资源算法traffic-sign-detection-homework

traffic-sign-detection-homework

2019-10-12 | |  234 |   0 |   0

NYU-CV-Fall-2018

Assignment 2: Traffic sign competition

Requirements

  1. Install PyTorch from http://pytorch.org

  2. Run the following command to install additional dependencies

pip install -r requirements.txt

Training and validating your model

Run the script main.py to train your model.

Modify main.pymodel.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.

Evaluating your model on the test set

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.


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