This is a Keras implementation of a CNN for estimating age and gender from a face image . In training, the IMDB-WIKI dataset is used.

• Python 3
• Keras2.0+
• scipy, numpy, Pandas, tqdm
• OpenCV

Tested on:

• CPU ,GPU:k80 (colab)
• Python 3.6.0, Keras 2.0.2, Tensorflow 1.0.0

The dataset is downloaded and extracted to the data directory.

!wget https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/static/imdb_crop.tar

Train the network using the training data created above.

python3 plot_history.py --input models/history_16_8.h5 

The val_loss was 4.7

Here the Wide Residual Network (WideResNet) is trained from scratch. The implementation of the WideResNet; two classification layers (for age and gender estimation) are added on the top of the WideResNet.

While age and gender are independently estimated by different two CNNs ,they are simultaneously estimated using a single CNN.

Trained on imdb, tested on imdb

https://www.openu.ac.il/home/hassner/projects/cnn_agegender