andikarachman/Non-Deep-Learning-Grocery-Product-Classification

Perform grocery product classification based on feature detection and description

Non-Deep Learning Grocery Product Classification

This software uses OpenCV's feature detection and description to perform classification of grocery products. To use this, you first need to extract and describe keypoints using this repo. Please see the demo of the software in the demo.mp4 file.

Dependencies for Running Locally

• cmake >= 2.8
  • All OSes: click here for installation instructions
• make >= 4.1 (Linux, Mac), 3.81 (Windows)
  • Linux: make is installed by default on most Linux distros
  • Mac: install Xcode command line tools to get make
  • Windows: Click here for installation instructions
• OpenCV >= 4.1
  • This must be compiled from source using the -D OPENCV_ENABLE_NONFREE=ON cmake flag for testing the SIFT and SURF detectors.
  • The OpenCV 4.1.0 source code can be found here
• gcc/g++ >= 5.4
  • Linux: gcc / g++ is installed by default on most Linux distros
  • Mac: same deal as make - install Xcode command line tools
  • Windows: recommend using MinGW

Basic Build Instructions

1. Clone this repo.
2. Put the directory of the build file of your OpenCV in the CMakeLists.txt.
3. Put all of the products detected keypoints files (the ones with txt filetype) in ref/keypoints/ folder. Some examples are provided for references.
4. Put all of the products keypoints descriptors files (the ones with xml filetype) in ref/descriptors/ folder. Some examples are provided for references.
5. Make a build directory in the top level directory: mkdir build && cd build
6. Compile: cmake .. && make
7. Run it: ./product_classification.

Video Demo

Video Demo