This project focuses on developing a multiclass image classification system. Image classification is a task of assigning a label to an image based on its content. In multiclass image classification, each image can be classified into one of multiple categories or classes.
The project utilizes various machine learning and computer vision techniques for image classification. This includes preprocessing techniques such as resizing, normalization, and feature extraction. Additionally, different classification algorithms such as Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Decision Trees, and Logistic Regression are explored and compared for their effectiveness in classifying images.
To run the code in this repository, you'll need Python 3.x along with the following libraries:
- OpenCV
- NumPy
- scikit-learn
- PIL (Python Imaging Library)