thundernet ncnn

Related tags

Deep Learning ncnn thundernet
Overview

MMDetection_Lite

基于mmdetection 实现一些轻量级检测模型，安装方式和mmdeteciton相同

voc0712

voc 0712训练 voc2007测试 coco预训练 thundernet_voc_shufflenetv2_1.5

input shape mAP
320*320 0.71
352*352 0.722
384*384 0.734
416*416 0.738
448*448 0.744
480*480 0.747

coco2017

thundernet_coco_shufflenetv2_1.5

input shape AP(0.5:0.95)
320*320 0.22

移动端推理 ncnn project

thundernet_ncnn

Get Started

Please see GETTING_STARTED.md for the basic usage of MMDetection.

@article{mmdetection,
  title   = {{MMDetection}: Open MMLab Detection Toolbox and Benchmark},
  author  = {Chen, Kai and Wang, Jiaqi and Pang, Jiangmiao and Cao, Yuhang and
             Xiong, Yu and Li, Xiaoxiao and Sun, Shuyang and Feng, Wansen and
             Liu, Ziwei and Xu, Jiarui and Zhang, Zheng and Cheng, Dazhi and
             Zhu, Chenchen and Cheng, Tianheng and Zhao, Qijie and Li, Buyu and
             Lu, Xin and Zhu, Rui and Wu, Yue and Dai, Jifeng and Wang, Jingdong
             and Shi, Jianping and Ouyang, Wanli and Loy, Chen Change and Lin, Dahua},
  journal= {arXiv preprint arXiv:1906.07155},
  year={2019}
}
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Comments
  • All mAP are 0 at train stage.

    All mAP are 0 at train stage.

    你好, 在确认数据路径正确的情况下, 在训练thundernet_voc_shufflenetv2_1.5的过程中, 无论是否使用预训练模型,evaluate的结果都是0. 单独使用test.py测试weight中的pre-trained models的mAP是0.749. 请问,可能哪里出现问题了? image

    opened by agrichron 2
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