GenderClassifierApp is a web application designed to predict gender based on facial features. It utilizes machine learning algorithms to analyze input data and provide predictions on whether the input corresponds to a man or a woman.
- User-Friendly Interface: Simple and intuitive web interface for inputting facial feature data.
- Prediction Engine: Uses a trained machine learning model to predict gender based on input parameters.
- Interactive Feedback: Instantaneous feedback on predictions displayed on the web interface.
- Scalable: Designed to handle multiple users simultaneously, ensuring robust performance.
- Song: "Facts"
- Artist: Tom MacDonald (feat. Ben Shapiro)
- YouTube Link: Facts - Tom MacDonald (feat. Ben Shapiro)
- Input: Users provide facial feature data such as forehead width, nose characteristics, and other relevant attributes via a user-friendly form.
- Processing: The input data is processed by a pre-trained Random Forest model, which has been trained to classify gender based on these features.
- Output: The application outputs a prediction indicating whether the input data corresponds to a man or a woman.
- Python: Backend logic and machine learning model training.
- Flask: Web framework for handling HTTP requests and responses.
- HTML/CSS: Frontend design and user interface.
- JavaScript: Enhances interactivity and form handling on the client-side.
- Scikit-learn: Used for data preprocessing and machine learning model implementation.
git clone <repository_url>pip install -r requirements.txtpython app.py
Access the web application through the provided URL and interact with the prediction form.