21. TensorFlow Object Detection API/3. Experiment with a ResNet SSD on images, webcam and videos.srt

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OK.

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So welcome to the 21 point to where we actually start playing with our SSD inside by using sari

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Hi welcome to Chapter 21 point to where we start experimenting with the object of action SSD based on

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resonate and we do this on images webcams and all of them feel it and videos.

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So let's get started.

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So now we're here in a virtual machine.

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And this project is going to be a bit different as we have done because we remember we created a new

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environment so we have to launch what I put in the books from a new environment so fiercely that school

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source caps lock is on source activate T.F. the API to get us to not use on the school.

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There we go.

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So that's a environment that we're in right now.

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So that's good.

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I will have to.

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This will probably be any name you name that previously before if you're not using my pre-installed

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with your machine.

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So I put iPod it's on the books and it brings up a point on the book browser of Jupiter.

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So now what I want us to go to is really there are two ways to get a set up.

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You're supposed to download and I put it in the book file in the resources file that file was basically

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this here.

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All right.

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However I left it in the artery here in case you wanted to manually copy and paste it into the directory.

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So let's actually go ahead and do that.

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So copy this file control Control-C and the doctor wants you to go to was the Saathiya models models.

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Research sorry and object detection and pissed that file in to here.

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OK.

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This one here is actually ulo.

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It's not actually going to work to paste it into here.

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So now let's go to a Titan notebook browser and find this directory.

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So find the file.

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I should say so.

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Good models research.

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Scroll down to object detection

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right here and let's launch this file.

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Ok so here we go this file here is actually not a file I created I just modified it slightly.

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This is a father comes intensive flows observation API and it allows you to basically play with the

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different features in it it's in the official Demel.

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So let's run the first box here.

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So imports this plot of stuff in line by the way in case I haven't mentioned it to you what this does

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is that it generates matplotlib Matlab plots inside a phone book as opposed to having it be like an

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open TV and a new window.

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So anyway that's duties imports here as well.

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And let's run this block here.

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These old directories would basically point to different models.

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This is the SSD.

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This is a resident SSD will be using that street and the cocoa.

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That's a common object data set and it's going to download it the first time if you didn't already have

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it saved is going to lose here.

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Actually I do have it saved so it should not download.

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I hope it is doing something so maybe it is downloading.

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So anyway let's run this box and wait for that to finish.

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And we load a little nap some help a code and then we do our detection boxes here and don't mind these

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red things that look like it's going to be at URL.

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This will still run.

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So it's fine.

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So right.

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These these boxes have from now.

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So let's do that we do this one and remember some of us do it again.

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Let's run this one.

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And that actually was not up wanted yet.

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This is what we want.

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So it goes through the images in a Test spot and it still takes a while to run.

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To be fair.

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And what it's going to do is basically it's going to take that image it found out and basically run

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all of these SSD functions that require it to classify detect objects here.

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So here we go.

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So the first first test image it picked up this is a dog you can see it clearly says this woman.

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I'm pressing control and moving my mouse button and we can see it's a dog here.

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And you can see the probabilities.

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It's a bit hard to make out.

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Maybe we can actually change some parameters here to make this a little more legible.

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Insightful.

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I applied in the book.

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It's a dog here and a dog here.

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So it's quite good.

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This is the image I use in my presentation slide.

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You can see this is a kite kite kite person person and these are the probabilities which I can read

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it looks like 60 tree just looks like a hundred.

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But what it is it is.

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So now let's try it on a webcam and I'm pretty much looking like a bit of a mess right now because it's

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quite late.

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And I have not comb my hair for a while but I'm sober to try this.

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So let's run this webcam should come on any second now.

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All right.

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This is me in my natural element here.

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And you can see that actually went up T-shirt on ice free advertising for Apple.

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So this is me here and this is the person box that's affecting me right now.

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So this is actually pretty cool.

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So let me just close this and no let's try it out on the video.

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So this is a dash cam video I downloaded off YouTube.

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And so let's it it

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it sometimes takes a while to load.

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Oh there we go.

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So this is a tip.

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So this is pretty cool.

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If I if I do say so.

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So we're running it here detecting imprisons cause I think we just saw a bike from a mistaken call again

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and the frame rate isn't that bad.

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Honestly it being on a C.P. you not a GP.

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This is actually pretty sick.

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So let's close this video now.

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So you've just run and experimented with SSD single shot detector.

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So I hope you found this chapter fun.

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I found it quite fun to play with this as well.

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What you can do is put any video you want here.

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Another dashcam video as well and any images you want.

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We'll go there to see what fall they look at Image Pat.

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Basically find fine image that is obviously not defined there.

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Keep going.

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Testament.

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It is as if it's about OK syntactical test images.

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This one here.

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So this is the directory we're looking at.

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We had what else images in it.

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I'm not sure what's in this file.

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I guess it's a source file for you want to put your source for images to sometimes.

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So this is pretty cool.

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So you can experiment with a web cam with your test images and watch your videos.

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OK.