- Get the code. We will call the directory that you cloned Caffe into
$CAFFE_ROOT
# 1. realize scale-compensation anchor matching strategy
# 2. realize random cropping square patches from original image
git clone [email protected]:lippman1125/caffe_s3fd.git
cd caffe
git checkout ssd- Download fully convolutional reduced (atrous) VGGNet.
By default, we assume the model is stored in$CAFFE_ROOT/examples/s3fd/
2. Create the LMDB file.
```Shell
cd $CAFFE_ROOT
# 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:
# - $HOME/data/faces_database/FACE/lmdb/FACE_trainval_lmdb
# - $HOME/data/faces_database/FACE/lmdb/FACE_test_lmdb
# and make soft links at examples/VOC0712/
./data/FACE/create_data.sh
- Train your model .
./build/tools/caffe train --solver examples/s3fd/solver.prototxt --gpu 1 --weights examples/s3fd/VGG_ILSVRC_16_layers_fc_reduced.caffemodel
-
ROC of FDDB compared with official, as follow:
-
ROC of FDDB compared with SSH/MTCNN, as follow:
-
examples
