Feline Image Analytics:Predicting Breed,Age,Gender,Stamina and Emotion

Understanding various aspects of cats, such as breed, emotion, age, gender, and stamina level, holds significance for humans in several ways. Firstly, it aids in establishing a deeper connection and bond between humans and their feline companions, fostering empathy and understanding. Secondly, it enables pet owners to provide tailored care that meets the specific needs of their cats, promoting their health and well-being. Additionally, recognizing these aspects helps in early detection of health issues and behavioral problems, allowing for prompt intervention and treatment. Moreover, understanding cat behavior and needs can contribute to a more harmonious coexistence between humans and cats, enhancing the overall quality of life for both parties. Traditional methods of obtaining advice on cat care, such as consulting veterinarians or purchasing specialized books, can indeed be costly for some individuals. Furthermore, access to reliable forums or online communities where pet owners can seek guidance may be limited in certain regions or communities. This lack of accessible resources can pose challenges for individuals seeking information on how to properly care for their cats, potentially leading to misinformation or inadequate care practices. A completely working web application that can predict cat breed,age,gender,emotion,stamina level using Convolutional Neural Network {CNN) based transfer learning models,specifically EfficientNet-b0 is suggested. System will take the essential characteristics from images of the cat to predict the aforementioned attributes. The collected findings indicate that the cat attribute prediction ranges from 48.05% to 100% when tested against four CNN-based models.