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Age, gender, emotion estimation

Demo

demo_dinner demo_obama

  • Instructions for demo
    python3 demo.py input_video_path="input/dinner.mp4" \

Train

  • Prepare dataset
    • For age and gender: IMDB + WiKi[6]
    • For emotion: FER-2013[7]
  • Instructions for train
    • If train with backone 'ShuffleNet V2', using train_shufflenet.py
    • If train with backone 'WideResNet', using train.py
    • imdb_db.mat, wiki_db.mat: please refer to [2] to run "create_db.py"
    • fer2013.csv": download from Kaggle
    python3 train_shufflenet.py
    --input_agender
    data/imdb_db.mat
    --input_wiki
    data/wiki_db.mat
    --input_emotion
    data/fer2013.csv
    --nb_epochs
    30
    --staircase_decay_at_epochs
    (5,8,)
    --lr
    0.1
    --validation_split
    0.15
    --batch_size
    64
    

References

[1] R. Rothe, R. Timofte, and L. V. Gool, "DEX: Deep EXpectation of apparent age from a single image," in Proc. of ICCV, 2015.
[2] yu4u/age-gender-estimation
[3] opconty/keras-shufflenetV2
[4] lmeulen/AgeGenderEmotion
[5] oarriaga/face_classification
[6] IMDB-WIKI – 500k+ face images with age and gender labels
[7] Challenges in Representation Learning: Facial Expression Recognition Challenge

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Age, gender, emotion estimation for facial recognition

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