Comments (3)
That table shows the performance of the yolov4-tiny mask/nomask detection on darknet:
AP of nomask | AP of masked | mAP | Recall | Average IoU | TP | FP | FN |
---|---|---|---|---|---|---|---|
73.93% | 94.53% | 84.23 % | 80% | 62.73 % | 3895 | 938 | 971 |
from ncnn-android-yolov4-tiny-custom.
@SunnyGrocery thanks for the information. it seems to me there is still room to get better performance, you can try:
https://github.com/Megvii-BaseDetection/YOLOX
from ncnn-android-yolov4-tiny-custom.
OK, but I haven`t enough time to optimize the project now. thanks for your advice. And also thanks for your suggestions so much ~
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