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Using global feature descriptors and machine learning to perform image classification

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Image Classification using Python and Machine Learning

This repo contains the code to perform a simple image classification task using Python and Machine Learning. We will apply global feature descriptors such as Color Histograms, Haralick Textures and Hu Moments to extract features from FLOWER17 dataset and use machine learning models to learn and predict.

Summary of the project

  • Global Feature Descriptors such as Color Histograms, Haralick Textures and Hu Moments are used on University of Oxford's FLOWER17 dataset.
  • Classifiers used are Logistic Regression, Linear Discriminant Analysis, K-Nearest Neighbors, Decision Trees, Random Forests, Gaussian Naive Bayes and Support Vector Machine.
  • Tutorial for this project is available at - Image Classification using Python and Machine Learning

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