So it looks like my file is completely uploaded because this number hasn't gone up in a little while.
And now you may notice a little discrepancy between what the file appears to be in size here on my local
machine seven twenty four point five and six ninety one.
Mm hmm.
But this has seven twenty four four hundred ninety five thousand nine hundred twenty six bytes which
equates to that.
So then maybe a little bit of a discrepancy in terms of how Google Drive Stores files compared to locally
and how it represents size but it looks like all of the files of uploaded which is what we're after.
So now we've got our zip file and our dog vision folder on our Google Drive.
The next step is to unzip it much like we could locally.
So if I just double click here it's going to expand dog breed ID dot zip.
So we'll have a look at what's inside
Beautiful.
So this is what we're off to try and test sample submission labels dot CSB and this is what Kaggle says
it's gonna give us if we were to download the zip labels sample submission test and train and in labels
we have ten thousand two hundred twenty two unique values.
OK.
Wonderful.
So these are the kind of things that we can test to make sure that even if we see a little discrepancy
here we can test once we've got our data in our notebook.
Hey does this line out with Kaggle.
So that's what we'll have to look at now.
So how do we unzip this in Google Drive and maybe a way we can do it from here.
Well we're going to see how to do it with code.
So let's go unzip and now remember these cells here.
Just like in Jupiter if we want to run something that's like on the command line we can use the bank
symbol here or the exclamation mark.
So this is going to go unzip and then we give it a file.
We need the file path here.
I believe he might be had to go coffeepot oh wait you can.
That's going to save us some time.
Beautiful.
We could do that or we could just type it out for practice.
So you actually don't need content little tidbit there so we can go here.
Let's see how we top it out.
Drive because we're gonna drive here.
Drive my drive.
Don't forget the space my drive.
Yours might be named a little bit different to mine but this is just what mine looks like.
Our target file is there.
So your target file be the same as mine.
My drive.
And then the project folder is dog vision.
So we need to go dog vision dog space vision and then dog breed identification dog zip.
Is that smell right.
I believe so.
And then we're going to posit the D tag the destination and then we want to put it in drive just the
exact same forward I drive my drive dog vision we just want to unzip it where it leaves I believe that
should be enough
wonderful.
Let's run this so we can shift it into what we could do that little play button.
This little play button here and now we're gonna get a big output of messages here because it has to
go through and unzip 10000 files into dog vision.
Now it may take a little while for this folder to update over here but we can be sure that it's running
by having a look at all this.
So say these are all test images.
Now again this might take a little while.
So while this code is running I'm going to stop this video here and we'll come back in the next one.
Once we've unzipped all of our data in the dog vision file and then we'll have our data ready to be
used for our project.
There we go.
We've got some updates.
So this might take a few minutes to run.
Make sure it's fully run before we go into the next segment because otherwise if it's not fully run
you'll come into the same mistake I made when trying to work with your data before it had been unzipped.
And so you end up working with less files than what Kaggle says there is and that causes whole bunches
of errors down the track.
So we'll let this run it may take a few minutes but I'll see in the next video once this is completed
and we'll go through what it's unzipped.