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These are the user uploaded subtitles that are being translated: 1 00:00:00,512 --> 00:00:03,328 Now they're likely to be more control Laura's coming through 2 00:00:03,584 --> 00:00:04,608 In the next few weeks 3 00:00:05,632 --> 00:00:07,680 The original controllers control 4 00:00:07,936 --> 00:00:08,704 And control 5 00:00:08,960 --> 00:00:11,264 Can be used by Universe similar way in fact 6 00:00:11,776 --> 00:00:12,800 I used to control net 7 00:00:14,336 --> 00:00:18,432 At work flow that we use for the controller for the canny 8 00:00:18,688 --> 00:00:19,456 Control Laur 9 00:00:19,712 --> 00:00:21,504 And this was the result that I got 10 00:00:21,760 --> 00:00:22,528 Using the 11 00:00:23,296 --> 00:00:25,856 Best control net that has been interested for STX l 12 00:00:26,368 --> 00:00:28,416 This is in comparison 13 00:00:28,672 --> 00:00:32,000 Play control Laura the 128 Frank control Laura from 14 00:00:32,256 --> 00:00:33,280 Stability a 15 00:00:33,536 --> 00:00:35,328 So there's quite a lot of difference between the two 16 00:00:35,840 --> 00:00:36,864 And I would 17 00:00:37,120 --> 00:00:41,216 Play for this particular render I think the control Laura actually won a little bit 18 00:00:41,472 --> 00:00:44,032 The original image is this image here 19 00:00:44,288 --> 00:00:44,800 We are looking 20 00:00:46,080 --> 00:00:48,384 Put very nice 1024 / 1024 image 21 00:00:48,896 --> 00:00:51,200 And I think what we want to do with this one 22 00:00:51,456 --> 00:00:52,736 Is to take a look at 23 00:00:52,992 --> 00:00:55,040 How we can get better results Maybe 24 00:00:55,552 --> 00:00:56,320 Even then this 25 00:00:56,576 --> 00:00:58,112 Using the controller 26 00:00:58,368 --> 00:00:59,392 What are the control 27 00:00:59,904 --> 00:01:02,208 First introduced 28 00:01:02,464 --> 00:01:04,512 What's in February of this year 29 00:01:04,768 --> 00:01:06,048 And they were introduced 30 00:01:06,304 --> 00:01:09,120 What's the following research at Stanford University 31 00:01:09,376 --> 00:01:11,424 The research paper is one 32 00:01:12,192 --> 00:01:13,984 Is fairly interesting to look at 33 00:01:14,240 --> 00:01:16,288 And having done that I can show you 34 00:01:16,544 --> 00:01:18,592 The original concept so we 35 00:01:18,848 --> 00:01:20,384 What's the county Edge detection here 36 00:01:20,896 --> 00:01:24,992 Is one that we've looked at for the controllers and we're going to be looking at for the control Nets 37 00:01:25,504 --> 00:01:27,808 And you can see the basic idea 38 00:01:29,088 --> 00:01:29,600 Control 39 00:01:29,856 --> 00:01:31,136 Set an aspects of the 40 00:01:31,648 --> 00:01:33,696 Using the original image 41 00:01:34,208 --> 00:01:37,536 Now I want to take a look at other ways that you can use control Nets cuz 42 00:01:37,792 --> 00:01:40,352 Very well presented inside of this paper 43 00:01:40,864 --> 00:01:42,912 So there are more examples of the 44 00:01:43,168 --> 00:01:43,936 Play Connie 45 00:01:44,448 --> 00:01:45,472 And how it can be used to 46 00:01:45,728 --> 00:01:47,264 Can you generate different types of images 47 00:01:47,776 --> 00:01:48,800 And here we've got 48 00:01:49,824 --> 00:01:50,336 Results 49 00:01:50,848 --> 00:01:52,896 Working with automatic pumps and user 50 00:01:53,920 --> 00:01:58,272 And you can see it I really like this one and that one and you can see the cute kittens 51 00:01:58,784 --> 00:02:00,320 Some variations 52 00:02:00,576 --> 00:02:01,344 It's based on 53 00:02:01,856 --> 00:02:02,624 The 54 00:02:02,880 --> 00:02:05,952 What's