landmark_classification-and-tagging-for-social_meida

Table of Contents

• Project Overview
• Directory Structure
• Installation
• Usage
• Transfer Learning
• CNN Model
• Voila App
• Contributing
• License

Project Overview

This project involves the use of transfer learning and convolutional neural networks (CNNs) to create and deploy AI models. A Voila-based web app is also provided to interact with these models.

Directory Structure

• checkpoints/: Directory containing model checkpoint files.
• src/: Source code directory.
  • data.py: Data loading and preprocessing functions.
  • transfer.py: Transfer learning functions.
  • cnn.py: CNN model architecture.
  • optimization.py: Optimization and loss functions.
  • train.py: Training functions.
• app.ipynb: Voila app notebook.
• transfer_learning.ipynb: Notebook for transfer learning.
• cnn_model.ipynb: Notebook for CNN model training.
• README.md: This README file.
• requirements.txt: Python dependencies.

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/your-repo-name.git
   cd your-repo-name

2. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

Usage

Transfer Learning

1. Open the transfer_learning.ipynb notebook.
2. Follow the steps to load and train the transfer learning model.
3. Save the trained model checkpoint in the checkpoints directory.

CNN Model

1. Open the cnn_model.ipynb notebook.
2. Follow the steps to define, train, and evaluate the CNN model.
3. Save the trained model checkpoint in the checkpoints directory.

Voila App

1. Open the app.ipynb notebook.

2. Follow the steps to set up the Voila app interface.

3. Run the following command to launch the app:

   voila app.ipynb --show_tracebacks=True

4. Interact with the app in your web browser.

   

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for details.