CRPN is a two-stage detection framework for multi-oriented scene text. The code is modified from py-faster-rcnn.

0. Clone the CRPN repository

   git clone https://github.com/xhzdeng/crpn.git
   

1. Build Caffe and pycaffe (see: Caffe installation instructions)

   cd caffe-fast-rcnn
   make -j8 && make pycaffe
   

2. Build the Cython modules

   cd $CRPN_ROOT/lib
   make
   

3. 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
   

4. Download pre-trained ImageNet VGG-16 models

   You can find it at [Caffe Model Zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
   

5. 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 
   

6. 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>/