This project applies machine learning to classify date fruit types into nine different classes. It utilizes TensorFlow to construct neural networks with convolutional layers for image recognition and classification. Additionally, it leverages OpenAI's ChatGPT to generate unique facts about each date fruit type, providing users with engaging and informative content. The web interface is built using Streamlit, offering an interactive and user-friendly experience.
Explore the Date Fruit Classifier and learn fascinating facts about different types of dates: Date Fruit Classifier Demo
- Transfer Learning: The model uses transfer learning from the MobileNet architecture to accurately classify date fruit types.
- Accuracy: The model achieved an accuracy of 95% with the test data, demonstrating its effectiveness in identifying the nine date fruit classes.
-
TensorFlow Neural Networks: Employs sophisticated convolutional neural networks (CNN) designed with TensorFlow to accurately classify images of different date fruits.
-
Nine Date Fruit Classes: Capable of recognizing and categorizing nine unique date fruit types, enhancing the understanding and appreciation of date fruit diversity.
-
Integration with OpenAI ChatGPT: Utilizes ChatGPT to generate intriguing and unique facts about each classified date type, enriching the user's knowledge and experience.
-
Streamlit Web Interface: Utilizes Streamlit to create an intuitive and engaging web interface, making it easy for users to interact with the model and discover information about different date fruits.
-
Clone Repo
-
Install requirements.txt
pip install -r requirements.txt- Run main.py via Streamlit
streamlit run main.pyHere are some screenshots of the app in action:
