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在pytorch-yolov3的基础上加入了DropBlock和Label Smoothing,Gridmask和mosaic数据增强等进行口罩检测

License: GNU General Public License v3.0

Shell 9.98% Python 90.02%

yolov3's Introduction

说明

PyTorch-YOLOv3 原作者:https://github.com/eriklindernoren/PyTorch-YOLOv3

使用改进的yolov3来进行口罩检测 在原始项目的基础上增加了一下改变: 1.加入了DropBlock和Label Smoothing的 2.加入了Gridmask和mosaic数据增强

Installation

$ cd YoloV3/
$ sudo pip3 install -r requirements.txt
$ cd weights/
$ bash download_weights.sh

Download data

链接:https://pan.baidu.com/s/1o3zUOicC9HEJpgja4nr-eQ 
提取码:b6uh
将数据集解压到data下面

Train

$ python3 train.py --model_def config/yolov3-custom.cfg --data_config config/custom.data --regular_mode 3 --mode 3

1.单独使用DropBlock和Label Smotthing

$ python3 train.py --model_def config/yolov3-custom.cfg --data_config config/custom.data --regular_mode 3

2.单独使用Gridmask和mosaic数据增强

$ python3 train.py --model_def config/yolov3-custom.cfg --data_config config/custom.data --mode 3

Test

$ python test.py --weights_path checkpoints/yolov3_ckpt.pth

Inference

$ python3 detect.py

对比结果

原始

改进

yolov3's People

Contributors

ciroi avatar

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