 This video is sponsored by Squarespace. Let's play a guessing game. What do you think the difference is between the photo on the left and the photo on the right? And I'll give you a second to formulate your guess, and then I'm going to start giving clues. Okay, so clue number one, these are the exact same data. So it's not additional time on the target that is making the difference here. And so that clue means it must be something in how I processed the data. Clue number two, it's not star reduction. I haven't done any typical star reduction techniques on these images, and I actually haven't done any star reduction in many years, and I'll explain why in this video. Okay, and the final clue, even though I called this my secret weapon in the title, it's actually something that I've shown on the channel many times before in both my processing walkthroughs and in my critique videos. So do you have it? What is it? Well, my secret weapon to get my photos looking like the one on the right is star net plus plus. And so that's a star removal technique. And I should say more generally, any method for doing star removal during processing and then adding the stars back in, that's my secret weapon in processing. And we'll get into why this is so powerful during the video. But in a nutshell, let me just explain sort of how it works. What star removal allows you to do is, of course, separate the stars from the rest of the picture from the nebulae. And so you can stretch and process these two parts of the picture separately. And what this allows me to do is bring out these really deep dusty structures that you don't see in the picture on the left. And it also allows you to control the star field through the stretch. So I just think the star field looks a lot better when you can really control its appearance by stretching it separately from the nebulae. And to me, this is a lot more effective than doing star reduction. And like I said, star net plus plus is the one that I'm going to be showing how to use extensively in this video because it's free and it works well. But there are other star removal methods. The first one I personally used and was J.P. Mezzavino, and he was definitely an innovator, maybe the first amateur to really popularize this method, especially for narrowband. He called his method the tone mapping method. And it used Photoshop's dust and scratches tool for removing the stars. And it was great. I used it for a number of years, but it was time intensive. And so when star net came out, which uses a neural network trained on astrophotography images to detect and remove the stars, I was immediately hooked on that because star net is just super fast compared to the old, more manual method. And then today we also have Russell Croman star exterminator, which I've also used. I have a license for it. It works super well to sometimes better than star net, but it's a paid plugin. I can't remember the exact price, like somewhere between $1,500 for both Photoshop and Pixinsight. So in this video, I'm going to be going deep on star net, which is free, specifically including installation of it, use of it, and so forth. Because there are actually a bunch of very recent developments, one of them being the use of star net inside the new version of serial 1.2.0, which you can watch my video on right here. It's a really big update for serial and the star net part of it makes it very powerful. And there's also a new experimental Mac OS optimized version. So if you're on an M one or M two Mac, you can really speed up your star net by using that new experimental version, but it's a bit different to install in you. So I'm going to show that in the video too, but I'm going to start with just the basics of the method as I do it. Taking out the stars, putting them back in, how I do that in my processing routine, and this part will apply no matter which specific tool you're using for the star removal part. And after I show how the method works in my processing, I'm going to go into a lot more depth about installing and operating star net version two in particular. So we're basically going to start big picture and then I'll get into the nitty-gritty. So let's go. This is an image of the blue horse head nebula. Of course, you can't see much yet because this is still in its linear state, meaning we haven't done any nonlinear stretching to the image yet. And that's where you really get to see the image. So let's go ahead and start doing that. I'm just going to pull up a levels command here and take this mid tone slider and bring it over towards the data right there. And then I'll bring the shadow slider and the mid tone slider in towards the data. And this is going to stretch out that curve. You can also do this with curves or any other stretching tool that you prefer. But the important thing here is visually, I want to show you where I like to bring it, which is right about here. Now this is not fully stretched by anyone's standards. I think most people would say there's not enough contrast here. It's too dark. But this is where I like to bring it before applying StarNet or some other star removal program. Because if you go too far, then it's just not as effective. I find that a low to medium stretch is what really works well, especially if you're going through my whole process of bringing the stars back in with a screen blend. So this is where I like to stretch it. You can see I did it pretty quickly. Now, if you were just going on with standard processing, the problem, of course, is if you just keep stretching the image, I'm going to undo all this, you get something fairly interesting pretty quickly. But look at that star field. It just really, really takes over. And the image ends up very sort of hard and contrasty, which is not what I'm going for with Nebulae. So this whole thing that I'm talking about right now really applies to processing Nebulae, where