Awesome
Thundernet ncnn
the C++ version of thundernet with ncnn
模型均来自thundernet_mmdetection
在ncnn编译对应环境库替换include和lib
检测结果
欢迎各位开发者移植到移动端,并测试贡献耗时
本耗时测试为macos 单线程
MobileNetV2-YOLOv3 (来自ncnn bencnmark)
input shape | mAP | cost(ms) |
---|
352*352 | 0.715 | 67.79 |
thundernet_shufflenetv2_15_voc
input shape | mAP | cost(ms) |
---|
320*320 | 0.712 | 57.57 |
352*352 | 0.722 | 64.33 |
384*384 | 0.734 | 73.63 |
416*416 | 0.738 | 89.28 |
448*448 | 0.744 | 97.97 |
480*480 | 0.747 | 110.04 |
thundernet_shufflenetv2_15_voc_fpn
input shape | mAP | cost(ms) |
---|
320*320 | 0.73 | 67.71 |
thundernet_shufflenetv2_15_v2_voc (使用了coco预训练模型)
input shape | mAP | cost(ms) |
---|
320*320 | 0.749 | 64.51 |
480*480 | 0.778 | 137.49 |
thundernet_shufflenetv2_15_v2_coco
input shape | AP(0.5:0.95) | cost(ms) |
---|
320*320 | 0.22 | 72.68 |
mkdir build
cd build
cmake ..
make
./thundernet_voc ../imgs/person.jpg
./thundernet_fpn_voc ../imgs/person.jpg
./thundernet_coco ../imgs/person.jpg
检测结果展示