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OK.

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So in twenty one point one we deal with a t i install and setup.

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So let's talk a bit about tensor flows object action.

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The TFT API is one of the more mature and relatively easy to use object action frameworks.

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Most of them are actually quite finicky and tricky to use.

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Typically most other obligation frameworks are finicky.

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As I just said and difficult to use and they brick quite easily as I have a lot of moving parts tend

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to flows of detection attempts to solve that by creating a framework API that uses tensor flow.

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No surprise there.

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To create an object detection modules using both our CNN family as well as the SSD family.

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So while the TI FOTA Woody API makes it far easier than until the remittance it still has a bit of a

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learning curve by the way.

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This is actually an output of the tensor flow optimization API with an SSD.

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It's quite cool isn't it.

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So now let's talk about it install and setup.

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Now if you're using the visual machine with this already installed you don't have to go through this.

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However it's not that hard to do so I'm just gonna go through it step by step.

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I'm not going to do it with you because I really have it installed on my machine and I don't I think

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if I try to reinstall it I could mess things up.

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But this is how I did it documented everything and it worked perfectly.

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So what you do basically activate activated computer visual library.

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We're not going to we're not going to install a disk because they can have a lot of clashes with packages

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and libraries being you know messy with each other not mixing well.

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So let's clone this environment.

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So we go into the terminal and go condo create and let's call this TFT we named this environment that

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so in future when you want to activate it you just go source activate TFT and it's there.

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So anyway copy this line in your terminal and clone your directory your sorry CV environment and then

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run this line here suited apt get install put above compiler Python pipe Perl Python Alexa Mel and python.

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Okay okay.

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Then we do pip install system pip install context lib Jupiter mapped lib and then go back.

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So just go back to old man home directory make up for local models and then get clone.

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This basically from here from this getup.

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Link here fanciful models and go back again to directory and get cloned this as well and now as we go

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back here go into this directory cocoa API Python API and end to make this will compile and build some

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stuff that you need and basically just copy this line here and then decide comments here so don't actually

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run this in a terminal.

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So this is where we get the intensify models from so you use w get put above zip and you download this

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link here and unzip this file and then you can delete this file afterwards.

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It's fine.

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And then what you do you get to part that we need to get everything working.

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So we defined this part here and then we go to our protection bills and we run the tests and if the

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stuff's tests run run successfully by opening this file we will know if this install works correctly.

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So go ahead and try it on your own.

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See if it works if there's any problems don't hesitate to contact me and all the times things change.

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We did the updates.

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So maybe just check this link if this isn't work first before you contact me.

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See if there's anything here.

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Menu maybe a new vision or a new dependency.

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You never know.

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Running the demo so download the python file in this folder.

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I actually do have this file in the in the in my Python the book files here.

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However they do work you don't don't run them from there they're actually copy and paste them into this

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territory here.

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So let me go to our virtual machine and I'll show you exactly where to find us.

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Okay so we're back in a virtual machine and directory I want you to go to is.

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Remember I told you based on our presentation here I wanted you to go to models models research oblique

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detection and put this file here or resources file here that you don't want it.

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Oh it's actually stored in your folder as well and your notebooks folder.

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But anyhow let's go to the surgery and I'll show you where to put this file since models models research

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and object let's type it in that type of it.

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Object detection and you'll see it is a notebook somewhere.

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This one here that is a file even a run from no one.

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Okay.

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So in the next chapter we're going to run this file and go to the Detroit tutorial.