Pet Emotion Recognition

Pet Emotion Recognition is a Flask-based web application used to identify emotions from facial expressions of pets. This system is well-equipped to identify general emotions like angry, happy, sad, and relaxed. At its core, it uses the powerful transfer learning-based MobileNetV2 architecture to identify emotions from provided image. This project has achieved a reliable validation accuracy of 92.06%.

Screenshots:

Home Page	Result page

How to Run:

1. Clone the repository

   git clone https://github.com/your-username/pet-emotion-recognition.git
   cd pet-emotion-recognition

2. Create a virtual environment

   python -m venv venv

3. Install the required packages

   pip install -r requirements.txt

4. Run the Flask application

   run app.py

5. Open your browser and go to

   http://127.0.0.1:5000
   

Tech Stack:

• Frontend: HTML, CSS, Bootstrap
• Backend: Flask
• Machine Learning: TensorFlow, Keras, Scikit-learn
• Model: MobileNetV2
• Data Manipulation: NumPy, pandas, Matplotlib

Dataset:

The Dataset used in this project can be acquired from - Kaggle.

License:

This project is licensed under the MIT License. See the LICENSE file for more details.