Potato Library

A custom C++ library for RMA-techniek used to classify defects in patatos.

Prerequisites

Before using this library, ensure that you have OpenCV installed.

# On Ubuntu
sudo apt-get install libopencv-dev

# On macOS
brew install opencv

Installation

Clone this repository and add the folder to your project e.g.

your_project/libs/potato-library

Usage

Include headers: In your client application, include the necessary headers from the Potato library.

#include "libs/potato-library/PotatoClassifier.h"
#include "libs/potato-library/Prediction.h"

Add the openCV dependency to your project

Add the following to your CMakeList.txt:

find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
target_link_libraries(your_client_app PRIVATE ${OpenCV_LIBS})

Link against the library

Link your client application against the Potato library.

Add the following to your CMakeLists.txt:

add_library(your_client_app STATIC
        libs/potato-library/PotatoClassifier.cpp
        libs/potato-library/PotatoClassifier.h
        libs/potato-library/Prediction.cpp
        libs/potato-library/Prediction.h
        libs/potato-library/PotatoClass.cpp
        libs/potato-library/PotatoClass.h)

target_include_directories(your_client_app PRIVATE libs/potato-library)

target_link_libraries(your_client_app PRIVATE potato_library)

Make sure to replace your_client_app with the actual name of your client application file.

Use the library: Now, you can use the functionality provided by your Potato library in your client application.

int main() {
    PotatoClassifier classifier("path/to/your/model.onnx");
    Prediction result = classifier.classify("path/to/your/image.jpg");

    // Use the prediction result as needed
    // ...

    return 0;
}```