Published Paper Details:

In the realm of interior design and construction, the selection of the granite slab is a crucial decision. To simplify this process, present a Granite Slab Classification System using images utilizing Convolutional Neural Networks (CNNs) and a Flask-based web interface, capable of categorizing granite slabs into four distinct types: Black Galaxy, SK Blue, Pearl White, and Ruby Red. This system, trained on a dataset comprising 2,505 training images and 751 testing images, offers a swift and precise means of identifying granite slabs based on their visual characteristics. Users can easily access information including granite name, color, price per square foot, availability location, and quality rating through the web interface, empowering professionals in the construction and interior design industry to make informed decisions when selecting granite slabs for their projects, thereby streamlining, and enhancing the selection process. This model demonstrates 97 % accuracy in classifying granite slabs based on their visual characteristics, enabling users to identify their desired granite type swiftly and accurately.