load image dataset (folder or zip) located in Google Drive to Google Colab?

Question

I have a dataset of images on my Google Drive. I have this dataset both in a compressed .zip version and an uncompressed folder.

I want to train a CNN using Google Colab. How can I tell Colab where the images in my Google Drive are?

1. official tutorial does not help me as it only shows how to upload single files, not a folder with 10000 images as in my case.

2. Then I found this answer, but the solution is not finished, or at least I did not understand how to go on from unzipping. Unfortunately I am unable to comment this answer as I don't have enough "stackoverflow points"

3. I also found this thread, but here all the answer use other tools, such as Github or dropbox

I hope someone could explain me what I need to do or tell me where to find help.

Edit1:

I have found yet another thread asking the same question as mine: Sadly, of the 3 answers, two refer to Kaggle, which I don't know and don't use. The third answer provides two links. The first link refers to the 3rd thread I linked, and the second link only explains how to upload single files manually.

Answer 1

I saw and tried all the above but it didn't work for me. So here is a simple solution with simple explanation that can help you load a .zip image folder and extract images from it.

• Connect to google drive

  from google.colab import drive
  drive.mount('/content/drive')
  

(you will get a link sign in to your google account and copy the code and paste onto the code asked in the colab)

• Install and import keras library

  !pip install -q keras
  import keras
  
  

(the zip file is loaded into the colab)

• Unzip the folder

  ! unzip 'zip-file-path'
  

To get the path:

• select file on left side of google colab
• browse for the file click on the 3 dots
• copy path

Now the unzipped image folder is loaded onto your colab use it as you wish