The Fruit Identification and Calorie Estimation System is a mobile application designed to help users identify fruits and estimate their caloric content using image analysis. Leveraging advanced machine learning technologies like Convolutional Neural Networks (CNN) and cloud-based infrastructure, this app offers a seamless and accurate way to track dietary information and promote healthier eating habits.
- Fruit Recognition: Identify a wide variety of fruits through the camera or image upload.
- Caloric Estimation: Estimate caloric content based on the type and quantity of the fruit.
- Cloud Integration: Efficiently process and store data using Google Cloud Platform (GCP).
- User-Friendly Interface: Simple and intuitive app design for ease of use.
- Mobile Accessibility: Native Android app built with Kotlin.
- Image Input: Users upload an image of a fruit or take a photo directly within the app.
- Fruit Recognition: The app utilizes a CNN model to classify the fruit based on features like shape, color, and texture.
- Calorie Estimation: The app retrieves the caloric value of the identified fruit using preloaded nutritional data.
- Results Display: Nutritional information, including calories, is displayed to the user.
- Tools/IDEs: Google Colab, Jupyter Notebook
- Libraries: TensorFlow, Keras, OpenCV, NumPy, Pandas, Matplotlib
- Frameworks: Convolutional Neural Networks (CNN)
- Platform: Google Cloud Platform (GCP)
- Technologies: Firebase, Cloud Functions, Google Cloud Storage
- Tools/IDEs: Android Studio, Figma
- Libraries: Retrofit
- Languages: Kotlin
