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Install PyTorch from http://pytorch.org
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Run the following command to install additional dependencies
pip install -r requirements.txt
Run the script main.py
to train your model.
Modify main.py
, model.py
and data.py
for your assignment, with an aim to make the validation score better.
- By default the images are loaded and resized to 32x32 pixels and normalized to zero-mean and standard deviation of 1. See data.py for the
data_transforms
. - By default a validation set is split for you from the training set and put in
[datadir]/val_images
. See data.py on how this is done.
As the model trains, model checkpoints are saved to files such as model_x.pth
to the current working directory.
You can take one of the checkpoints and run:
python evaluate.py --data [data_dir] --model [model_file]
That generates a file gtsrb_kaggle.csv
that you can upload to the private kaggle competition https://www.kaggle.com/c/nyu-cv-fall-2018/ to get onto the leaderboard.