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 running 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. 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 my raspberry it also produces low fps rate 0.7.
Can someone suggest me something please? Is the reason related to the yolo models or opencv or python? How can I make the fps rate higher and faster for object detection with webcam?