Alright team, let’s dive into today's tutorial on creating consistent characters in AI-generated images. We'll explore using a character reference URL for consistency and in-painting to vary scenes with the same character. We’ll also look at a blending hack, though it might not be available forever. Let’s get started and elevate our creations!

I'm not sure how creating consistent characters will really benefit our fizzy drink company. \n
I mean, isn't it more important to focus on our product and marketing strategies? \n
But I guess if it can enhance our brand image or help us in storytelling, it might be worth exploring. \n
I'm curious to see how this tutorial will change my perspective. \n
Let's give it a shot and see what we can learn!

Consistency is key when it comes to creating memorable and believable characters in storytelling. Whether you're writing a book, a screenplay, or a video game, ensuring that your characters remain consistent throughout different situations and scenarios is essential for maintaining their authenticity. In this blog post, we'll explore some techniques and tools that can help you achieve consistent characters in your creative projects.

One effective method for creating consistent characters is demonstrated in the transcript above, using OpenAI's DALL-E model. The transcript highlights how you can generate different variations of a character by using different prompts. However, to maintain consistency, a specific parameter can be added to the prompt, known as the "C dot E F character reference." By adding this parameter along with the character's URL and specifying a desired consistency level, the model can generate variations of the same character that remain consistent with each other.

Additionally, the transcript introduces another technique that utilizes in-painting to create consistent characters. By taking an initial image of the character and manipulating it using in-painting tools, you can create multiple variations of the same character in different scenarios. This technique allows you to cut out specific parts of the image and replace them with new backgrounds or outfits, resulting in a consistent character that can be used in various situations.

One of the advantages of using the in-painting technique is that you can generate multiple images of the same character, each with different expressions, poses, or settings. This can be particularly useful when mapping out different scenarios that your character needs to be in. For example, if you're writing a detective novel, you can create images of the character in various crime scenes or interrogation rooms. By having a range of consistent character images, you can effectively illustrate the character's development and experiences throughout the story.

Furthermore, the transcript suggests that you can use the generated character images as training data for your own stable diffusion model. By refining the generated images and iteratively improving upon them, you can create a more customized and consistent character. This can be especially valuable if you want to have more control over the generated variations and ensure that they align with your creative vision.

It's worth noting that while the techniques mentioned in the transcript primarily rely on AI models and tools, there are other traditional methods for developing consistent characters. These include carefully crafting character profiles, defining their personalities, motivations, and backstories, and ensuring that their actions and dialogue remain consistent with their established traits. These traditional methods can work in conjunction with AI-generated images to create well

Consistent Characters

 Okay, I'm going to show you how to do consistent characters in mid Jenny. So this is an example of a character I wanted to replicate. Like I've got a picture of her and the party just generated this, using this prompt. But say for example, I was writing a story about. She was one of the main characters I'd want to show her in different situations, maybe in the dentist office or at a birthday party. 

Whatever it is. And if we use the same prompt again, we're just going to get different results. And see all of these like very clearly different people, even though they're quite similar. So how do you keep them consistent? So mid Jenny actually added one way to do this. 

So if you click a copy of the link and then let's put in the same prompt again. Actually, yeah, that'd be grab the prompt.  

Just say 

At a dentist office.  

All right. A.  

Okay. So that is a new prompt. And obviously we just run that. We're going to get like a very different person. But no, to keep it similar, just going to click copy link.  And then the parameter you need to add here. Is , 



C dot E F character reference and then paste in the URL. Then you want to add dash. 

You want to say C w. And let's just say. It's, this is from zero to a hundred and so we want to keep it at that's how consistent you want it to be? Let's keep it like 90 on it to be very consistent. All right. Now let's pace that and see. How it works.  And what a man Jenny should do here is keep that character relatively consistent. Over time. 

So that would be really helpful.  

But obviously, while that's running, I'm going to tell you about a different technique that I use. That doesn't rely on this proprietary feature. It uses in painting instead. So I'm going to. And to show you that in a second. Now let me see. Is this look like the same person is. Pretty similar. 

So this is her.  

