- After cloning the project, create a folder in this directory called data.
- Download the Fruit 360 dataset from Kaggle, unzip the files, and place them under the datadirectory.
- Install the required packages via pip (pip install -r requirements.txt). It is reccomended that you create a virtual environment for this project.
- In each experiment directory, run generate_dataset.pyto create a sampled dataset to work from.
- To train models, run the appropriate training scripts in the directory.
- To test models, edit the test script to load the desired weights then run the test script. It will print out a full classification report.
- 
                Notifications
    You must be signed in to change notification settings 
- Fork 1
TylerKirby/generative-data-augmentation
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Code for Data Mining Project on Using GANs for Dataset Augmentation
Resources
Stars
Watchers
Forks
Releases
No releases published
              Packages 0
        No packages published