you're going for maybe a softer look where the star field isn't so prominent. So anyways, let's undo those past few levels right there. And sometimes I might go a little bit further than this. Something like that, maybe. But something around here where the stars look how you want the stars to look. That's the important thing here, I think, is in this initial stretch, get the stars looking how you want them to look and don't really pay attention to what's going on with the Nebulae yet. Okay, and then you go ahead and make sure that you are 16 bits per channel. If you're in 32 bits, you're going to want to switch it at this point. And then you'll save as, and what you want to save as is a TIFF. And if you have used any adjustment layers or anything else, if there's more than one layer over here, before you save, you should flatten the image, which if I had more than one layer, this option right here, flattened image would be available under the layer menu. Okay, so now I'm going to save it. I'll save it as a copy. And I'll save it to the desktop as stars. Okay, and then if you are using StarNet command line, which I'm going to show in a lot more depth later, you would just put it into the StarNet folder and open up your terminal and type in the appropriate command. So first I have to move to the directory. So I'll just do that this way, CD space, drag this in. And of course, again, I'm going to show all of this a lot slower after we get over this broad strokes thing. But I just want to show you step-by-step how I do this process first. Okay, so this is called StarNet to the input file is stars.tiff and I want to call the output file starless.tiff. Okay, and this is by the way, the new Mac OS optimized version that works on Apple Silicon. And you can see how quickly it works. It's really pretty amazing. I'm going to show how to install this because it's a little complicated. Okay, that's done. It took about 20 seconds or something like that. And now we can see here in that same folder, it has generated this nice starless version. Now it did leave a few bright star cores, but that's fine. It's really not going to affect the way that I'm going to show you how to do this. So next we just go back to this exact same Photoshop file and we can do file, place embedded and drop our starless image right on top. Press enter and change this blend mode on the starless image from normal to screen. Okay, and so now we're at this point. You can see it looks not that great. It looks very low contrast and not very bright, but here's the cool thing now because we have this starless layer and the stars on different layers, we can work on them separately, but see what it's going to look like with them combined. So this is how I really love processing. So now I'm just going to open up layers on the starless layer and as I'm adjusting this, I'm getting an idea of the final picture, but I'm only adjusting this starless layer, right? And at this point, I usually move to curves and I just do this very slowly. I just apply more and more contrast Wow. Look at that. Look at that. That's already looking so nice. Just to the starless layer and you can see because I placed it into the image, these actually come in as smart filters that I can turn off and on. I just really love Photoshop for some of these features. I know that a lot of people have moved on from Photoshop, but it has some things for processing that I just find so convenient and that's it. That's my... So then, I mean, to finish off this image, I could just add some saturation. Right? So it's really, really simple, I think, to get a really high quality image this way. I mean, of course, this picture still has some problems because it's only 30 minutes of data and I haven't processed it carefully, but you can see how quickly we went from the not stretched image just stacked to something that looks really good just through this technique of removing the stars and applying my curves just to the starless layer. Okay. And what I just showed, of course, is going to work whether you're a starnet user, a star exterminator user, a Dustin Scratches method user. It doesn't matter how you make this starless layer. The key thing is just that you separate the stars and the starless layer, apply a blend mode to one of them, and then stretch the starless layer separately from the stars. So the stars stay nice and small while you can bring out a lot of this dim stuff in the starless layer. Now, in terms of screen blend and different kinds of blends, I know that some people prefer linear dodge. In this example, with not much integration, this is just 30 minutes, to my eye, linear dodge is creating more noise, more color noise, but in some cases I would use it because it might work better, but screen lighten in some cases and linear dodge are the most common blend modes. I like 90% of the time use screen. And I should say that if you are a Pixinsight or Serial user, those both have a process called pixel math. And in pixel math, you can actually do any of these blend modes. It just requires knowing the right formula. So I'll put up the one for screen right now so you can see what it is. And I'll also show that in more depth in Serial and Pixinsight specific tutorials, but this one is more just sort of generally about this starless method. And the way that I'm almost always doing it is here in Photoshop, just because I love the ability to see what I'm doing live very quickly. And even go back in, and if I change my mind, slightly change a curve, it's just a really nice ability. Oh, actually, one more thing I should say about this, when I did this, it's very easy to, you know, overdo this technique. And you can see when I've overdone it, it's cool because I can see all of this really dim stuff in the background. Even this weird, you know, H2 region over here, but it also is bringing up the noise. And so this is a complaint I