https://github.com/rajkhanke/facial-expression-detection-using-machine-learning
The System detects the facial emotion among the seven (happy, sad, angry ,surprise, fear, neutral, disgust) using the convolutional neural network (CNN) Architecture
https://github.com/rajkhanke/facial-expression-detection-using-machine-learning
cnn deep-learning machine-learning opencv
Last synced: about 2 months ago
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The System detects the facial emotion among the seven (happy, sad, angry ,surprise, fear, neutral, disgust) using the convolutional neural network (CNN) Architecture
- Host: GitHub
- URL: https://github.com/rajkhanke/facial-expression-detection-using-machine-learning
- Owner: RajKhanke
- Created: 2024-04-28T20:13:40.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-28T20:22:40.000Z (about 2 years ago)
- Last Synced: 2024-04-28T21:29:47.539Z (about 2 years ago)
- Topics: cnn, deep-learning, machine-learning, opencv
- Language: Jupyter Notebook
- Homepage:
- Size: 14.1 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# facial-expression-detection-using-Machine-Learning
The System detects the facial emotion among the seven different types of emotions using the convolutional neural network (CNN) Architecture at the accuracy rate of 60 % and a loss of less than 0.20.
The seven types of expressions are :
Angry
sad
fear
neutral
surprise
disgust
Happy
The model is trained and tested over fer_2013 image dataset available on kaggle, with the total epoche count of 50.
The model is connected with the web0cam using OpenCV.
To clone the repository in your system use :
git clone https://github.com/RajKhanke/facial-expression-detection-using-Machine-Learning.git
dataset link : https://www.kaggle.com/datasets/msambare/fer2013