I have trained a custom YoloV4, single class object detector using AlexeyAB's darknet.
The best weight files of my model result in the following performance
I obtained this evaluation using the command,
darknet.exe detector map data/obj.data yolo-obj.cfg backup\yolo-custom-best.weights
Upon running the model on a video, I get around 25 fps.
My Question is : When I read articles about YOLO, they claim that it detects in milliseconds (ms). Why is my model showing detection time of 5 seconds but comparable in FPS to other, much faster models?
- Is the detection time shown in the image (returned by the given command), something different? (If yes, then how do I find how fast my model is?)
- If No, how to make it faster?
Please note that the detection time mentioned in the paper, which is the same as the one mentioned in the GitHub repo here is assuming it's run on a
single batch
at test time on aTesla V100
GPU. In addition to these factors, the runtime also varies according to the size of the input imageIn case you are using a different GPU or the CPU, it shouldn't be surprising for you to find longer detection times. The same goes with the FPS