get all the time about this method is, oh, why would I want to do that? It makes the noise so bad. And really what it's doing is it's just, you know, revealing the noise by bringing up all of the levels. So when you bring up the signal, you also bring up the noise. Now, the only real answer to this is, okay, you have to go gather more data, because this is just 30 minutes. If I did times 10 and got, you know, 30 hours of this, all of this noise would just disappear. Now, that's not always possible. So the other thing that you can do is noise reduction. But what I'd really encourage you to do is, just be realistic about how far you can stretch your data. And just be comfortable with this still looks really nice. You don't have to go to the extreme, right? You can just find this sort of happy medium where it looks good. And you can also start playing around with masks, because here in the blue horse head, this is a fairly high signal area. Out here in the dusty parts, this is a low signal area, where the noise is going to really come up if we try to stretch this too far. So you can play around with masks as well. I will say that there are, you know, noise reduction methods that I play around with. One of them here in Photoshop is the camera raw filter. I don't like the sharpening and noise reduction sliders too much, but I love this color noise reduction slider. I use this all the time. It will make your whole photo look a little less saturated, but it's really great for removing a lot of this weird splotchy color noise in the dim areas of your photo. I don't know if you can see that on the video, but it really does work quite well. Okay, so that's it for the broad strokes part of this video. I hope you understood sort of my method here. You understood sort of my method here. It's really not super complicated. And before I jump into the nitty gritty of StarNet installation and use, let me tell you about today's sponsor, Squarespace. Squarespace is the all-in-one platform for designing and hosting a beautiful website or portfolio. I was amazed when I went to redesign my personal site, nicocarver.com, just how fast I could put something together with Squarespace's professional templates. I just chose one that I thought looked good. I dropped in my photos here into different categories. And I got to pick what the categories were, of course, and Squarespace handled the rest. No fiddling with code. Everything is what you see is what you get with their website editor. But if you do want to go in and make some changes, it is very easy to change the design, add captions, change how the photos look, all these kinds of things are, of course, possible. And so I think this would be a great choice if you want to have a nice, professional-looking spot to share your astrophotography with your own domain name. So if you're interested, head over to squarespace.com slash Nebula Photos to start your free trial. And if you like it, you can get 10% off your first purchase with the code Nebula Photos. Okay, now we're going to dive into StarNet. And this is going to be fairly exhaustive because I'm going to show all the different installation and use procedures for all the different versions. StarNet used to be available on SourceForge. And now it's on its own website, starnetastro.com. So this is where you go to download everything. Once you're here, just click on download. And there's a bunch of different versions. We're going to start with all the macOS versions before moving on to Windows. I'm not going to show Linux, but it's fairly similar, I imagine, to macOS, but easier. MacOS has a bunch of new security features. And I'm doing features and air quotes because they make it sort of difficult to install software like this. But anyways, we're going to muddle through it. Let's start at the bottom here with the command line tool. So click on macOS. It will automatically start downloading a zip file to your computer. Double click that zip file to unzip it. And then you can get rid of the zip file, leaving you with just this folder. Now you can put this folder anywhere you want on your Mac. I'm just putting it here on the desktop to make it easy for this tutorial, but it really can be anywhere. It doesn't matter. The next thing you're going to do is open up the terminal application. So you can just either press command spacebar or click on this little magnifying glass up here and start typing in terminal, T-E-R-M-I-N-A-L and press enter. It should open up something like this. I'm going to make mine bigger. And this is how we're going to actually interact with the StarNet application, which is all inside this folder. The first thing that we're going to actually have to do is change a bunch of permissions. But before we can even do that, we have to actually get into the folder on the command line. Right now, I can see that my working directory is the my home directory. That's this little tilde right here. So to change directory, we just type in cd for change directory space. And on Mac, there is a handy feature where if you drag a folder or a file into the terminal window and let go, it will copy the path right there into terminal. So now I can just press enter and we can see we've moved to that folder because now our working directory is that folder. And let's run some commands now. So the first command we want to run is called chmod, S-C-H-M-O-D space. And what this is short for is change mode, I believe. But it's just sort of thought of, by me at least, as like the permissions command. Like it gives permissions for the operating system to do different things with your files. So the only kind of permission we need to add for this command line one is the execute command. So we do plus x, x for execute. And we're going to give this permission to both star net plus plus, press enter. And to the shell file and run underscore star net .sh. And I'm going to, of