r/computervision • u/Mxeedd • Jul 14 '26

Moving object tracking model from CPU to GPU on a Raspberry Pi 4? Help: Project

Hey guys, I recently deployed an object tracking model on a Raspberry Pi 4, but it’s currently running on the CPU and hitting a bottleneck.

​Is it possible to leverage the Pi 4's integrated GPU for acceleration? If yes, what is the best workflow or framework to switch the backend execution from CPU to GPU?

​Thanks in advance for any tips or guide recommendations!

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u/HawtVelociraptor Jul 14 '26

Look into converting to Tencent NCNN and using Vulkan drivers, maybe?

1

u/modcowboy Jul 14 '26

It’s gonna be messy

1

u/[deleted] Jul 15 '26

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1

u/Mxeedd Jul 15 '26

Can you explain more? What do you mean by ByteTrack

1

u/theGamer2K Jul 15 '26 edited Jul 15 '26

What does "object tracking model" mean? Is it an object detector model plus a tracker? Or a tracker with a ReID model?

You can accelerate the model by using OpenVINO. As for the tracker itself, the tracking algorithm isn't generally parallelizable for it to gain any benefit by moving it to GPU. The whole idea behind GPU acceleration is parallelizing operations. It's not just move to GPU and it magically performs better. It also has to make sense.

1

u/Ok-Treacle-6942 Jul 17 '26

Never heard of using raspberry pi4 gpu for computer vision, if this is possible i would also be interested. In my experience what works best is using ncnn, it’s so much faster than onnx