English to Darija Translator using a sequence-to-sequence model built with Python and Natural Language Processing (NLP). Break language barriers effortlessly.
# Morrolingo
Welcome to the English to Darija Translator project! This web application utilizes a sequence-to-sequence model and NLP techniques to translate English text into Darija, Moroccan dielect. Below, you'll find an overview of the project, its features, and instructions to get started.
## Project Structure
- `model.py`: Source code for the sequence-to-sequence model used in translation.
- `templates/`: Contains the HTML templates for the web interface.
- `index.html`: Landing page of the web application.
- `interface.html`: Translation interface in action.
- `front.py`: Flask framework code that connects the frontend and backend.
- `static/`: Contains static assets like CSS files and images.
- `css/`: CSS files for styling the web pages.
- `images/`: Images used in the application.
- `test.txt`: The dataset used for training and testing.
## Steps to build :
by following this tutorial "
pytorch.org "
as a teamwork we were able to build this amazing friendly web app :
1.Prepare Resources:
-Install Python and required libraries like TensorFlow or PyTorch for the model.
-Collect a dataset with English-Darija sentence pairs.
2.Preprocess Data:
-Clean and format the dataset.
-Tokenize sentences into words or subword units.
3.Build Model:
-Create an encoder-decoder architecture.
-Use embeddings to convert words into vector representations.
4.Train Model:
-Split data into training and validation sets.
-Train the model using training data and monitor performance using validation data.
5.Develop Web App:
-Set up a Flask web app framework.
-Design a user interface for input and display of translations (html ,css and js)
## Getting Started
1. Clone the repository: "git clone
github.com"
2. cd english-to-darija-translator
3. pip install -r requirements.txt
4. Run the Flask app: python front.py
5. Access the translator in your web browser by visiting …