In this project, we used a UC Merced land use dataset that was available on Kaggle. The dataset was classified into 21 classes where there were agricultural lands, airplane pictures, baseball diamonds, beach,es and so on. Each class was stored in a separate folder. So the first step was to extract images from each folder.
The images are 256x256x3. After extracting the images, we have to shuffle them in order to enhance the process of learning for the model.