course, I'm going to, of course, put all of these commands in the video description, but I will warn you if you copy and paste them, that you do have to copy and paste them one at a time, pressing enter after each command. Okay. And then we're going to do a sort of weird one for the lib tensor flow framework. So instead of chmod, you're going to do xattr-r-dcom.apple.quarantine. And then the name of the file. And a little tip for command line stuff, you can just press tab after you've written part of the name. And there's two lib tensor flow files. So I have to put in the next part. Okay. And then press tab again, and you can get the full file name there without typing the whole thing in. I'm going to press enter. Okay. And after you press enter with any of these commands, if you get an error, read that error message, because it usually will tell you what you did wrong. If it says file not found, then you misspelled it. If it says, you know, wrong command, then make sure that, you know, you're typing in the command exactly as I did here. Anyways, we've now set up the permissions structure for this to work. But macOS is going to give us a few more curve balls as we try to run this. But let's try to run it here for the first time. So to make this work, we're going to have to put our file, we want to make starless into the folder. So I'm just going to drag that into the folder. And then I'm going to change this shell file, this run underscore star net.sh with text edit, just telling it, you know, what the name of the input file is, which is stars.sh and what the name of the output file should be. So you can name these whatever you want. This one, you know, this input file has to match the name of your file here, what you want to make starless, but then you can call the output file whatever you'd like. But it should read like this, you know, dot slash star net plus plus space input file space output file. Once you've done that, you can save that shell file and close out of that. And then we can try running it here in the command line. So to run it, you just do dot slash run underscore star net dot sh enter. And it's going to throw this nice error message at you. It can't be opened because the developer can't be verified. Do not click on move to trash. Click cancel. Then go up here to your Apple logo in the upper left, go under system preferences, open up security and privacy and click on allow anyway. You can leave this open because we're going to use it again. We're going to run that command again dot slash run star net dot sh enter. Click open. It's going to throw another error. Lib tensor flow can't be opened. Okay. Click cancel. Click cancel again. Down here in security and privacy, click allow anyway. Did it let me do it. So now let's actually just run it like you would after everything is set up like this. So you're just going to open up terminal, change the directory CD space, drag this in, press enter. Make sure that your picture is in there that you want to make starless and that here in the run star net dot sh that it has the name of your picture and what you want to call the output file. And then just in command line type in dot slash run underscore star net dot sh. Let me say something about this. Just click open. Give it a second here. And there we go. So now it's going and it's that easy after you get it all set up. It's really only the first time you install it on your Mac that it's very annoying. After that, it's not too bad. It does take a while on this pretty good M1 pro laptop. This older version of the command line interface takes about, let's time it three and a half minutes to finish. But there is a newer version right here. See new experimental CLI distribution from macOS. Now I'll click on here to open it up. This one, it says right here on M1 chips. It will actually work on M1 or M2 chips, I believe. But don't quote me on that. I personally have an M1 chip, so I haven't been able to try it on M2. But anyways, the way to know if you have that kind of chipset is to go into the little Apple up here, click on about this Mac, and it should tell you right here under chip. If you see Intel here, then you can't use this version. But if you see Apple, then this is worth a try. Okay, just like before we can click download. It'll download the zip file and you'll just double click it to unzip it. Get rid of the zip file. Open up this folder and you'll see that there is some readme instructions. These are mostly correct in terms of installation. They just, there's a little bit of a wrinkle that I'll show you. Okay, we're going to start by doing some permission stuff. So we'll do that chmod again plus x. Let's make sure that starnet2 can run. That's the name of it here, starnet2. Press enter. Oh, forgot to move to this directory, cd space, drag this in. Okay, try that again, chmod plus x starnet2. Okay, and then we're going to also do that chmod plus x on the install.sh file. Okay, and then the readme says, okay, just run the install.sh. So we're going to do dot slash install.sh, give it our password. And I got this error. This is a copy error saying user local lib is not a directory. So I'm not sure what that meant, but I knew how to find directories on my Mac. So what I did was I went to finder here, went to the go menu, went down to go to folder and typed in slash usr slash local, double clicked. And this is what I found. I found that under usr local, there was no lib directory. So we can just make one. A directory is the same thing as a folder. So we can just right click and choose new folder, get our password again, and type in lib enter. Okay, so now there's a lib folder for it to copy some things into. So we can now type in that command again dot slash install.sh enter. And this time it worked. And I know it worked because look at all of these files that it copied into that folder. All right, so now we can actually try out