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Gender classification (from scratch) using deep learning with Keras

The keras model is created by training SmallerVGGNet from scratch on around 2200 images (~1100 for each class) gathered from Google Images. It acheived around 95% training accuracy and ~85% validation accuracy. (20% of the dataset is used for validation)

Python packages

  • numpy
  • opencv-python
  • tensorflow
  • keras

Install the required packages by executing the following command.

$ pip install -r requirements.txt

Sample output

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