Centroid tracking using DCV

[Ferhat Kurtulmuş]

On Tuesday, 28 February 2023 at 12:29:05 UTC, Sergey wrote:
> On Tuesday, 28 February 2023 at 12:08:14 UTC, Ferhat Kurtulmuş 
> wrote:
>> On Wednesday, 15 February 2023 at 17:32:33 UTC, Ferhat 
>> Kurtulmuş wrote:
>>> I heard you are not having fun enough with d today.
>>
>> Hello everyone,
>> We have mir.ndslice and dcv, and then we should be able to 
>> run, for instance, tinyYOLOv3 with video streams. I believe 
>> that such applications will attract more people's attention to 
>> d.
>>
>> Here is how it looks like and the source code:
>>
>> https://www.youtube.com/watch?v=m3ex9lDELfQ
>> https://github.com/aferust/dcv-tinyyolov3
>
> Great job. Could we have any comparison in the 
> performance/memory usage versus original solution in Python?

I have not conducted any comparisons yet. There are a lot of 
factors affecting performance. My old laptop lacks good cuda 
support, so I disabled the CUDA acceleration. I cannot give you a 
strongly backed test result, but I can say that preprocessing is 
not so costly in my example. The FPS drop is primarily due to 
onnxruntime itself. The preprocessing step only takes 2 or 3 
msecs. The newer versions of onnxruntime have various backend 
options for acceleration, such as CUDA, tensorrt, directML (uses 
directX).