I take a lot of photos with my phone. About every month I  back them up to my computer and sort them into folders. Even though the  photos most contain my pets, I have other photos like of my motorcycle,  receipts, funny Reddit posts and funny conversations. Here's an example  folder layout:

  • Pictures
  • Jane
  • Ginger
  • Stanley
  • Huginn
  • Cat Combo
  • LG G6
  • Reddit
  • Conversation

I can use machine learning to sort through these photos and organize  them a heck of a lot quicker. Right now, the machine learning is using  AWS' database. This means that it may not label my photos correctly. For  example, one photo of the dog on a floral bed labeled the photo as  "floral" rather than "dog." I'd like to implement a cross-check with  Google Vision.

From this small weekend project, I learned more about Python,  functions, argument parameters, for loops, closing files properly, and  closing GitHub issues.

Eventually, I will figure out Tensorflow and manually train a model to sort for me. But this is a great first step for me.

Check out the GitHub repo here: