Canine Breed Classification and Health Insights

Abstract

A web application that incorporates deep learning for precise dog breed identification along with customized Canine healthcare advice is shown in this research. The Django framework, which is used in the development of the application, offers a dependable and expandable backend for processing data, integrating APIs, and authenticating users. The system successfully classifies a variety of dog breeds by utilizing the VGG16 convolutional neural network architecture, which was trained on an extensive collection of dog photos. The program offers customized health advice after successful breed identification, encompassing breed-specific susceptibilities to common diseases, suggested vaccinations and screenings, food recommendations, and grooming needs. Through the integration of cutting-edge image recognition technology, breed-specific health data, and an intuitive Django-powered interface, this ground-breaking platform equips dog owners with the information and tools they need to proactively address their pet's particular healthcare requirements, ultimately improving their general well-being. With only a few clicks, users can upload photos, get immediate breed identification results, and access pertinent health information thanks to the user interface's easy-to-use design.