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Simple opencv & tensorflow based solution to estimate Faces, Age and Gender on pictures

Project description

Face Age & Gender detection tool

Simple opencv & tensorflow solution to estimate Age and Gender in your next project. Command line or Python DIY style.

Based on and forked from: https://github.com/yu4u/age-gender-estimation

Good enough for pet-projects and prototypes, but not ready for production real-life applications

How

pip3 install py-agender

Warning: ~190MB download (pretrained network is heavy).

CLI:

py-agender PATH_TO_IMAGE

Python:

from pyagender import PyAgender

agender = PyAgender() 
# see available options in __init__() src

faces = agender.detect_genders_ages(cv2.imread(MY_IMAGE))
# [
#   {left: 34, top: 11, right: 122, bottom: 232, width:(r-l), height: (b-t), gender: 0.67, age: 23.5},
#   ...
# ]

# Additional options & methods in PyAgender source

Don't forget to download pretrained weights if using source code DIY style.

TODO:

  • add options (like STDIN input, output formatters etc.) for useful commandline applications
  • add help output
  • train better network with higher image resolution

Tests

python3 -m unittest 

Dependencies

  • Python 3.5, 3.6
  • numpy ~> 1.15
  • Keras ~> 2.2
  • TensorFlow ~> 1.9
  • opencv-python ~> 3.4.2+contrib

Tested on:

  • MacOS 10.13 high Sierra without GPU (you're welcome to update & contribute!)

Model

These weigts are from https://github.com/yu4u/age-gender-estimation on first console version run they are cached in ./pyagender.pretrained_models folder:

https://github.com/yu4u/age-gender-estimation/releases/download/v0.5/weights.28-3.73.hdf5

License

This project is released under the MIT license.

However, the IMDB-Wiki dataset used for pretrained network above is originally provided under the following conditions:

Please notice that this dataset is made available for academic research purpose only. All the images are collected from the Internet, and the copyright belongs to the original owners. If any of the images belongs to you and you would like it removed, please kindly inform us, we will remove it from our dataset immediately.

Refer to fresh IMDB-Wiki dataset License and act accordingly.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
py_agender-0.0.8-py3-none-any.whl (188.3 MB) Copy SHA256 hash SHA256 Wheel py3
py-agender-0.0.8.tar.gz (188.3 MB) Copy SHA256 hash SHA256 Source None

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