I have a question to do, I’ve made tests with my HEF model on my Raspberry Pi 5, my Ubuntu Desktop (Workstation Dell Precision 3660) and my NPU module Hailo8L using a camera in the follow inference code:
import degirum as dg
import degirum_tools
import degirum_tools.streams as dgstreams
import os
# Limitar o número de threads para operações paralelas
#os.environ["OMP_NUM_THREADS"] = "2"
#os.environ["OPENBLAS_NUM_THREADS"] = "2"
#os.environ["MKL_NUM_THREADS"] = "2"
#os.environ["VECLIB_MAXIMUM_THREADS"] = "2"
#os.environ["NUMEXPR_NUM_THREADS"] = "2"
inference_host_address = "@local"
# inference_host_address = "@local"
# choose zoo_url
#desktop
zoo_url = "/home/gabriel/Desktop/rasp/hailo-rpi5-examples/resources/best_22-01_01_i640.json"
#raspberry
#zoo_url = "/home/pi/Desktop/hailo-rpi5-examples/resources/best_22-01_01_i640.json"
# set token
#token = degirum_tools.get_token()
token = ''
# token = '' # leave empty for local inference
#webcams
source1 = 0 # Webcam index
source2 = 2 # Webcam index
#videos desktop
source3 = "/home/gabriel/Desktop/rasp/hailo-rpi5-examples/resources/11_29_2024_11_50_00_cut1.avi" # Video file
source4 = "/home/gabriel/Desktop/rasp/hailo-rpi5-examples/resources/11_29_2024_11_50_00_cut2.avi" # Video file
source5 = "/home/gabriel/Desktop/rasp/hailo-rpi5-examples/resources/11_29_2024_11_50_00.avi" # Video file
#videos rasp
#source3 = "/home/pi/Desktop/hailo-rpi5-examples/resources/11_29_2024_11_50_00_cut1.avi" # Video file
#source4 = "/home/pi/Desktop/hailo-rpi5-examples/resources/11_29_2024_11_50_00_cut2.avi" # Video file
#source5 = "/home/pi/Desktop/hailo-rpi5-examples/resources/11_29_2024_11_50_00.avi" # Video file
# Define the configurations for video file and webcam
configurations = [
{
"model_name": "best_22-01_01_i640",
"source":source5,
"display_name": "Video/Cam-1",
},
#{
# "model_name": "best_22-01_01_i640",
# "source": source2,
# "display_name": "Video/Cam-2",
#},
]
# load models
models = [
dg.load_model(cfg["model_name"], inference_host_address, zoo_url, token)
for cfg in configurations
]
# define gizmos
sources = [dgstreams.VideoSourceGizmo(cfg["source"]) for cfg in configurations]
detectors = [dgstreams.AiSimpleGizmo(model) for model in models]
display = dgstreams.VideoDisplayGizmo(
[cfg["display_name"] for cfg in configurations], show_ai_overlay=True, show_fps=True
)
# create pipeline
pipeline = (
(source >> detector for source, detector in zip(sources, detectors)),
(detector >> display[di] for di, detector in enumerate(detectors)),
)
# start composition
dgstreams.Composition(*pipeline).start()
In both devices works well my HEF model, but I noticed that my FPS metric did not exceed 30 FPS.
Well, my doubt is about this, someone knows why do my FPS not exceed 30 FPS or have some guess? Is it a NPU limitation or a metric in the convertion or a hardware limitation (rasp and desk) or idk what else?
So, I understood that the camera FPS is the limiter, I agree with this, but in my situation, as you can see, that isn’t the case.
So, about this, do you have another guess? How I spoke in the first question, maybe is it a NPU limitation or a metric in the convertion (when I converted my model) or a hardware limitation or idk what else?
