|
%!s(int64=2) %!d(string=hai) anos | |
---|---|---|
.. | ||
CMakeLists.txt | %!s(int64=6) %!d(string=hai) anos | |
README.md | %!s(int64=2) %!d(string=hai) anos | |
bikes.jpg | %!s(int64=6) %!d(string=hai) anos | |
cards.jpg | %!s(int64=6) %!d(string=hai) anos | |
jeep.jpg | %!s(int64=6) %!d(string=hai) anos | |
multiple-plates.jpg | %!s(int64=6) %!d(string=hai) anos | |
oneway.jpg | %!s(int64=6) %!d(string=hai) anos | |
patient.jpg | %!s(int64=6) %!d(string=hai) anos | |
slippery.jpg | %!s(int64=6) %!d(string=hai) anos | |
stop1.jpg | %!s(int64=6) %!d(string=hai) anos | |
stop2.jpg | %!s(int64=6) %!d(string=hai) anos | |
textDetection.cpp | %!s(int64=4) %!d(string=hai) anos | |
textDetection.py | %!s(int64=4) %!d(string=hai) anos |
This repository contains the code for Deep Learning based Text Detection Using OpenCV (C++/Python) blog post.
Text detection using OpenCV DNN
The text detection
scripts use EAST Model which can be downloaded using this link: https://www.dropbox.com/s/r2ingd0l3zt8hxs/frozen_east_text_detection.tar.gz?dl=1
Once the file has been downloaded (~85 MB), unzip it using tar -xvzf frozen_east_text_detection.tar.gz
.
After unzipping, copy the .pb
model file to the working directory.
To compile the text_detection.cpp
, use the following:
cmake .
make
Refer to the following to use the compiled file:
./textDetection --input=<input image path>
Refer to the following to use the Python script:
python text_detection.py --input <image_path>
Want to become an expert in AI? AI Courses by OpenCV is a great place to start.