It is the simplest classification model for the geometric shapes(Triangle, Rectangle, and Circles). Image of any geometric shape(Triangle, Rectangle, and Circles) is taken as input, and it predicts the numeric label corresponding to that shape,{(1->Triangle),(2->Circle),(3->Rectangle)}. It involves Feature extraction and Classification model (neural networks): (1) Feature extraction is used to extract the features from the provided image (number of Extracted features may varies from image to image) and reduce the dimensionality of feature set, in order to get a fixed number of features for each image. (2) Classification model takes the transformed features of the image dataset( 5 principal components) as inputs and outputs a label accordingly.
Shapes folder contain 60 images of different shapes(triangle,circle,rectangle), 20 of each class.
- PCA_shapes.m : Script to Extract features from images
- neural_shapes.m : Script for Classification model
- shapes.mat : Saved workspace from earlier run
- pca_shapes.csv : Extracted features used as input for classification model
- shapes(folder) : Contains images numbered from 1 to 60
- shaples_label : File storing the targets(labels) for the images dataset
Sourabh Garg sourabh.8.june.1996@gmail.com @codeSG