Cinemoods 🎥🍿

Project Goal 🎯

The goal of this project is to create a personalized movie recommendation app that leverages emotion recognition to suggest films based on the user's current emotional state. By analyzing movie descriptions using the BERT-based emotion recognition model, the app aims to enhance the Netflix viewing experience by offering tailored recommendations that resonate with users' feelings.

Features ✨

• Emotion-Based Recommendations 🎭: Suggests movies that resonate with the user's current emotional state, such as joy, sadness, or fear.

• Data Cleaning & Preprocessing 🧹: Ensures movie descriptions are clean and ready for analysis by removing special characters and stopwords.

• Advanced Emotion Recognition 🤖: Utilizes the BERT model for accurate emotion predictions based on movie descriptions.

• User-Friendly Interface 💻: Provides an interactive and easy-to-navigate web interface for seamless user experience.

• Diverse Movie Selection 🎬: Offers a wide range of movie recommendations tailored to various emotions, enhancing viewing options.

• Easy Integration with Netflix 📺: Designed to work with Netflix titles, making it convenient for users to find suitable movies on the platform.

Project Structure 📁

├── Cinemoods
|   ├── Code/
|   ├── UI/                                  
│   ├── app.py                                   # Streamlit UI application
|   ├── model_pkl.py                             # Emotion prediction model
|   ├── model.ipynb 
│   ├── Datasets/
│   │   ├── netflix_titles.csv                   # Original dataset
│   │   ├── netflix_cd.csv                       # Cleaned dataset
│   │   └── netflix_titles_with_predictions.csv  # Dataset with predicted emotions                            
│   └── requirements.txt                         # Required packages for the project
├── LICENSE                                      # Licensing information
└── README.md                                    # Project documentation and instructions

Video Output 🎥

Watch the project demo here:

demo.mp4

Requirements 📦

To run this project, ensure you have the following dependencies installed:

• pandas==1.5.3
• nltk==3.6.3
• torch==1.13.1
• transformers==4.30.0
• huggingface-hub==0.16.4
• streamlit==1.21.0
• matplotlib==3.6.2

You can install the required packages using pip:

pip install -r requirements.txt

Usage 🚀

Clone the repository:

git clone https://github.com/yourusername/SwiftServe.git

Navigate to the project directory:

cd Cinemoods

Install the required packages:

pip install -r requirements.txt

Prepare the dataset:

# Dataset containing Netflix titles and descriptions
titles_file = "netflix_titles.csv"

# Cleaned dataset with descriptions
cleaned_titles_file = "netflix_cd.csv"

# Dataset with predicted emotions
predicted_emotions_file = "netflix_titles_with_predictions.csv"

Run the Streamlit app:

streamlit run app.py