CRPN is a two-stage detection framework for multi-oriented scene text. The code is modified from py-faster-rcnn.
-
Clone the CRPN repository
git clone https://github.com/xhzdeng/crpn.git
-
Build Caffe and pycaffe (see: Caffe installation instructions)
cd caffe-fast-rcnn make -j8 && make pycaffe
-
Build the Cython modules
cd $CRPN_ROOT/lib make
-
Prepare your own training data. It should have the basic structure followed PASCAL VOC dataset
Create symlinks for YOUR dataset cd $CRPN_ROOT/data ln -s [dataset_path] VOCdevkit
-
Download pre-trained ImageNet VGG-16 models
You can find it at [Caffe Model Zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
-
Train with YOUR dataset
cd $CRPN_ROOT ./experiments/scripts/train.sh [NET] [MODEL] [DATASET] [ITER_NUM] # NET is the network arch to use, only {vgg16} in this implemention # MODEL is the pre-trained model you want to use to initial your weights # DATASET points to your dataset # IETR_NUM
-
Test with YOUR dataset
cd $CRPN_ROOT ./experiments/scripts/test.sh [NET] [MODEL] [DATASET] # NET is the network arch to use, only {vgg16} in this implemention # MODEL is the resulting model you trained before # DATASET points to your dataset
Test outputs are saved under:
output/<experiment directory>/<dataset name>/<network snapshot name>/