Zeshaninsta/Oromo-Dataset-Collection

A web application for collecting and managing an Afaan Oromoo dataset, featuring real-time data updates, a user-friendly interface for submitting sentences, and a downloadable CSV file. Built with React for the frontend and Flask for the backend. # Oromo Dataset Collection A web application designed to collect and manage a dataset for the Afaan Oromoo language. This project enables users to submit incorrect and corrected sentences in Afaan Oromoo, which are stored in a CSV file. The application provides real-time updates on the number of entries in the dataset and allows users to download the dataset. ## Features - **Data Collection:** Users can submit incorrect and corrected sentences in Afaan Oromoo. - **Real-time Dataset Count:** The number of entries in the dataset is displayed and updated in real-time. - **Downloadable Dataset:** The collected data can be downloaded as a CSV file. - **Cultural Design:** The UI reflects Oromo culture, providing a more engaging user experience. ## Technologies Used - **Frontend:** React, Tailwind CSS - **Backend:** Flask, Python - **Data Storage:** CSV file ## Getting Started ### Prerequisites - Node.js and npm installed - Python and pip installed ### Installation 1. **Clone the repository:** ```bash git clone github.com cd Oromo-Dataset-Collection ``` 2. **Install frontend dependencies:** ```bash cd frontend npm install ``` 3. **Install backend dependencies:** ```bash cd ../backend pip install -r requirements.txt ``` ## Running the Application 1. **Start the Flask backend:** ```bash cd backend flask run ``` 2. **Start the React frontend:** ```bash cd ../frontend npm run dev ``` 3. **Open the application:** ```bash Go to localhost in your web browser. ``` ## API Endpoints ```bash - GET /api/dataset-count: Returns the current count of entries in the dataset. - POST /api/add-data: Adds a new entry to the dataset. - GET /api/download-dataset: Downloads the dataset as a CSV file. ``` ## Project Structure ```bash Oromo-Dataset-Collection/ ├── backend/ # Flask backend │ ├── app.py # Main Flask application │ └── dataset/ # Directory for storing the dataset ├── f …