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WordSpotting with deep Convolutional Neural Network

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DeepTextSpotter

DeepTextSpotter: An End-to-End Trainable Scene Text Localization and Recognition Framework

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

Requirements

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

Installation

  1. Get the proper version of caffe
git clone https://github.com/MichalBusta/caffe.git
cd caffe
git checkout darknet

  1. build caffe
mkdir Release 
cd Release 
cmake -D CMAKE_BUILD_TYPE=Release -D BLAS=Open -D BUILD_SHARED_LIBS=Off ..
make 
make install (optionally)
  1. build project
cd "SOURCE dir" 
mkdir build
cd build
cmake ..
make 

Download models

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

Run webcam demo

python2 demo.py

Notes:

  • 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

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