This is a refresh of my tutorial on [how to make realistic](https://www.reddit.com/r/StableDiffusion/comments/10yn8y7/lets_make_some_realistic_humans_tutorial/) people, and [how to make realistic people with SDXL](https://www.reddit.com/r/StableDiffusion/comments/16opi4h/lets_make_some_realistic_humans_now_with_sdxl/), and [let's make realistic humans with flux](https://www.reddit.com/r/StableDiffusion/comments/1enrkyz/lets_make_some_realistic_humans_now_with_flux/), but this time we will be using the Z Image model..
\*Special Note = imgpile currently has something going on, so many of the old SDXL images are unavailable. I'm working on shrinking them and hosting on imgur again\*
Since this is the fourth time around, I won't be going into detail for each area, and instead recommend loading up the original posts if needed.
**Setup*\*
These sample images were created locally using ComfyUI and the default workflow settings.
All images were generated at 1024x1536, with Euler, Simple and 9 steps, We will use the same seeds throughout the entire test, and, for the purpose of this tutorial, avoid cherry-picking our results to only show the best images.
**Prompt Differences*\*
Whenever possible, I try to use the simplest prompt for the task.
With SD 1.5 we were able to use:
`photo, woman, portrait, standing, young, age 30`
while with base SDXL we had to move over to using:
Positive prompt: `close-up dslr photo, young 30 year old woman, portrait, standing`
Negative prompt: `black and white`
Like Flux we will be using:
`close-up portrait photo of a standing 30 year old female with VARIABLE`
This prompt was selected to use natural language (avoid using commas and tags), and uses female/male instead of "woman/man," as man and woman aged the children, and turned men into women when certain clothing types were selected.
In a few areas the prompt will be modified slightly to be "wearing" instead of "with."
**Age Modification*\*
Since this is a new model, I thought I would give the age test a fresh start to determine if we needed to still use the "young" tag to prevent people from looking substantially older than they were. I feel like model does the best at the age test I've of any model:
[Full age test](https://imgur.com/a/EN95Qqh)
[30 year old woman and man](https://imgur.com/Ax6wu7m) Flux
[30 year old woman and man](https://imgur.com/gdHtIgg) SDXL
**Hair Color Modifications*\*
For this section we will still use the Fischer-Saller hair color scale and this prompt:
[Hair Color Examples](https://imgur.com/a/u4aBy69) Z-Image
[Hair Color Examples](https://imgur.com/46QHB22) Flux
[Hair Color Examples](https://imgur.com/ZjXmuae) SDXL
[Hair Color Examples](https://i.imgur.com/kAV7vYD.jpg) SD1.5
Rainbow hair colors:
[Rainbow Color Hair Examples](https://imgur.com/a/4wDHb0I) Z-Image
[Rainbow Color Hair Examples](https://imgur.com/9ezSDut) Flux
[Rainbow Color Hair Examples](https://imgur.com/jmARsaL) SDXL
[Rainbow Color Hair Examples](https://i.imgur.com/c6URMAE.jpg) SD1.5
**Hair Style Modifications*\*
Continuing to modify the hair, we will use the list of hair style types directly from my previous character creation tutorial. These are based on boorutags, and as such can impart unwanted styles to an image.
Z-Image and Flux could possibly be better served with descriptive terminology to describe the hair, but many of these names are common enough that I expected them to work:
[Hair Style Examples](https://imgur.com/a/UZTuu6g) Z-Image
[Hair Style Examples Part 1](https://imgur.com/Nz4uaRf) Flux
[Hair Style Examples Part 2](https://imgur.com/NV6cHbh) Flux
[Hair Style Examples](https://imgpile.com/images/DRp0qa.png) SDXL
[Hair Style Examples](https://i.imgur.com/EAsLECj.jpg) SD1.5
**Face Shapes*\*
Directly tying in with hair styles are face shapes, because in theory, you should select a hairstyle that best matches your face shape. For this we will use the face shapes that Cosmopolitan Magazine calls out:
[Face Shape Examples](https://imgur.com/a/SVipslt) Z-Image
[Face Shape Examples](https://imgur.com/bu8Dx6w) Flux
[Face Shape Examples](https://imgur.com/3gdkPr8) SDXL
[Face Shape Examples](https://i.imgur.com/scKIAmv.jpg) SD1.5
**Eye Modifications*\*
For eyes we will use the most common eye shapes:
[Eye Shape Examples](https://imgur.com/a/ertUKmb) Z-Image
[Eye Shape Examples](https://imgur.com/AvBoFqg) Flux
[Eye Shape Examples](https://imgur.com/um5kQgR) SDXL
[Eye Shape Examples](https://i.imgur.com/BQObxmu.jpg) SD1.5
Next is natural eye colors, as defined by the Martin-Schultz scale:
[Eye Color Examples](https://imgur.com/a/nMnbLeV) Z-Image
[Eye Color Examples](https://imgur.com/Z3I4sLI) Flux
[Eye Color Examples](https://imgur.com/gjs7Gji) SDXL
[Eye Color Examples](https://i.imgur.com/xE50nZG.jpg) SD1.5
It's a toss up if I'd include or exclude eye color with Z-Image. With Flux the changes are substantially more subtle than with SDXL or SD1.5, and may actually be okay to include in your prompts now. However, it may just be best to use a hair color, or a skin tone, and allow the eyes to naturally generate whatever color they will.
