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BananaAnalysisApp

Flask-based web application designed for the analysis of bunches of bananas using deep learning and convolutional neural networks
Updated 5 months ago

BananaAnalysisApp

Introduction

This repository contains a Flask-based web application designed for the analysis of bananas using deep learning and convolutional neural networks. The app utilizes a TensorFlow Lite model to perform image processing and classification to determine the quality of bananas for potential export or rejection.

Features

  • Image upload and processing using Flask.
  • Banana detection and cropping algorithm.
  • Resizing images maintaining aspect ratio.
  • Deep learning model inference for banana classification.

Installation

To run the application locally, follow these steps:

  1. Clone the repository to your local machine.
  2. Install the required dependencies using pip install -r requirements.txt.
  3. Run the app with python app.py.

Usage

Once the application is running, navigate to localhost:5000 in your web browser. Upload an image of a banana, and the application will classify it as either suitable for export or as a reject.

Model

The deep learning model used in this application is a TensorFlow Lite model. It is not included in the repository and should be added with the name model.tflite in the root directory.

Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request with your proposed changes.

License

This project is open source and available under the MIT License.