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A gentle introduction to training your first emotion detection system using the PyTorch Deep Learning library
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Neuraspike/Real-time-Emotion-Detection-System
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A gentle introduction to training your first emotion detection system using the PyTorch Deep Learning library
I've used the Facial Expression Recognition 2013 (FER2013) dataset, for this example. You can download it:here
- Python version used in this project: 3.6
- matplotlib==3.3.4
- pandas==1.1.5
- scikit-learn==0.24.2
- numpy==1.17.4
- opencv-contrib-python
Otherwise, use the following command to install the packages according to the configuration file requirements.txt.
- pip install -r requirements.txt
For a more detailed explanation of the code, visit either of the following links:
MIT License
Copyright (c) 2022 Neuraspike
Permission is hereby granted, free of charge, to any person obtaining a copyof this software and associated documentation files (the "Software"), to dealin the Software without restriction, including without limitation the rightsto use, copy, modify, merge, publish, distribute, sublicense, and/or sellcopies of the Software, and to permit persons to whom the Software isfurnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THEAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHERLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THESOFTWARE.
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A gentle introduction to training your first emotion detection system using the PyTorch Deep Learning library
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