/human_gender_prediction

A project of my AI class at Chonnam National University

Primary LanguageJupyter Notebook

TensorFlow 1.1.0 Python 3.5 Jupyter Notebook

Windows x64 cuDNN v5 CUDA 8.0

Human Gender Prediction

Chonnam National University
2017 AI Class
Professor Lee Chilwoo
Student: Nguyen Hai Duong
Target: predict human gender using Convolutional Neural Network

Gender prediction examples

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Confusion matrix on Wiki testing set

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How to run source code

For a complete training (at least 8GB memory is required)

  1. Download the Jupyter notebook gender_prediction.ipynb and save it to a specific path (called GD_PATH)
  2. In GD_PATH, create folder gender/wiki_crop
  3. Download the processed WIKI dataset [1] and save them to GD_PATH/gender/wiki_crop
  4. Download additional testing images and store them in GD_PATH
  5. Open gender_prediction.ipynb with Jupyter and run all cells

For testing using trained model

  1. Download the Jupyter notebook gender_prediction_testing.ipynb and save it to a specific path (called GD_PATH)
  2. Download trained model on WIKI dataset [1] and save it to GD_PATH
  3. In GD_PATH, create folder gender/wiki_crop
  4. Download WIKI testingset [1] including 64_64_11938_4098_testing_x_onehot.npy, and 64_64_11938_4098_testing_y_onehot.npy and store them in GD_PATH/gender/wiki_crop
  5. Download additional testing images and store them in GD_PATH
  6. Open gender_prediction_testing.ipynb with Jupyter and run all cells

References

[1] Rasmus Rothe, Radu Timofte, and Luc Van Gool, "Deep expectation of real and apparent age from a single image without facial landmarks," International Journal of Computer Vision (2016)

Personal information

Nguyen Hai Duong
Supervisor: Professor Kim Soo-Hyung
Pattern Recognition Lab
Chonnam National University, Korea
E-mail: nhduong_3010@live.com