the basic composition remaining the same 55 00:02:06,208 --> 00:02:09,280 So this is really about retaining compositional elements 56 00:02:09,536 --> 00:02:11,584 And we can see here also that you can 57 00:02:11,840 --> 00:02:12,608 Use 58 00:02:13,120 --> 00:02:14,144 That have been 59 00:02:14,656 --> 00:02:18,240 That have been created inside of stability 60 00:02:18,496 --> 00:02:19,520 That's stable diffusion 61 00:02:20,032 --> 00:02:23,360 What are the AI images to create the socials 62 00:02:26,688 --> 00:02:29,248 But the paper doesn't stop there it shows us how 63 00:02:29,504 --> 00:02:30,528 Line input 64 00:02:30,784 --> 00:02:32,576 Can be used to create variations 65 00:02:33,088 --> 00:02:34,880 And for the down we can see 66 00:02:35,392 --> 00:02:36,160 Other uses 67 00:02:36,928 --> 00:02:38,208 Basic scribbles 68 00:02:38,720 --> 00:02:39,232 How to 69 00:02:39,488 --> 00:02:40,768 Play Adele's variations 70 00:02:42,048 --> 00:02:46,144 The amount of research that went into this very simple elephant 71 00:02:47,680 --> 00:02:48,704 Produces these 72 00:02:49,216 --> 00:02:50,240 These variations here 73 00:02:50,496 --> 00:02:54,848 Has been going on for quite some time and quite a lot of what we're doing 74 00:02:55,360 --> 00:02:56,384 Basically 75 00:02:56,640 --> 00:02:58,176 Is built on this type of research 76 00:02:58,688 --> 00:03:03,552 But it's interesting to see how you can sometimes get less and less of research 77 00:03:04,064 --> 00:03:06,624 Kind of coming together in a single project 78 00:03:07,392 --> 00:03:09,696 Which certainly what seems to have happened here 79 00:03:09,952 --> 00:03:13,280 So there's a type of input known as the Hedge 80 00:03:15,328 --> 00:03:16,608 Another one is 81 00:03:16,864 --> 00:03:17,376 Play pose 82 00:03:18,912 --> 00:03:20,192 These women posing 83 00:03:20,704 --> 00:03:22,240 According to this kind of stick figure 84 00:03:23,264 --> 00:03:24,800 Add more posing 85 00:03:25,568 --> 00:03:26,592 So all of this is 86 00:03:26,848 --> 00:03:29,920 What's possible with the control net 87 00:03:30,432 --> 00:03:31,968 The posing head is 88 00:03:32,224 --> 00:03:33,760 Who's coming from a 89 00:03:35,808 --> 00:03:37,344 Michael Jackson's concert 90 00:03:39,392 --> 00:03:40,160 Turn lights to see 91 00:03:40,416 --> 00:03:41,696 The king strutting his 92 00:03:41,952 --> 00:03:42,976 Off in AI 93 00:03:43,488 --> 00:03:49,376 And we've also got some really basic stuff this kind of stuff I think this might be called segmentation 94 00:03:49,632 --> 00:03:50,656 You have to 95 00:03:51,680 --> 00:03:52,960 You'd have to 96 00:03:53,216 --> 00:03:55,264 Correct me on that if I'm wrong but you can see 97 00:03:55,520 --> 00:03:56,544 Play basic color 98 00:03:57,056 --> 00:03:58,336 I'm coming through 99 00:03:58,592 --> 00:03:59,872 Impressive images 100 00:04:00,128 --> 00:04:02,432 And what the research is the same 101 00:04:06,784 --> 00:04:09,344 It's kind of research has been done by several researchers 102 00:04:09,600 --> 00:04:10,880 Overtime Nvidia 103 00:04:11,392 --> 00:04:13,184 Stanford University 104 00:04:13,440 --> 00:04:15,744 And interestingly they compare 105 00:04:16,000 --> 00:04:20,095 Technique I think this is a technique which was developed by stability AI 106 00:04:20,863 --> 00:04:22,399 And we can see 107 00:04:22,655 --> 00:04:24,703 How did Technic actually compares 108 00:04:25,215 --> 00:04:26,751 The benefits and the 109 00:04:28,031 --> 00:04:29,055 And the disadvantages 110 00:04:29,311 --> 00:04:30,847 So quite a lot of stuff here 111 00:04:31,103 --> 00:04:33,151 