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This project is used to compare two model that is being made using Support Vector Machine (SVM) algoritm that is being trained by using one dataset, but the model is trained using a dataset that is being preprocessed using some preprocessing techniques, while the other one is just the plain image dataset.

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yawpie/fruit-classification-svm

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Apple Detection using Support Vector Machine (SVM)

Installation

To run the notebooks inside the src please use Python version 3.12.2

Dependencies

To run the scripts please install these libraries:

  1. Numpy
  2. Pandas
  3. Matplotlib
  4. OpenCV

Description

This repository is used to store and save progress for Digital Image Processing Labs Project

Dataset

Dataset used for this project can be found here. Alternatively you can use this instead if the dataset above is too big.

About

This project is used to compare two model that is being made using Support Vector Machine (SVM) algoritm that is being trained by using one dataset, but the model is trained using a dataset that is being preprocessed using some preprocessing techniques, while the other one is just the plain image dataset.

Topics

python opencv image svm scikit-learn jupyter-notebook image-processing pandas pca-analysis pca image-classification matplotlib preprocessing svm-model svm-classifier glcm pyplot matplotlib-pyplot

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