star net two. It's a little bit different than this previous incarnation. Instead of using that shell file, you just type in star net two and then use the sort of the common command line language of like dash h dash i, all these different like flags that it uses to tell it different things to do. So if we do star net two space dot dash h, this is the help option. And so it will give us all of the different things that we can do with the command line. So here's the usage and then here's all the different things you can try. I'm just going to do a really basic one here. So I'm going to do star net two. Let me first copy my stars dot tiff file into there. And do dash i for input. And we want the input to be stars dot tiff. And then I'll do dash o starless dot tiff. Okay, so this is just like before. It's just a sort of a different way of operating it. We're just telling it this is the input file and this is what I want to call the output file. And you have to make sure that the input file stars dot tiff is in this folder before you run this. Okay, I'm going to press enter and look at it go. As Nikita said here, it should be blazingly fast on M1 CPUs. And that is definitely true. Look at that. I think it's only going to take about 30 seconds to complete. Well, remember the old one took over three and a half minutes. So a huge speed increase. And then we also get some extra options here in terms of what we can do with it. Like making the mask image and things like that. But in terms of the actual output of the starless image, it should be identical to what you get with the older version. Next thing that I want to show you is that StarNet has been incorporated into Serial along with a lot of other cool star processing tools. They're under image processing, star processing. But when you click on star net star removal, you'll see that execute is grayed out and it says no valid star net executable found in the installation directory. So let's cancel out of that. And you actually have to go over here to preferences, miscellaneous and tell it where your star net plus plus installation directory is. Now, if you are on Windows or you have the star net GUI or if you are a PIX insight user and you have the star net plugin, neither of those ones are going to work. You actually have to get the command line version of star net and point to that. For more information about Serals implementation of star net, check out this video right here because I've covered it in depth in this video introducing Serial 1.2.0. So I'm not going to repeat it here, but it's a really neat implementation, including this ability to basically have the starless and star version blended and change their stretches live with the star recomposition tool. So you're definitely going to want to check that out. And let's go over the PIX insight plugin. This one has given me a lot of trouble on new versions of macOS. Well, it used to be much easier to install, so it's too bad, but we'll get through it. Don't worry. It's just a lot of little steps. And then once you do it once, it's all in there and installed, and you don't have to worry about it until you update PIX insight. Okay, double click the zip file as we have been doing. And then as we have been doing, we're going to open up terminal again. Let me look at the file names. And we're going to again use chmod. This time, though, instead of doing that plus x, we're going to do 755. This is read, write, and execute. And the reason we have to give it read, write privileges in addition to execute is we're not going to be running this off the command line. We're letting PIX insight find these files, and so it needs to be able to read them. So we're doing chmod 755, and then what I'd suggest is just drag in the file here in Determinal, press Enter, and we'll just keep doing that for each file. And the nice thing is, even if we copy these files, even if we move them, these permissions should continue with them. So I'm just doing it for each file in the directory, except for license and read me, because we're not going to be using those. All right, done. Next up, we're going to be copying and moving a bunch of these files into different places on the computer. So to do that, open up a new Finder window, Command N. Go to your Applications, and scroll down to the PIX Insight folder. And here, inside the PIX Insight folder, go into Bin, scroll down and Bin, until you see all of these files that start with LibTensorFlow. Click on the first one, Shift-click, click on the last one, and then press Command-Delete to delete them all. You're going to type in your password. Great. Now, we're going to go over here to what we downloaded. Click, hold down Command, click, click, click. So you have these four files selected. Right-click, choose Copy. Right-click on Bin, choose Paste for Items. Type in your password again. Okay, and just double-check that all of those copied over. Yes, they did. I don't know if this is necessary, but some people say you should also copy this weights file to the Lib folder. So we'll do that. Okay. And then, there are a couple more places we want to copy these LibTensorFlow files. So, click on the PIX Insight application here inside the PIX Insight folder. Then, right-click on it, choose Show Package Contents, go into Contents, Frameworks, and copy these guys over. And one more place. If you followed me in the earlier command line parts, you already have created a new command line. You already have created a user local-lib folder. If you haven't already though, go ahead and make a folder in here, user local-lib, and then copy these two files into it. Great. Okay, so now we've done all the copying of files to various places. Now we can go ahead and open up PIX Insight, and hopefully it will install just fine. Just in case this is useful for future people watching this, I am on 1.8.9-1. I think that's the latest. Oh, and it build 