Commit 7ff2e846 authored by Aditya Hiteshbhai's avatar Aditya Hiteshbhai

fix: edited README.md and created requirements.txt

parent a874f674
Pipeline #1888 canceled with stages
# cs725-project # CS-725 Project
## Overview
The EmoMusic Recommender is an innovative application that combines text and facial emotion analysis to suggest personalized music recommendations.
## Team Members
- **Udhay Brahmi**
- Responsibilities: Implementing CNN model
- GitHub: [GitHub Profile](https://github.com/udhaybrahmi)
- **Jay Gorakhiya**
- Responsibilities: Implementing Text-Based model and Database
- GitHub: [GitHub Profile](https://github.com/jaygorakhiya)
- **Utsav Manani**
- Responsibilities: Streamlit Design and Implementation, GitHub
- GitHub: [GitHub Profile](https://github.com/utsavmanani)
- **Vinit Patel**
- Responsibilities: Streamlit Implementation and Presentation
- GitHub: [GitHub Profile](https://github.com/vinitpatel-007)
- **Aditya Kansara**
- Responsibilities: UI and Model integration with Database
- GitHub: [GitHub Profile](https://github.com/adityakansara)
## Work Split
Briefly outline the distribution of tasks among team members.
- **Udhay Brahmi**
- Completed implementation of the CNN model.
- **Jay Gorakhiya**
- Implemented the Text-Based model.
- Set up and managed the database.
- **Utsav Manani**
- Designed and implemented the Streamlit interface.
- Contributed to GitHub repository management.
- **Vinit Patel**
- Implemented Streamlit features.
- Prepared and delivered project presentations.
- **Aditya Kansara**
- Integrated UI with the model.
- Ensured smooth integration with the database.
## Instructions for Running the Project
1. **Install Dependencies:**
- Open a terminal and navigate to the project directory.
- Run the following command to install the required dependencies:
```bash
pip install -r requirements.txt
```
2. **Run the Streamlit App:**
- After installing the dependencies, run the Streamlit app using the following command:
```bash
streamlit run app.py
```
3. **Text and Face Emotion Detection:**
- Once the app is running, open the provided URL in your web browser.
- Enter text in the designated input field and press the "Submit" button.
- The app will scan the user's face and detect emotions based on both text and facial expressions.
4. **Music Suggestion:**
- After emotion detection, the app will suggest music based on the detected emotion.
**Note:** Make sure to have a webcam connected for face detection.
opencv-python==4.8.1.78
pandas==2.1.3
numpy==1.26.2
streamlit==1.28.2
sqlite==3.35.2
textblob==0.70.1
tensorflow==2.14.0
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