The goal here is to show, using real generations, what you actually get in the end when the entire process is done correctly — from face and body creation to the first photoshoots.
This step is important because it answers the main question:
“Okay, I’ve done all of this — what’s next? And does it really work?”
Starting Point: The Base Image of the Model
We begin with the core image that was created after:
combining face and body (face swap),
upscaling,
final proportion checks.
This is the first canonical image of the model. It:
already looks realistic,
is fully consistent,
can be used as an input reference for any further tools.
This exact image is what we sent into the Carousel.
Carousel as the First Content Multiplier
The examples show that:
only one single image was uploaded to the Carousel,
and the output was a full photoset with multiple angles.
The key points:
the body remained the same,
breast size stayed consistent,
proportions did not drift,
the face remained recognizable across all images.
Even with just one source image, the result was stable. This immediately confirms that the model base was created correctly.
Why These Variations Matter for the Next Steps
An important practical note is emphasized:
If the next step were, for example, Image Editor or any other tool where accurate anatomy matters, we would:
use multiple variations from the Carousel,
select shots from above, from the side, and at angles,
helping the neural network better understand body and breast shape.
Even without this extra step, a single image already demonstrates strong consistency.
First Clothed Version: Fast Results Without Manual Tweaking
Next, we move on to the results of generating a clothed version of the model.
Several outfit variations in dresses were created — without complex prompts and without manual adjustments.
This is important because:
the model now has an official clothed version,
it can be used for Safe for Work content,
it works as an input for any future generations.
Mass Generation with Photoshoot: One Click, Dozens of Scenes
The next step is running Photoshoot across multiple categories at once:
lingerie,
BDSM,
other NSFW directions.
The examples demonstrate that:
generation is launched with a single click,
the output is a large set of scenes,
while the model itself remains the same.
This is the key scaling moment:
we no longer generate one image at a time — we generate content in batches.
Second Level of Scaling: Reusing Carousel Again
A logical next step is then demonstrated:
one of the already generated images is sent back into the Carousel.
As a result:
every image becomes a series,
every series can become input for new tools,
content variety grows exponentially, not linearly.
All of this happens without losing the model’s identity.
Using MyGeneration as an Asset Library
Special attention is given to the MyGeneration section:
all generations are saved,
you can return to them at any time,
any successful image can be:
sent to Carousel,
used in Image Editor,
taken as a reference for new scenes.
In practice, MyGeneration becomes a visual asset library for your model, not just a generation history.
Final Takeaway: What a Properly Built Model Actually Gives You
This lesson clearly demonstrates the main result of all previous work:
one properly built model →
one base image →
dozens of photosets →
hundreds of variations →
complete freedom to combine tools.
The key idea is this:
you are no longer dependent on a single image. You are managing a system where each generation strengthens the next.
By carefully observing the prompts used in the video examples and combining tools intelligently, you can produce nearly unlimited Safe for Work and Not Safe for Work content — without losing quality or character identity.
That is the goal of the entire architecture.