Age, gender, emotion estimation

Demo

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