This is a project which explores Human Emotion Detection. There are seven human emotions talked about in this project: angry, disgust, sad, happy, fear, surprised and a poker face.
It uses the neural network whihc is defined by keras and works on that. We will also be using the CascadeClassifier for object detection during the video testing from the live feeds.
The ipynb file is used to generate a model. And the model can be imported as shown in videotester.py file. Happy Coding!
Following is the link to the dataset:https://www.dropbox.com/s/w3zlhing4dkgeyb/train.zip?dl=0
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This project uses both machine learning as well as image processing to perform the task of detecting human emotions. We have defined seven emotions and we use the keras.models for importing out model which has seven dense layers. Better models can be used in future projects
anirudhrealdeal/HumanEmotion1
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This project uses both machine learning as well as image processing to perform the task of detecting human emotions. We have defined seven emotions and we use the keras.models for importing out model which has seven dense layers. Better models can be used in future projects
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