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This Repo consist code for transfer learning for facial emotion detection via valence and arousal levels. We used pretrained weights from VGG-16 net and apply on that features deep neural network and lstm model in pytorch. We tested our model on Aff-wild net dataset.

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Facial-emotion-Recognition

Aff-Wild data consists of Videos. SO

framesExtraction.py will extract all frames and save location of it in csv file.

Extract features from this frames using pretrained VGG16 model it's done in save_features_vgg16.py. Features are saved in data/bottleneck_

Then train this features usinf lstm and neural network mode in train.py

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This Repo consist code for transfer learning for facial emotion detection via valence and arousal levels. We used pretrained weights from VGG-16 net and apply on that features deep neural network and lstm model in pytorch. We tested our model on Aff-wild net dataset.

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machine-learning pytorch artificial-intelligence lstm-model transfer-learning vgg16 harr-cascade facial-emotion-recognition valence-arousal aff-wild

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