NeuralMango: Advanced Mango Classification and Price Prediction

The mislabeling of mangoes in local Pakistani markets unfairly impacts buyers, who frequently end up paying a premium for a cheaper type of mango fruit. To address this issue, our study employs advanced deep learning techniques, specifically leveraging the EfficientBNet2 model. This model aids in providing consumers with accurate information about the mangoes they purchase, including details on daily government-set prices for these varieties. We've developed a user-friendly Flutter app supported by the predictive capabilities of the EfficientBNet2 model, enabling buyers to make informed decisions. Our research aims to bridge the gap caused by mango mislabeling in Pakistani markets, ultimately preventing buyers from falling victim to price discrepancies in various types of mangoes. By utilizing EfficientBNet2 and TensorFlow, our goal is to furnish users with real-time pricing data and comprehensive product information. The creation of the Flutter app serves to empower buyers by putting this predictive technology directly into their hands. The significance of this study lies in its potential to simplify the buying process for everyday consumers through the application of deep learning models. Furthermore, by providing accurate pricing information, we anticipate contributing to greater stability within the local mango market.