You Only Look Twice - Foveated version
The pre-trained models used to test our method are CaffeNet, AlexNet, GoogLeNet and VGGNet (16 weight layers).
Donwload files and from root, create a build directory (mkdir build). Execute from root
bash scripts/setup.sh to directly download the pre-trained models.
To compile from root:
cd build
cmake ..
make
To run yolt.cpp from root:
bash scripts/setup.sh
First, run the setup.sh script
bash scripts/setup.sh
Second, run the detector from the root:
bash scripts/run_detector.sh
To configure your network and its parameters, change the run_detector.sh
file accordingly.
If you use our code, please cite our work:
@inproceedings{almeida2017deep,
title={Deep Networks for Human Visual Attention: A hybrid model using foveal vision},
author={Almeida, Ana Filipa and Figueiredo, Rui and Bernardino, Alexandre and Santos-Victor, Jos{\'e}},
booktitle={Iberian Robotics conference},
pages={117--128},
year={2017},
organization={Springer}
}
To test the python wrapper on an example image, change the filename='filename.jpg'
, and run the following command from the root directory:
python src/python_bindings/test.py