Cat Breed Auto Identify Photo 0.5.2

Application Overview
The application allows users to identify cat breeds through images using their device's camera or image gallery.

Functionality
The application employs a neural network, specifically the EfficientNetV2 architecture, to analyze submitted photos. It generates hypotheses regarding the breed depicted in each image. The updated classifier demonstrates a more stringent response, primarily recognizing real cats while generally disregarding illustrations, cartoons, toys, dogs, other animals, and human images.

Recognition Accuracy
The system is trained on a dataset encompassing 62 cat breeds derived from 13,000 photographs. In this iteration of the application, the recognition accuracy stands at 63% based on a validation set of 2,000 images not included in the training process, and an impressive 86% across all available photos. The training database is actively being enhanced, which will lead to improved breed recognition and increased accuracy in future releases.

Future Objectives
The application aims to continuously enrich the training dataset with user-submitted photographs. This initiative will contribute to expanding the variety of recognized cat breeds and enhancing overall recognition accuracy. Ultimately, the project's goal is to develop an expert system capable of identifying every known cat breed from photographic evidence.