Last for the eyes is the eyebrow category, which once again was driven by a Cosmopolitan list:
[Eyebrow Examples](https://imgur.com/a/0VBNxxd) Z-Image
[Eyebrow Examples](https://imgur.com/HDWB8n6) Flux
[Eyebrow Examples](https://imgur.com/cP72TX3) SDXL
[Eyebrow Examples](https://i.imgur.com/gN56vyj.jpg) SD1.5
**Nose Modifications*\*
Next up is different noses types, which I pulled off of a few plastic surgery websites.
[Nose shape examples](https://imgur.com/a/uM1VB9H) Z-Image
[Nose shape examples](https://imgur.com/zgR2qvi) Flux
[Nose shape examples](https://imgur.com/IJRRSML) SDXL
[Nose shape examples](https://i.imgur.com/yWCEVia.jpg) SD1.5
Flux is far too literal on some of these.
**Lip Shapes*\*
Returning to the definitive source for body information, Cosmo, I pulled together a list of lip types.
[Lip Shape Examples](https://imgur.com/a/fy3H59V) Z-Image
[Lip Shape Examples](https://imgur.com/Jq2uZuW) Flux
[Lip Shape Examples](https://imgur.com/xR57w2W) SDXL
[Lip Shape Examples](https://i.imgur.com/48LfTxX.jpg) SD1.5
**Ear Shapes*\*
For ears I used a blend of Wikipedia and plastic surgery sites to get an idea of the types of ears that exist.
[Ear Shape Examples](https://imgur.com/a/1CblH84) Z-Image
[Ear Shape Examples](https://imgur.com/QjaOd4k) Flux
[Ear Shape Examples](https://imgur.com/N7nXuKu) SDXL
[Ear Shape Examples](https://i.imgur.com/npRldrf.jpg) SD1.5
Similar to noses, some of these are comical or have taken on a fantasy spin. I wouldn't recommend including these for most realistic human prompts.
**Skin Color Variations*\*
Skin color options were determined by the terms used in the Fitzpatrick Scale that groups tones into 6 major types based on the density of epidermal melanin and the risk of skin cancer.
[Skin Color Variation Examples](https://imgur.com/a/nvWREWU) Z-Image
[Skin Color Variation Examples](https://imgur.com/5rAAYu1) Flux
[Skin Color Variation Examples](https://imgur.com/DQzvGyk) SDXL
[Skin Color Variation Examples](https://imgpile.com/images/DRp35R.png) SD1.5
**Continent Variations*\*
I ran the default prompt using each continent as a modifier:
Continent Variation Examples: Z-Image maybe added later.
[Continent Variation Examples](https://imgur.com/LQcjxHz) Flux
[Continent Variation Examples](https://imgur.com/ycg0g2J) SDXL
[Continent Variation Examples](https://i.imgur.com/wAmhvAn.jpg) SD1.5
**Country Variations*\*
After the continents, I moved on to using each country as example, with a list of countries provided by Wikipedia. I struggled with choosing the adjective form, versus the demonym, before finally settling on adjective - which may very well be the incorrect way to go about it.
I am no expert on each country in the world, and know that much diversity exists in each location, so I can't speak to how well the images truly represent the area. Although interesting to look at, I would strongly caution against using these and and saying, "I made a person from X country."
Also, since the SDXL photos were so much larger, I had to split each group in half.
