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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.
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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