Vinlib

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🎯 About

Describe your project

✨ Features

✔️ Sift compare images;
✔️ C++ OpenCV code;
✔️ Node addon API;

🚀 Technologies

The following tools were used in this project:

• Node.js
• [C++]
• [OpenCV]

✅ Requirements

Before starting 🏁, you need to have Git and Node installed.

🏁 Starting

# OpenCV prerequisites

$ sudo apt update && sudo apt install -y cmake g++ wget unzip
$ wget -O opencv.zip https://github.com/opencv/opencv/archive/master.zip
$ unzip opencv.zip; rm opencv.zip
$ git clone https://github.com/opencv/opencv_contrib.git
$ cd opencv-master
$ mkdir -p build && cd build
$ cmake -DBUILD_SHARED_LIBS=OFF -DBUILD_LIST=calib3d,core,imgcodecs,features2d,imgproc,objdetect -DOPENCV_GENERATE_PKGCONFIG=YES -DWITH_GTK=NO -DWITH_PNG=NO -DWITH_JPEG=YES -DWITH_TIFF=NO -DWITH_WEBP=NO -DWITH_ITT=NO -DWITH_IPP=NO  -DBUILD_JASPER=NO -DWITH_OPENEXR=NO -DWITH_QUIRC=NO -DWITH_RT=NO -DWITH_OPENJPEG=NO -DWITH_JASPER=NO -DWITH_EIGEN=NO -DHIGHGUI_ENABLE_PLUGINS=OFF ..
$ make -j6
$ sudo make install
# Clone this project
$ git clone https://github.com/stsier/vinlib

# Access
$ cd vinlib
$ mkdir build; cd build


# Install dependencies
$ npm install -S node-addon-api
$ npm install -g cmake-js

# Build
$ cmake-js

# Or
~~$ npm install -g node-gyp~~
~~$ node-gyp configure~~
~~$ node-gyp build~~

# Build

# Test the project
$ node index.js

# Output
info.Env(): :  vs
[Extract Feature] Compute SIFT features using opencv sift
 [Extract Feature Sift]   keypoints: 3356; descriptors: [128 x 3356]; took 6758.45ms
[Extract Feature] Compute SIFT features using opencv sift
 [Extract Feature Sift]   keypoints: 4830; descriptors: [128 x 4830]; took 6671.97ms
[Good Matcher] took 71.613560ms
 Good match percentage: 96/3356==2.860548%%
 inliers: 26 / 96
[Homography Matcher] took 25.797964ms
 Filter match percentage: 27.083334%
------------------------ Flann matcher : 0.774732%
[Good Matcher] took 430.586592ms
 Good match percentage: 83/3356==2.473182%%
 inliers: 25 / 83
[Homography Matcher] took 18.470230ms
 Filter match percentage: 30.120483%
------------------------ BruteForce matcher : 0.744934%
[Good Matcher] took 402.348928ms
 Good match percentage: 88/3356==2.622169%%
 inliers: 24 / 88
[Homography Matcher] took 25.558200ms
 Filter match percentage: 27.272728%
------------------------ BruteForceSq matcher : 0.715137%

📝 License

This project is under license from MIT. For more details, see the LICENSE file.

Made with ❤️ by Sergei TSIER

🔗 References

Node js C++ OpenCV Python Homography OpenCV C++ Homography Filtering with Homography BEBILD

 

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