**Fair warning - some of these images may have nipples**.
[Country Variation Examples](https://imgur.com/a/8byfcjL) Z-Image
[Country Variation Examples 1](https://imgpile.com/images/DRpSIN.png) SDXL
[Country Variation Examples 2](https://imgpile.com/images/DRpZKW.png) SDXL
[Country Variation Examples 3](https://imgpile.com/images/DRpa2P.png) SDXL
[Country Variation Examples 4](https://imgpile.com/images/DRSn3j.png) SDXL
[Country Variation Examples 5](https://imgpile.com/images/DRSs6E.png) SDXL
[Country Variation Examples 6](https://imgpile.com/images/DRSfRr.png) SDXL
[Country Variation Examples 7](https://imgpile.com/images/DRSlfR.png) SDXL
[Country Variation Examples 8](https://imgpile.com/images/DRSmBg.png) SDXL
[Country Variation Examples 9](https://imgpile.com/images/DRSzuc.png) SDXL
[Country Variation Examples 10](https://imgpile.com/images/DRS8JN.png) SDXL
[Country Variation Examples 11](https://imgpile.com/images/DRS2Ex.png) SDXL
[Country Variation Examples 12](https://imgpile.com/images/DRSqVL.png) SDXL
[Country Variation Examples 13](https://imgpile.com/images/DRSLRj.png) SDXL
[Country Variation Examples 1](https://i.imgur.com/mRuGuCn.jpg) SD1.5
[Country Variation Examples 2](https://i.imgur.com/SvxVgGO.jpg) SD1.5
[Country Variation Examples 3](https://i.imgur.com/2nKJbPA.jpg) SD1.5
[Country Variation Examples 4](https://i.imgur.com/YUTN6fq.jpg) SD1.5
[Country Variation Examples 5](https://i.imgur.com/6Bferw7.jpg) SD1.5
[Country Variation Examples 6](https://i.imgur.com/Zur9y8q.jpg) SD1.5
[Country Variation Examples 7](https://i.imgur.com/64l8Ns2.jpg) SD1.5
**Weights and Body Shapes*\*
To try and adjust weights I added the variable words to the default prompt.
[Weight and Body Shape Examples](https://imgur.com/a/zPyLcGo) Z-Image
[Weight and Body Shape Examples](https://imgur.com/TniiS2t) Flux
[Weight and Body Shape Examples](https://imgpile.com/images/DRSWuS.png) SDXL
[Weight and Body Shape Examples](https://i.imgur.com/0Co38Cx.jpg) SD1.5
Flux is surprisingly not that great at these. It may again be down to the fact that we are better served by longer natural word prompts, but some of these terms are pretty common and I would have expected them to work a bit better.
**Height Modification*\*
Learning my lesson from trials with SD1.5, I skipped over attempting to use a number and switched straight to common text values. With Z-Image short just and tall kind of work.
[Heights Examples](https://imgur.com/a/qLy2RVz) Z-Image
[Heights Examples](https://imgur.com/undefined) Flux
[Weighted Heights Examples](https://imgur.com/KlOysya) SDXL
[Weighted Heights Examples](https://i.imgur.com/WLZDrQf.jpg) SD1.5
I'm not sure how weighting works with Z-image, but I did give it a try. With SDXL, there doesn't appear to be much of a difference with the weighted versions. You are either short, or tall, with not much difference in-between. The best change would probably be the woman in the pink shirt, as she does at least get a longer neck and raises in frame the taller she is.
**General Appearance*\*
Although I said we were trying to make average looking folks, I thought it would be nice to do some general appearance modifications, ranging from "gorgeous" to "grotesque." These examples were found by using a thesauruses and looking for synonyms for both, "pretty," and, "ugly."
[General Appearance Examples](https://imgur.com/a/mtTPunB) Z-Image
[General Appearance Examples Part 1](https://imgur.com/Nae51Vp) Flux
[General Appearance Examples](https://imgur.com/1bW1Wp8) SDXL
[General Appearance Examples](https://i.imgur.com/9HZq3WU.jpg) SD1.5
**Emotions*\*
For emotions I used ChatGPT and asked it to produce a list of of human emotions, formatted as CSV without breaks.
