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https://github.com/DayBreak-u/thundernet_ncnn

the C++ version of thundernet with ncnn
https://github.com/DayBreak-u/thundernet_ncnn

ncnn thundernet

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the C++ version of thundernet with ncnn

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# Thundernet ncnn

## the C++ version of thundernet with ncnn

模型均来自[thundernet_mmdetection](https://github.com/ouyanghuiyu/thundernet_mmdetection)

在[ncnn](https://github.com/Tencent/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
![avatar](imgs/person_res.jpg)
![avatar](imgs/dog_res.jpg)