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CS 7641 - Machine Learning Course Project on Image Classification on CIFAR-10 using supervised and semi-supervised learning techniques

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Image classification using supervised and unsupervised methods

Description

The method description and the results are provided here.

Setup

1.Create a conda environment using requirements.txt using the command provided below.

conda create --name img-classifcation --file requirements.txt

2.requirements.txt already contains Pytorch 1.3 which is supposed to run on a GPU. If you plan to run this code on CPU, install Pytorch using this command. Make sure to be inside the conda environment img-classification while installing it.

```conda install pytorch torchvision cpuonly -c pytorch```

How to run a model?

After the requirements are installed, open a terminal to run the model as -

bash scripts/run_<model_name>.sh

Contributing

Write your model architecture inside models folder. models.softmax.py has been provided for reference.

Scripts inside scripts can be used to train the models. scripts/run_softmax.sh has been provided for reference.

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CS 7641 - Machine Learning Course Project on Image Classification on CIFAR-10 using supervised and semi-supervised learning techniques

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