B-IT-BOTS robotics team.
Face classification and detection from theReal-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.
- IMDB gender classification test accuracy: 96%.
- fer2013 emotion classification test accuracy: 66%.
For more information please consult the technical report
Real-time demo:
B-IT-BOTS robotics team :)
Instructions
To train previous/new models for emotion classification:
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Download the fer2013.tar.gz file from here
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Move the downloaded file to the datasets directory inside this repository.
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Untar the file:
tar -xzf fer2013.tar
- Run the train_emotion_classification.py file
python3 train_emotion_classifier.py
To train previous/new models for gender classification:
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Download the imdb_crop.tar file from here (It's the 7GB button with the tittle Download faces only).
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Move the downloaded file to the datasets directory inside this repository.
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Untar the file:
tar -xfv imdb_crop.tar
- Run the train_emotion_classification.py file
python3 train_emotion_classifier.py
Run real-time emotion demo:
python3 video_emotion_color_demo.py
Run real-time guided back-prop demo:
python3 image_gradcam_demo.py
Make inference on single images:
python3 image_emotion_gender_demo.py <image_path>
e.g.
python3 image_emotion_gender_demo.py ../images/test_image.jpg