Object recognition and computer vision 2021/2022

Assignment 3: Image classification

Requirements

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

2. Run the following command to install additional dependencies

pip install -r requirements.txt

Dataset

We will be using a dataset containing 200 different classes of birds adapted from the CUB-200-2011 dataset. Download the training/validation/test images from here. The test image labels are not provided.

Training and validating your model

Run the script main.py to train the model:

python main.py --data [data_dir] --model-name [model_name]

Run python main.py -h for more information, such as available model names.

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-name [model_name] --model [model_file]

That generates a file kaggle.csv that you can upload to the private kaggle competition website.

Acknowledgments

Modifications by Arthur Cahu

Adapted from Rob Fergus and Soumith Chintala https://github.com/soumith/traffic-sign-detection-homework.
Adaptation done by Gul Varol: https://github.com/gulvarol