So in the last section, you've made your API.
No, that's true, that API into an actual full webpage that someone or anyone in the world with internet
access can use.
So let's open the book 75 and let's see how we do that.
So let's begin here.
We're opening that notebook.
So let's plug in my repo here.
Install flask and grub install.
Navigate to the directory.
Download the file and install it.
Next, we have my what could there that is, Steve, that he did in the previous lesson.
So now let's take a look at this file so you can see it looks quite simple.
This is all the code there is.
So what is this doing?
So basically, we have in the GetUp report clue and we have the files that do the common functions here
that do to do computer vision parts that you can take a look at these if you want.
It's basically this one that gets to model, transforms the image and then formats the class name as
well so that it returns it to the user.
And we also have the inference function here, which is what I was looking for.
This is one that takes to gets a prediction out of it from the transform and get model classes sort
of functions.
So basically this we have all the functions that we need here.
We have flash, we have in grok, we have post requests and also can get requested.
But let's look at the post requests here.
So it actually loads a little website and that website here is index HTML so indexed.
Each HTML is live in Templates directory and that basically consists of the HTML site.
We can take a look at that here.
This is the HTML of the webpage that we'll be deploying to the web.
Once we start this app up, so enough talk.
Let's see this and maybe can help you.
This can help you understand better what we're doing.
So let's click this link here and you're going to get or I didn't get to Google warning me because I
opened it up before.
So now we can upload an image here, so let's take a look.
The screenshots?
Let's go to my downloads, which is quite messy right now.
What would be a good image to use?
Actually can try a random QR code.
Let's see what happens.
This was a QR code I was doing some test with and it says Packet.
So not that cool.
Let's try something else.
So, OK, so let's try this very nice split of a bowl of ramen soup.
Let's see what our classifier thinks.
It is remote.
It is trained on image that.
So let's see, it sets pot pot pipe.
It's kind of cool.
Let's try.
Another image from my satellite was Try this chihuahua.
Well, let's see what happens.
Jhalawar.
So we've got it right.
So you can see our little web up here is working quite well.
Let's try some fireworks.
Yeah, let's see if it has fireworks.
As a class surgeon, it did not have fireworks in the class, so I'm guessing maybe fireworks can look
like a sea and perhaps actually can.
It's kind of cool that it could, actually.
Let's take a look at this dog here.
Rottweiler, if he gets that one.
And you can see it's working quite well.
So that's it for this section here.
Hope you enjoyed it.
And Gronk and Flask make it very easy to test these web apps in the cloud so you can experiment here
where you can experiment on your local machine.
Would running this on your local machine?
You don't need an grok anymore, but however you do if you want to actually host it and a web if you
don't, you can just access it to your local host address here, and it's going to be something similar
to this as well.
So thank you for watching, and we'll stop there for now, and I'll see you in the next section.
Thank you.