If you're more research-oriented 112 00:04:33,407 --> 00:04:35,967 You probably want to take a look at this this paper 113 00:04:37,759 --> 00:04:39,551 What we want to do however is to look at 114 00:04:40,319 --> 00:04:41,599 Fatalities of using 115 00:04:42,367 --> 00:04:43,135 Control net 116 00:04:44,159 --> 00:04:48,255 One thing I wanted to mention with the controllers for some of the more advanced users out there 117 00:04:48,767 --> 00:04:51,071 Is that they do mention just how easy it is to 118 00:04:51,327 --> 00:04:52,607 Play train a control net so 119 00:04:53,887 --> 00:05:00,031 They say training is as fast as fine-tuning at the fusion model so if you want to get a little bit more sophisticated or advanced 120 00:05:00,287 --> 00:05:02,847 It should be possible to create your own control net 121 00:05:03,103 --> 00:05:05,151 But in future it may be possible ALS 122 00:05:06,175 --> 00:05:07,967 How to create your own control Laura 123 00:05:08,223 --> 00:05:10,783 Which can be derived from control net 124 00:05:11,551 --> 00:05:14,879 Came out a couple of weeks ago 125 00:05:15,135 --> 00:05:15,903 And if you want 126 00:05:16,415 --> 00:05:17,439 Download that one 127 00:05:17,695 --> 00:05:18,975 It is cold 128 00:05:19,231 --> 00:05:21,279 I think actually published by hugging face 129 00:05:21,535 --> 00:05:22,303 Go control 130 00:05:22,559 --> 00:05:24,351 Put candy sdx 0 131 00:05:24,607 --> 00:05:25,631 Dash 1.0 132 00:05:25,887 --> 00:05:29,983 So this one is the one you download I'll have a link to this particular page 133 00:05:30,495 --> 00:05:33,823 And there are a number of options they've got here so the one I will be using 134 00:05:34,079 --> 00:05:36,127 I think it's going to be the safe tensor 135 00:05:36,639 --> 00:05:39,711 5 gigabyte one away it might be the pickle 5 gigabyte 136 00:05:40,223 --> 00:05:41,247 One of those two 137 00:05:41,503 --> 00:05:45,599 And you can if you want to download the 2 1/2 GB versions of these on 138 00:05:47,391 --> 00:05:48,671 Heard some feedback 139 00:05:50,207 --> 00:05:56,351 Different uses not everyone is getting success with smaller ones so the larger ones I've not had 140 00:05:56,607 --> 00:05:58,143 Play anything but success with those logic 141 00:05:58,911 --> 00:06:02,495 The project itself contains quite a lot of information about how 142 00:06:03,007 --> 00:06:04,287 The control that can be used 143 00:06:04,799 --> 00:06:07,615 But we'll cover the basic use patterns in this video 144 00:06:08,127 --> 00:06:09,407 Oh and following videos 145 00:06:09,663 --> 00:06:11,455 And I'll give you some 146 00:06:11,711 --> 00:06:16,319 Files that you can use to set up your own control nest and get some pretty decent results 147 00:06:19,391 --> 00:06:22,463 Now conceptually controlling is a very similar to control Laura 148 00:06:22,719 --> 00:06:26,559 And if you haven't watched the videos on control Laura's I would recommend that you watch those 149 00:06:27,327 --> 00:06:29,119 Working with controllers 150 00:06:29,375 --> 00:06:30,143 Because everything 151 00:06:30,399 --> 00:06:31,935 We need to do for the control 152 00:06:32,191 --> 00:06:33,727 What's needs to be understood 153 00:06:35,007 --> 00:06:37,055 From the videos inside of the control 154 00:06:37,311 --> 00:06:39,103 What is the same process you need to download 155 00:06:39,359 --> 00:06:40,895 The same extensions 156 00:06:41,407 --> 00:06:42,175 And 157 00:06:42,431 --> 00:06:45,759 Will show you in the next video how to actually put everything together 10873

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