https://github.com/onurmx/emotion-recognition
Emotion recognition from facial images using convolutional neural networks.
https://github.com/onurmx/emotion-recognition
ckplus computer-vision convolutional-neural-networks deep-learning deep-neural-networks emotion-recognition fer2013-dataset image-augmentation image-classification image-processing image-recognition kdef-dataset machine-learning pyside pytorch resnet tensorflow torch torchvision vgg
Last synced: 7 months ago
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Emotion recognition from facial images using convolutional neural networks.
- Host: GitHub
- URL: https://github.com/onurmx/emotion-recognition
- Owner: onurmx
- License: mit
- Created: 2022-06-16T06:50:00.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-11-18T09:01:39.000Z (almost 2 years ago)
- Last Synced: 2025-01-18T12:35:24.724Z (9 months ago)
- Topics: ckplus, computer-vision, convolutional-neural-networks, deep-learning, deep-neural-networks, emotion-recognition, fer2013-dataset, image-augmentation, image-classification, image-processing, image-recognition, kdef-dataset, machine-learning, pyside, pytorch, resnet, tensorflow, torch, torchvision, vgg
- Language: Python
- Homepage:
- Size: 96.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# emotion-recognition
Emotion recognition from facial images using convolutional neural networks.
## Classifiers
Resnet, VGG-16, and Onsunet convolutional neural network architectures are used.
## Libraries
PyTorch, TensorFlow libraries are used to implement convolutional neural networks. Each architecture has two variants for each libary.
PySide is used to provide graphical user interface to application.
## Datasets
FER2013, KDEF, and CK+ datasets are used to train classifier. Each dataset is processed in both PyTorch and TensorFlow libraries.
## Execution of the application
To execute the application, it is enough to run main.py file.
```
python main.py
```