Rao Muhammad Dayan Atif@Dayan_Atif

This Streamlit app enables users to upload images and have them classified using the pre-trained MobileNetV2 model. MobileNetV2, trained on the ImageNet dataset, is efficient and designed for mobile and edge devices. Users can upload a `.jpg`, `.png`, or `.jpeg` image, which is then displayed and resized to meet the model's input requirements (224x224 pixels). The image is preprocessed and passed to the model for prediction. Once the model generates predictions, the app decodes the results and shows the top predicted class label alongside the confidence score as a percentage. The app provides a simple, user-friendly interface for image classification, allowing real-time interaction with a powerful deep learning model. This application is ideal for users looking to explore image classification with minimal setup and a smooth interface, leveraging Streamlit's intuitive design and MobileNetV2's lightweight architecture for accurate and fast results.

The Medical AI Agent is a user-friendly Streamlit application designed to help individuals identify possible diseases based on their symptoms. Users can select symptoms from a predefined list, and the agent suggests potential diseases while also offering helpful health tips for managing those symptoms. The system uses a rule-based approach, where symptoms are mapped to relevant diseases through a pre-programmed dictionary. This tool is intended for quick and general health insights, but it is not a substitute for professional medical diagnosis or treatment. Its simple interface makes it accessible for non-technical users as well.

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