The implementation of DeepTextSpotter: An End-to-End Trainable Scene Text Localization and Recognition Framework : ICCV 2017.

• python2.7
• opencv 3.x with python bindings

1. Get the proper version of caffe

• or take required layers: Transpose, Reorg, Region, CTCLoss

• CTCLoss is warp around - https://github.com/baidu-research/warp-ctc - nice implementation, thanks!

git clone https://github.com/MichalBusta/caffe.git
cd caffe
git checkout darknet

2. build caffe

mkdir Release 
cd Release 
cmake -D CMAKE_BUILD_TYPE=Release -D BLAS=Open -D BUILD_SHARED_LIBS=Off ..
make 
make install (optionally)

3. build project

cd "SOURCE dir" 
mkdir build
cd build
cmake ..
make 

RPN: https://drive.google.com/open?id=0B8SUcdkLTcuTZjRHeUpjdzhmbFE OCR: https://drive.google.com/open?id=0B8SUcdkLTcuTMmI0TS1uNDJaZGs

the paths are hard-coded, models shoud be at models subdirectory

python2 demo.py

• The provided RPN model is tiny version of full "YOLOv2" detector (= demo runs at 7 fps on 1GB Nvidia GPU)
• For decoding final output, we provide just greedy and dictionary based prefix decoding