Sharingan is a tool built on Python 3.6 using OpenCV 3.2 to extract news content as text from newspaper’s photo and perform news context extraction.
For more details and explanation, please refer the blog post here: http://vipul.xyz/2017/03/sharingan-newspaper-text-and-context.html
How it works?
Canny Edge Detection
Contour Approximation and Bound Box
The segmentation done above gives the following result after context extraction:
[‘residential terraces’, ‘busy markets’, ‘Puppies’, ‘inhumane conditions’, ‘popular e-commerce sites’, ‘Sriramapuram’, ‘Russell Market’, ‘issue licences’, ‘meeting conditions’, ‘positive impact’, ‘pet owners’, ‘R. Shantha Kumar’, ‘welfare ofﬁcer’, ‘Animal Welfare Board’, ‘India’] [‘Kittie’] [‘Compassion Unlimited’] [‘public spaces’, ‘Animal’, ‘rights activists’, ‘civic body’, ‘Bengaluru’], [‘BENGALURU’, ‘Bruhat Bengaluru Mahanagar Palike’, ‘Dane’, ‘English Mastiff’, ‘Bulldog’, ‘Boxer’, ‘Rottweiler’, ‘Bernard’, ‘Shepherd’, ‘Retriever’, ‘draft guidelines’, ‘sterilisation’, ‘pet dogs ’, ‘Owners’]
Installing OpenCV 3.2 from source Python 3.6
mkdir release && cd release
cmake -DBUILD_TIFF=ON \ -DBUILD_opencv_java=OFF \ -DWITH_CUDA=OFF \ -DENABLE_AVX=ON \ -DWITH_OPENGL=ON \ -DWITH_OPENCL=ON \ -DWITH_IPP=OFF \ -DWITH_TBB=ON \ -DWITH_EIGEN=ON \ -DWITH_V4L=ON \ -DWITH_VTK=OFF \ -DBUILD_TESTS=OFF \ -DBUILD_PERF_TESTS=OFF \ -DCMAKE_BUILD_TYPE=RELEASE \ -DBUILD_opencv_python2=OFF \ -DCMAKE_INSTALL_PREFIX=$(python3.6 -c "import sys; print(sys.prefix)") \ -DPYTHON3_EXECUTABLE=$(which python3.6) \ -DPYTHON3_INCLUDE_DIR=$(python3.6 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \ -DPYTHON3_PACKAGES_PATH=$(python3.6 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())") ..
The output of above will be similar to this: output
Setting up Sharingan
git clone firstname.lastname@example.org:vipul-sharma20/sharingan.git
pip install -r requirements.txt
IMPORTANT: You will require some corpora and trained models for the code to run. You can refer to: http://www.nltk.org/data.html
In : import nltk In : nltk.download()
Try out the code on Jupyter Notebook
docker build -t sharingan-docker .
docker run -p 8888:8888 -it sharingan-docker
I am no wizard. Big thanks to people who came up with these solutions and posts:
See here: Sharingan
This project is licensed under MIT License:
Copyright (c) 2017-2018: Vipul Sharma
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This project uses following external libraries, which have their own licenses:
- NLTK (https://github.com/nltk/nltk/blob/develop/LICENSE.txt) [Apache]
- OpenCV (https://github.com/opencv/opencv/blob/master/LICENSE) [BSD]
- NumPy (https://github.com/numpy/numpy/blob/master/LICENSE.txt)