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refinedet's Introduction

Single-Shot Refinement Neural Network for Object Detection

fork from https://github.com/sfzhang15/RefineDet

Introduction

添加widerface数据集训练脚本

Contents

  1. Installation
  2. GetData
  3. Training
  4. Demo

Installation

  1. Get the code. We will call the cloned directory as $RefineDet_ROOT.
https://github.com/ycdhqzhiai/RefineDet.git
  1. Build the code.
cd $RefineDet_ROOT
mkdir build
cd build
cmake ..
make -j8

GetData

  1. download datasets.
    网盘链接: https://pan.baidu.com/s/10ZFFIgbp7H3bveyViMwkug#list/path=%2F
    密码：uc5s
  2. 解压.
unzip XXX.zip
  1. 生成VOC格式数据.
python face_labels.py
  1. 生成lmdb.
# You can modify the parameters in create_data.sh if needed.
# It will create lmdb files for trainval and test with encoded original image:
#   - $HOME/data/VOCdevkit/VOC0712/lmdb/VOC0712_trainval_lmdb
#   - $HOME/data/VOCdevkit/VOC0712/lmdb/VOC0712_test_lmdb
# and make soft links at examples/VOC0712/
cd $RefineDet_ROOT
./data/wider_face/create_data.sh

5.建立软链接.

cd face_data
ln -s $wider_face_trian_lmdb trainval_lmdb
ln -s $wider_face_test_lmdb test_lmdb

6.生成测试集name_size.txt.

cd $RefineDet_ROOT/data/wider_face/
bash create_list.sh

Training

bash train.sh

Demo

# For GPU users
python test/refinedet_demo.py
# For CPU users
python test/refinedet_demo.py --gpu_id -1

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