Fourth iteration of the Road To Grandmaster series. Now the task at hand is to classify images as belonging to one of two subreddits: /r/Doom and /r/AnimalCrossing. This time there's no local notebook, as I don't have a powerful GPU at my disposal. You can, however, download the data locally following the instructions below.
The strategy here was to use a pretrained CNN to differentiate between the memes from the subreddits, and Pytorch Lightning was the tool of choice to implement everything.
As this time we require some GPU setup, the easiest way to reproduce the results is accessing the Kaggle notebook here. To download the data locally, you'll need to have your Kaggle API credentials set up (you need a Kaggle account):
-
At Kaggle, go to the Account tab (top right after clicking on you profile picture)
-
Click on "Create API Token" and download the
kaggle.json
file -
Move the
kaggle.json
file to a.kaggle
folder on you home directory:Linux:
~/.kaggle/kaggle.json
Windows:
C:\Users\<Windows-username>\.kaggle\kaggle.json
Then run the get_data.py
script:
python data/get_data.py