Original subtitles

So what exactly is opens you the open sea the sense of open source computer vision and it wasn't until

initiative launched in 1989.

No the primary purpose of NCB was to consolidate a lot of the completed mission research that was being

done.

And on a lot of this research was written in C++ which is why open C-v is actually written in C++.

However there are several bindings that exist that Lois use open CVN I don't of Matlab and mobile applications

as well.

These findings are quite useful however they do tend to slow down from open civies operation.

So if you want speed use of in C++ However using it in Python allows us to do to easily grasp complex

concepts and use them by which is a powerful data orea to in bytes.

So the first major release of openside me was actually in 2006 and a second 2009 and two just last year

in 2015.

Now in this course we actually use.

I actually encourage you to use 2.4 one tree is actually very new latest release I think was just last

year.

You can check the Web sites maybe latest version by the time you this rediscuss and it's quite stable

and it's widely deployed.

I remember seeing start seeing that people still ease up to 60 percent of researchers to use open see

the 2.4 1 tree.

Now if you think you need to use open see victory point X you can go an install.

However they actually are some disadvantages to using 2.0 Plus know some important algorithms such as

sift unsafe have actually been removed.

You can actually manually add them back in.

Well it's a bit tedious and I'm not going to actually urging that during this course you output links

up.

You're free to do as you please if you to learn more about open C-v you can go to NCB that order or

check in with TPD page.

I should also say it opens in the triplane X actually has a love of the modern research built into it

as well.

And bug fixes.

However if you do want to use those maybe just stick with 2.4 tree.

So I think you're about ready to get out of the programming that opens in Python.

So let's begin.

And we'll continue this cool long session and discourse.

So we're finally here using open C.V So this ends I apply to a notebook is actually going to teach you

to read write and display images with open C-v notice what is heavily commented at least by my standards

and it is going to teach you how to do the functions I described above.

Zow to run at each block of code if you press control and so on matchbooks I believe that's command

center.

And we run it and then we go.

So yes you should see him having a second or two.

One comes up here and that means that it was run successfully so to import open C-v into on if you're

familiar with Pitre and you'd know you'd have to import a lot of different tools and libraries into

place.

So we can use less advanced functions open series called CV to me because the first version was called

CD 1.

So we imported and 72.

Secondly we don't necessarily need to import some buy into this Swiss concession here but it's also

a good habit because you never know when you actually need to use it.

Imageries we import some pie as mainly because it's needed to write using it and instead of.

We get a pretty much call this anything kind of call it X.

However the convention in them is to use the whole number.

So let's run this block of code as well.

There we go.

So now that's a lot of this image.

No you do if you have one notebook open you don't necessarily need to import CB2 again.

Well that's a good habit of Waites you know missing libraries and allows you to run lots of code independently.

So do it to get into the habit.

So no we don't use to seek CB2 that Emerita function to load images.

Now Aliff would have given you full of images that we use in this course.

So by using the argument we enter into Imry function is a part of that image or actually an image file

actually and that returns the image here.

So we're storing the first image here as input

and not in display this image.

We actually call on the CB2 in show function.

This function takes two arguments.

I've put all the notes in the comments in case you want to go over this on your own.

However I will talk to you.

So the first argument is a title that's going to be displayed on the window.

So since this is your first division up you're going to make an item that's called Say Hello World Vision

and image file that we want to open is going to be an input file that we previously loaded into here.

Now you would see it as we'd key and destroy all Windows keys.

It was not necessarily that important.

However you should always use them when you're loading images.

It he waits for you to press any key until and then it loses a window.

They destroy windows destroy all Windows function actually is very important.

Otherwise it leaves your window hanging with dysfunction.

You would wish me to crash your bike and restart it to Colonel restart here.

So let's not do that.

So let's run this code.

The real heroes are improved image.

It's a big shift that I took in Paris when I was here a couple years ago.

And there we go.

So you wouldn't your first image into open city notices a movement at all the comments.

It's much neater and of course I probably will run record looks like this something that will comment

like lower image here.

Well it's not too difficult to understand.

I hope you guys are following this as well

if there's anything that's unclear in my clueless please it be a message not get back to you as soon

as possible within 24 hours.

So now let's take a closer look at what images are stored.

So no that's important.

Yes indeed.

And using some paste sheep function using duct tape is actually very useful when you're looking at the

dimensions of injury.

You enter the door shape and it returns a tuple which gives you the dimensions of an image.

So it took away five group represented to them and listen to the X Y dimensions of the image identity

being the height 12:45 the tree being do.

RG The values of the image.

So let's take a look at looking at height and Woodson's image by actually displaying it using a print

function.

What is what we're showing here is that we can get.

We can isolate the height and widths of this tree which you would use will be useful later on.

We use it just to convert it into simple volume because otherwise it comes up with Oh yeah.

And we put pixels here.

This is just simple string concatenation very basic bytes on a loop it's not too difficult for you if

you're unfamiliar.

And that's it there.

So no let's go into saving images and open sea.

We use a CD to write function which is very similar to that as you can see the Emerita function over

just one has two arguments.

First argument is the name of the file that we're going to see if it does now.

Any time you're opening files or writing files and or conceived functions use these inverted commas

to indicate that it's a string.

Secondly this second argument here is going to be the filing of the image.

So as we previously did our image as input using every function we can then put inputs here and that

writes a file.

Now one cool thing about open CD is that it actually stores in multiple formats.

You read it multiple formats to XP and these are the most common types but believe they can be MTs and

if you add image types as well.

So we run this and this should be written to your working directory and Tom you can just take a look

in the file explorer and you'll see it here.

If it didn't run if it didn't successfully run for some reason it would be to the faults in the above

statements you I guess and that's it for your basic lesson in open see the hope you guys had fun.

We're going to move one now integrate skewing images.