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
pip3 install py-agender[cpu] # for the cpu version of TensorFlow
pip3 install py-agender[gpu] # for the gpu version of TensorFlow
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 sourceDon't forget to download pretrained weights if using source code DIY style.
- add options (like STDIN input, output formatters etc.) for useful commandline applications
- add help output
- train better network with higher image resolution
- train another (more compact & precise) network architecture
python3 -m unittest
- Python 3.5, 3.6, 3.7
- numpy ~> 1.15
- Keras ~> 2.2
- tensorflow or tensorflow-gpu ~> 1.10
- opencv-python ~> 3.4.2+contrib
Tested on:
- MacOS 10.13 high Sierra without GPU (you're welcome to update & contribute!)
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
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.