I'm having low fps for real-time object detection on my raspberry pi
I trained the yolo-darkflow object detection on my own data set using my laptop windows 10 .. when I tested the model for real-time detection on my laptop with webcam it worked fine with high fps 
However when trying to test it on my raspberry pi, which runs on Raspbian OS, it gives very low fps rate that is about 0.3 , but when I only try to use the webcam without the yolo it works fine with fast frames.. also when I use Tensorflow API for object detection with webcam on pi it also works fine with high fps
can someone suggest me something please? is the reason related to the yolo models or opencv or phthon? how can I make the fps rate higher and faster for object detection with webcam?
My detector on raspberry pi without any accelerator can reach 5 FPS.
I used SSD mobilenet, and quantize it after training.
Tensorflow Lite supplies a object detection demo can reach about 8 FPS on raspberry pi 4.
how to increase fps for raspberry pi for object detection