AI_DL_Assignment / 21. TensorFlow Object Detection API /2. TFOD API Install and Setup.srt
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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.