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This project uses OpenCV and a Convolutional Neural Network (CNN) model to classify the emotion on a person's face into one of seven categories: angry, disgusted, fearful, happy, neutral, sad, and surprised. The model is trained on the FER-2013 dataset, which consists of 35887 grayscale, 48x48 sized face images with seven emotions.

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JAYANTH5775/Emotion_detection

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https://www.kaggle.com/datasets/msambare/fer2013 - > DATA SET LINK 

creating the virtual environment to the   install the libraies in the venv 

To create a virtual environment in Windows 11, follow these steps:

- Open a Command Prompt terminal by searching for "command prompt" in the Windows search bar or pressing the Windows Key + R, and then enter cmd.
- Navigate to your project directory using the cd command.
Create the virtual environment in a desired directory using the following command:
python -m venv env
- This will create a new folder called env inside the directory where you executed the command.

- Activate the created virtual environment by running the following command in the same directory where you executed the last command:
cd env/Scripts && activate && cd ../../




pip install -r requirements.txt -> comment to install the required libraries

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This project uses OpenCV and a Convolutional Neural Network (CNN) model to classify the emotion on a person's face into one of seven categories: angry, disgusted, fearful, happy, neutral, sad, and surprised. The model is trained on the FER-2013 dataset, which consists of 35887 grayscale, 48x48 sized face images with seven emotions.

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