Tensorflow Yolo v3 project is running too slow

[PSINH5]

How to use all the cores available on my Intel machine for a Tensorflow Yolo v3 object detection project? I believe it is using only one core at a time. What we want is a much higher performance, something similar to this :- https://software.intel.com/en-us/articles/tips-to-improve-performance-for-popular-deep-learning-frameworks-on-multi-core-cpus

[nikos1]

Hello Parth,

YOLO v3 runs a bit slower than other networks. What is your inference device? CPU. GPU, MYRIAD? Tiny YOLO will run much faster if accuracy is acceptable in your application.

> I believe it is using only one core at a time.

How do did you find out? Using a profiler? I am seeing all CPU cores and GPU EUs utilized when I run YOLOv3.

What is you OS, Windows or Linux?

Are you using the OpenVino model optimizer to convert YOLO v3 pb to IR? What version of the OpenVino SDK are you using?

Cheers,

Nikos