1556. Okay. And we're going to go to Process, go down to Modules, click on Install Modules, make sure the directory is Applications, PIX Insight, dash slash bin, click on Search, and usually if you get the beach ball, that means it's working. So it should find StarNet here. Yep, one additional module were found on directory. Okay, click on that, StarNet 2, and click Install. Okay, you should see one of one modules installed. And now if you go to Process and go down to, etc., right there at the bottom, StarNet 2. And we want to make sure that it's actually working. So go ahead and click File Open and open up your picture. And this one isn't linear, so I'm going to uncheck that. That is a cool thing in PIX Insight and also now in Serial that you can use linear data. What it actually does, I think, is it stretches it. It removes the star and then it stars and then it unstretches it, something like that. But this isn't linear, so we're going to uncheck that and then just drag this little new instance triangle icon onto the picture. Make sure that it's working. Yes. Okay, so if you start seeing that percentage going up, then you know you've installed StarNet correctly into PIX Insight for Mac. I know that was complicated as well. But we're going to now move on to Windows installation and use of StarNet, which I think should be easier. So let's go ahead and move over to Windows. Okay, now I'm on a Windows machine, so let's try some of these Windows options. So starting with this one, the graphical user interface. So I'm just going to click Windows there. Just like before, it starts downloading a zip file. It's a zip file, so if I just double click it and click extract all. And now you can move this folder wherever you want. I'll just move mine again to the desktop for ease of tutorial making. Okay, if you'd open that folder, there is an application inside called StarNetGooey. If you double click it, it says Windows protected your PC. Don't run, but just click more info and then you can click run anyway. And this is quite easy to use. All you have to do is click browse and my file is on the desktop. So I'm going to click desktop, click on the stars file. And I do not want to overwrite it. So I'm going to rename my output from stars.tiff to starless.tiff. And it has instructions right down here too. So even if you I think this is pretty easy. I think anyone can do this one. So then just click run. And there we go. And we're off to the races. Now on Windows or Linux or an older Mac, if you have an Nvidia GPU, you can speed this up by using that instead of the CPU to run StarNet. And I'll include some links in the description for how to do that. I'm not going to show it in this tutorial because other people have already covered it. But it's pretty cool. It can really speed up StarNet. Okay, it's finished. And let's just check the output here. It looks exactly right. So I think and then you can just close out of that. I think this is probably one of the easiest to use. I think it's very easy to install and to actually operate. So if you're on Windows, don't be afraid of StarNet. It's quite easy. Okay, moving right along. Let's try the PIX Insight plugin. So I'm just going to download it and extract it. Okay. And then I'm going to go to Windows, Program Files, PIX Insight, Bin. And I'll copy TensorFlow, StarNet weights and StarNet 2 into this folder. Okay. And then Open PIX Insight. Go to Process, go down to Modules, Install Modules, click Search. It says one additional found, StarNet 2. Let's install it. Okay, installed. And then let's try it out. So let's open up a picture. And then under Process, go down to Etc. Open up StarNet 2. This isn't linear data. So I'm going to uncheck that and then just drag the new Process icon onto the picture. And as long as you see that percentage progress thing starting to go up, you know that StarNet has installed correctly in PIX Insight for Windows. So again, a lot easier than on Mac. Let's keep moving here. So let's try the command line tool. Now you might be asking why even use the command line tool when Windows has a graphical user interface already? Well, one reason might be if you want to use it with Seral. Seral wants you to download the command line tool and point to that. So if you use Seral on Windows, this would be the way to do it. Okay, there's it's downloaded. So I'm going to extract it and put it on my desktop and open it. Okay. And the way the command line one works is there's this Run StarNet batch file in here. If you open that with Notepad or something like that, you'll see it looks something like this. It's calling the executable StarNet++ and then it's here's the input and output. The default is to use this test file, but if I change it to stars and save this, then I can just double click on run underscore StarNet and it should start going in Windows command line here. And the only reason I'm really showing this is because just in case anyone needs it. And also if you are a Seral user, this is the directory that you would point to to get StarNet working in Seral. So that's it. Hopefully this was helpful and you're now seeing the names of everyone who supports this YouTube channel over on patreon.com slash nebula photos. It's an excellent community of dedicated amateur astrophotographers, just people who want to learn and are very willing to share their own expertise. We have over 800 members now. There's an active discord that you can get involved in. And I can't thank my patreon members enough because I'm now doing this full time. Thanks to all of you. And it is what has allowed me to make these videos and to really pursue this as my own business. So thank you so much to all my current patreon members. And if you enjoy this channel, I think you will get a lot of benefit out of joining my patreon community. It starts at just $1 a month. 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