And yeah, you can see a condo looks the same. So a little bit wrong though. I think to be honest and look, she's wearing the same sequent dress. I didn't want it to be wearing that. I want it to be. In a dentist office. So we'll see if we can address that.  All right. How do I do it? 

What I do, my trick is I want to pan out. I'm going to click pan.  Submit.  And that's going to add some extra bits to the right-hand side.  And we're going to do that twice in order to get a two to one aspect ratio.  

And you can see here that we've added some extra background side.  

And then we need to upscale one of them. Does really matter which one.  And the moon to pan that, again.  

When you get here is basically. Enough space for two of the same character.  

Okay, let me just upscale one of these.  I'm just doing the one with the least amount of noise and the. Background. Okay. So now we have our character. We have, a consistent background on this side. All right. What we can do now is we can do a very region.  



And this is where the magic happens. 

So you can do this actually with any AI tool that offers in painting. So we're just going to select.  This sort of. Basically cutting out this part of the image. So the right-hand side of the image. And instead of. Doing one image with a background on the right hand side, are we going to change it? 

So we're going to say. Sorry. Two images.  Is side by side. The same.  



And you say At an 1975. Priority.  

And then we're going to say.  

This.  Hey. Your sweater.  

Alright.  

And then we're going to get rid of this stuff. We don't need that.  All right. And we've got the aspect ratio two to one.  So let's see if that works and this is not always consistent by the way. Sometimes it does go a little bit crazy, but that should give us the best chance of success. So how does this work? When you're in painting you're basically erasing part of the image and then prompting it for what you want. They image new part of the image to be well. The. Here we go. 

So what we're doing is we're taking instead of this, a wide angle, A shot. We're cutting it in half, or we're saying it's just two pictures of the same. Person right.  

And you can see here that, okay. It didn't get the dentist office saying properly, but it is the same person, right? It's very consistent, which is good. And she is wearing a blue sweater. So that is pretty good. And now all of these have our eyes closed. So one of the things I'm going to try now is I can go back to a very region. Did I say one it's still cut out. You're saying let's just try. The. She's Chinese five for potty left. At wearing the blue sweat 

Staring straight at the camera.  

Alright.  

All right, the, see if that fixes the problem, you're back into any normal kind of prompting techniques that you're going to use to do this. But the key is that. We're in painting. So there's two. Pictures of the same character now. The reason why this is useful is now we can basically cut out. If we drop this into Figma or Photoshop or whatever, We can cut out the different images that we want. 

So we can do this a bunch of times and then get Maybe 10 20 images that the same woman. And there's a few different things. We can do that, but one is we can. Map out all the different scenarios that we need her to be in. But the more interesting thing is that you could then use that as training data to train your own stable diffusion model on this specific character. 

And that's something I've done. In the past as well. You can see that if some of these are better than others you might take a bit of an iterative process here. Like maybe you need to get her with her eyes opened first, keep the sequined dress and then try and work on. Maybe a different background and they'll try and work on a different outfit. And it is a bit of an issue that you're active process, but the really cool thing here is that now you have a method for getting to different. Perspectives or two different behaviors or situations from the same character. 

And that character is consistent. And this works really well. Now the other thing actually I've found.  In general is that you can't do this with uploaded images. There is a little bit of a hack. They have this blend functionality. And if you blend two images together, they're similar. 

You do get a generated version in the same style. If you did need to hack it, I don't know how much longer that. But if he didn't need to hack it and wanted to get a character that you didn't generate that as like an upload character, then you could do that. But for now they've disabled. The ability to in paint, uploaded images. But yeah, hopefully that's helpful for you guys. 

And it gives you a lot of different opportunities to create more interesting character development in your stories.

What is the purpose of using the "C dot E F character reference" parameter in the tutorial?

What technique does the tutorial suggest using instead of the proprietary feature to achieve consistent characters?

How does in painting work in maintaining consistency in characters?

How can the generated images be further utilized in character development?

What is a limitation of the in painting technique mentioned in the tutorial?

There is a random element to diffusion models, so you get a different result every time you run the same prompt, making it hard to keep characters in a story consistent.

Vexpower Learning Certificate of Completion

Congratulations Rhys Fisher 💪