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Segmentation guided attention

Pytorch implementation for the paper: Reconciling explainability and performance in neural networks by means of semantic segmentation-guided feature attention:An application to urban space perception (unpublished).

Requirements

Python >= 3.6.5 (only tested on that one)

For more check requirements.txt

Setup and preprocessing

First install dependencies

pip install -r requirements.txt

Get the dataset and put all the images in a single placepulse/ folder in the root directory. Also put the complete votes.csv file in the root directory. After that run the preprocessing scripts.

python image_crop.py
python place_pulse_clean.py
python placepulse_split.py

Training

Now you can start training:

python train.py

For information on the different parameters run:

python train.py -h

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Reconciling explainability and performance in neural networks by means of semantic segmentation-guided feature attention:An application to urban space perception

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