CODEWITHSUNDEEP
computer-visionobject-detectionyolodarknetyolov4
varungupta
varungupta

Reputation: 154

Custom YoloV4 Detection Time

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

metrics of my model trained on google colab

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?

Upvotes: 0

Views: 301

Answers (1)

Jitesh Malipeddi
Jitesh Malipeddi

Reputation: 2385

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 a Tesla V100 GPU. In addition to these factors, the runtime also varies according to the size of the input image

In 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

Upvotes: 1

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