee name=split ! queue ! metamux.
split. ! queue name=detect_q ! qtimlvconverter ! queue !
qtimlsnpe delegate=dsp model={args.model_path} layers=“</model.22/Mul_2, /model.22 /Sigmoid>” !
queue ! qtimlvdetection name=detection threshold={args.detection_threshold * 100} results={args.max_detections} module=yolov8 labels={args.labels_path} !
text/x-raw, format=utf8 !
queue ! tee name=split2
split2. ! queue ! metamux.
split2. ! queue ! appsink name=sink emit-signals=true sync=true drop=false
“”"

Greetings

Dear customer,we are currently syncing this issue internally.

Dear customer
Before and after the function ①, obtaining the timestamps and calculating the difference will provide the exact inference time.

Okay I will try it, thank you

This is the time of the model inference itself, but what if I want to get the time of total processing of one frame with pre and post processing included

Dear customer
What does “total processing time” specifically refer to? Is it the time from when a frame request command is issued until the display is completed (including inference time)?

I mean the time from issuing the frame request command to getting the coordinates of the bounding boxes, because let’s say I don’t need a display, which in itself takes some time.

Dear customer
One terminal executes object detection, while another terminal executes the following commands to obtain the time of issuing the frame request command:

journalctl -o short-iso-precise -f  | grep process_capture_request

for example:


After function ①, obtain the time of getting the coordinates of the bounding boxes.