Opencv 4 DNN, People detection CPU performance with yolo 2 tiny model
I am still working on tutorial how to simply run yolo and others model in opencv 4. I try to do as simple as possible. Not like a general sample in Opencv. Differently, simply, and described as much as possible.
Some technical specifications video Testing opencv 4.0 DNN with yolo tiny 2 model on people detection in a mall. Pure CPU, I7 (4 cores), running by the following command under windows 10. Performance for CPU without 2 much optimization effort is 500 ms per image approximately on my configuration. Let me know if there is some problem with the parameters. testOpecv.exe --config=C:\darknet-master\cfg\yolov2-tiny.cfg --model=C:\darknet-master\weights\yolov2-tiny.weights --classes=C:\opencv32\darknet-master\data\coco.names --width=616 --height=616 --scale=0.00192 --rgb
Sources: Thank you for a great job https://opencv.org/ https://pjreddie.com/darknet/yolo/
Some technical specifications video Testing opencv 4.0 DNN with yolo tiny 2 model on people detection in a mall. Pure CPU, I7 (4 cores), running by the following command under windows 10. Performance for CPU without 2 much optimization effort is 500 ms per image approximately on my configuration. Let me know if there is some problem with the parameters. testOpecv.exe --config=C:\darknet-master\cfg\yolov2-tiny.cfg --model=C:\darknet-master\weights\yolov2-tiny.weights --classes=C:\opencv32\darknet-master\data\coco.names --width=616 --height=616 --scale=0.00192 --rgb
Sources: Thank you for a great job https://opencv.org/ https://pjreddie.com/darknet/yolo/