It may already be released by someone, but I made a cooperative sample of RealSense D435 + Neural Compute Stick + MobileNet-SSD + RaspberryPi3.
Distance can also be measured while detecting objects.
I'm glad if you can use it as a reference.
This time, it is single stick + single thread.
By the way, sample of multistick + multithread is here.
PINTO why will it not work with 2.0 +? Is it because of the initialization ?
This sample uses programs created for the generation of NCSDK Ver1.
It seems that the call part of the API has been updated in Ver2.
I just did not test it with Ver.2.
I will make it correspond to Ver.2 in the near future.
How many fps were able to maintain.
By the way, I have not measured FPS for the following programs yet.
I will try it today. Please wait for a while.
Movie playback and detection are performed asynchronously.
Detection is probably about 8FPS for single threads and about 15FPS for 3 threads.
FPS changes according to the input resolution of the camera.
In order to prioritize speed, the input image is now dropped to 320x240, so it is a coarse image.
It corresponds to NCSDK Ver2.
Input image is 640x480.
I do not know whether the measurement method is correct, the performance is still 6.5 FPS.
It is an article written by me, but combined the following procedure.
Procedure for installing NCSDK v2.05.00.02 to RaspberryPi3(Raspbian Stretch)
Procedure for "make examples" NCSDK v2.05.00.02 RaspberryPi3(Raspbian Stretch) / Ubuntu16.04
Large screen support (over 1024x768) and multistick/multithread correspondence will be done next time.
The following sample program is compatible with NCSDK v 2.00.05.02 + MobileNetSSD(Caffe) + Asynchronous execution.
It was about 12 FPS with one stick.
Due to the influence of "Global Interpreter Lock", it does not seem to be able to raise the performance any further unless it corresponds to multiprocess.
Sample of Multistick + Multithread.
Hello. And I'm sorry many times.
It supports MultiProcessing. (Quad core)
It is a rough measurement result, but it is a play speed of about 25 FPS and a prediction rate of about 12 FPS.
It is out of frame because it is asynchronous.
I hope it will be helpful for everyone.
I was referring to @sggriset article.
Thank you very much!!
I tried combining Object Detection with MobileNetSSD and Transparent Background.
By using SSD, I succeeded transparent the background while responding to dynamically changing distances.
Because the load of image processing is high, although only performance of only 5FPS comes out…
It may be interesting to look at combination with face detection etc.
If you have a lot of money, that is the correct answer.
Performance of UP Board 2 is incomplete, so I would like you to try it on LattePanda Alpha+OpenVINO if you can.
I am poor so I can not try it.
I thought that many engineers wanted to know the marginal performance.
Seriously, I measured the performance for each number of sticks.
Video playback rate and detection rate are calculated separately.
In 4 core RaspberryPi 3 use of 3 stick or more seems to have no effect.
Video device ： USB Camera (No RealSense D435)
Input resolution ： 640x480
Output resolution ： 640x480
1 Stick = 6 FPS
2 Sticks = 12 FPS
3 Sticks = 16.5 FPS
4 Sticks = 16.5 FPS