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Pytorch implementation of DEX: Deep EXpectation of apparent age from a single image

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DEX: Deep EXpectation of apparent age from a single image

This is a pytorch version of DEX. Refer to its Home Page for more details

You can refer to insight if you want a much smaller model but it uses mxnet instead of pytorch. I haven't convert it to pytorch yet.

Getting Started

A separate Python environment is recommended.

  • Python3.5+ (Python3.5, Python3.6 are tested)
  • Pytorch == 1.0
  • opencv4 (opencv3.4.5 is tested also)
  • numpy

install dependences using pip

pip3 install numpy opencv-python
pip3 install https://download.pytorch.org/whl/cpu/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl
pip3 install torchvision (optional)

or install using conda

conda install opencv numpy
conda install pytorch-cpu torchvision-cpu -c pytorch

Usage

git clone https://github.com/siriusdemon/pytorch-DEX.git
cd pytorch-DEX
python demo.py path/to/image 

Results

predict image: imgs/2.png
woman: 0.994, man: 0.006
age: 21.433

predict image: imgs/5.png
woman: 0.010, man: 0.990
age: 42.896

Installation

You can use dex as a separate Python package right now!

cd pytorch-DEX
pip install .

See demo.py for example.

Citation

@InProceedings{Rothe-ICCVW-2015,
  author = {Rasmus Rothe and Radu Timofte and Luc Van Gool},
  title = {DEX: Deep EXpectation of apparent age from a single image},
  booktitle = {IEEE International Conference on Computer Vision Workshops (ICCVW)},
  year = {2015},
  month = {December},
}

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