zeusees / Faceboxes
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FaceBoxes: A CPU Real-time Face Detector with High Accuracy
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Faceboxes 完整复现
- 经作者同意,我们更新了完整复现 @lippman1125
- 原始不需要修改caffe版本参见,该版本没有做稠密化。
- 更新了一版人脸识别windows demo, 链接: https://pan.baidu.com/s/1rKgUWtj3AIfHqjn_yARQHg 密码: xksi
Makefile.config已经修改了好了,使用GPU的方式
所以直接使用下面的命令编译:
make -j8
# Make sure to include $CAFFE_ROOT/python to your PYTHONPATH.
make pycaffe
make test -j8
# (Optional)
make runtest -j8
(1) 利用脚本wider_face_2_voc.py脚本把wider_face数据转换成VOC格式。并遮盖掉小于20x20的人脸。
脚本的位置在:
(2) 在wider_face_2_voc.py的同一级目录中创建wider_face文件夹,放解压好下载的wider数据,如图:
在caffe/data目录下创建faces_database文件夹,拷贝wider_face文件夹(前面生成的VOC格式数据),layout如图:
cd caffe
\# Create the trainval.txt, test.txt, and test_name_size.txt in data/FACE/
./data/FACE/create_list.sh
\# You can modify the parameters in create_data.sh if needed.
\# It will create lmdb files for trainval and test with encoded original image:
\# data/faces_database/FACE/lmdb/FACE_trainval_lmdb
\# data/faces_database/FACE/lmdb/FACE_test_lmdb
\# and make soft links at examples/FACE/
./data/FACE/create_data.sh
运行以下命令开始训练:
./build/tools/caffe train --solver examples/faceboxes/solver.prototxt
train.prototxt支持Anchor densification strategy
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