@Frank Thank you for the explanation with the diagram. 
I have trained a model to detect a single class using yolov3. The detection seems fine on the CPU, however on the NPU, I have some issues with the non max suppression (as I get 2601 detections on a single image). Can you share your expereince, so it would help me to solve this problem?
These below are the parameter:
const int classes = 1;
const float thresh = 0.5;
const float hier_thresh = 0.5;
const float nms = 0.80;
const int numBBoxes = 5;
const int relative = 1;
const char *coco_names[1] = {“battery”};
float biases[18] = {10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326};
I even increased the nms value to 0.80, yet, I have the same issue. Please shed some input which can help me to solve the issue! Thanks in advance.
Please find the sample output.
Repeat 1 times, thread 1, avg time 85.24 ms, max_time 85.24 ms, min_time 85.24 ms
num_detections,2601
0: 100%
left = 245,top = 30
0: 100%
left = 253,top = 30
0: 100%
left = 269,top = 30
0: 100%
left = 385,top = 35
0: 100%
left = 102,top = 59
0: 100%
left = -23668,top = 51
0: 100%
left = 110,top = 51
0: 100%
left = -1333402262,top = 58
0: 100%