[Emotion examples](https://imgur.com/a/092axzw) Z-Image
[Emotion examples 1](https://imgur.com/WY6eZ9a) Flux
[Emotion examples 2](https://imgur.com/bQ9eyyD) Flux
[Emotion examples 1](https://imgpile.com/images/DRSQj3.png) SDXL
[Emotion examples 2](https://imgpile.com/images/DRS3Xw.png) SDXL
[Emotion examples](https://i.imgur.com/7w4sXTH.jpg) SD1.5
**Clothing Options*\*
By far, I think clothing is one of my favorite areas to play around with as, was probably evident in my [clothes modification tutorial](https://www.reddit.com/r/StableDiffusion/comments/1ch5zcc/1000_clothing_option_ideas_sorted_by_category/) (Z-image version of this tutorial to come sometime).
Rather than rehash what I've covered in that tutorial, I'd like to instead focus on on an easy method I've come up with to make clothing more interesting when you don't want to craft out an intricate prompt.
To start off with let's take some plain clothing prompts:
[Basic Clothing Options Examples](https://imgur.com/a/1JEkj3w) Z-image
[Basic Clothing Options Examples](https://imgur.com/IaGGAJx) Flux
[Basic Clothing Options Examples](https://imgur.com/SAciciy) SDXL
[Basic Clothing Options Examples](https://i.imgur.com/vde6ZEn.jpg) SD1.5
To kick things up a notch though, this is a case where I'm going to go against my normal rules about keyword stuffing by suggesting that you instead copy and paste some items names out of Amazon.
So, head on over to Amazon and type in any sort of clothing word you want, such as "women's jacket," and then check out the horrible titles that they give their products. Take that garbage string, minus the brand, and then paste it into your prompt.
[Word Vomit Prompt Clothing Option Examples](https://imgur.com/a/pE2tdGX) Z-Image
[Word Vomit Prompt Clothing Option Examples](https://imgur.com/1NYLbWd) Flux
[Word Vomit Prompt Clothing Option Examples](https://imgur.com/oQ7ndYr) SDXL
[Word Vomit Prompt Clothing Option Examples](https://i.imgur.com/iN9GOig.jpg) SD1.5
Look a that - way more interesting, and in some cases more accurate, plus the added bonus of Z-image, Flux and SDXL doing an incredibly good job of matching the expectations for patterns.
My theory on this one is that either we have models trained on Amazon products, or Amazon products have AI generated names. Either way it seems to have a positive effect.
One thing to keep in mind though is that certain products will drastically shift the composition of your photo - such as pants cutting the image to a lower torso focus instead.
For the fun of it, I've added in some popular Halloween costumes:
[Halloween Costume Examples](https://imgur.com/a/wL09qgZ) Z-Image
[Halloween Costume Examples](https://imgur.com/BAztCQz) Flux
[Halloween Costume Examples](https://imgur.com/AqgiZkX) SDXL
[Halloween Costume Examples](https://i.imgur.com/Bi5RdVq.jpg) SD1.5
**Genetic Disorders*\*
With the goal of creating real people, I decided to include the most common genetic disorders that have a physically visible component.
[Genetic Disorder Examples](https://imgur.com/a/yXEMsa2) Z-Image
[Genetic Disorder Examples](https://imgur.com/tbhju8O) Flux
[Genetic Disorder Examples](https://imgur.com/aC8XRqx) SDXL
[Genetic Disorder Examples](https://i.imgur.com/9tehqWv.jpg) SD1.5
I am in no way an expert on any of these disorders, and can't really comment on accuracy, but SDX seems to not match the sample images as well for some of these, and Flux is even worse. Z-image doesn't seem to match well either on many of these.
**Facial Piercing Options*\*
Even with Z-Image, piercing still suck. You would be better served inpainting a piercing.
[Facial Piercing Examples](https://imgur.com/a/uR1IMrq) Z-Image
[Facial Piercing Examples](https://imgur.com/Ciuh0MY) Flux
[Facial Piercing Examples](https://imgur.com/C9fHBkS) SDXL
[Facial Piercing Examples](https://i.imgur.com/gUqkZPY.jpg) SD1.5
**Facial Features / Blemishes*\*
I decided to add a wide variety of different facial features and blemishes. Z-image is hit or miss. Maybe some of these would do better on a different seed though.
[Facial Feature Examples](https://imgur.com/a/sVNQxw5) Z-Image
[Facial Feature Examples](https://imgur.com/05fHCVs) Flux
[Facial Feature Examples](https://imgpile.com/images/DRSZFk.png) SDXL
[Facial Feature Forward Variable Placement Examples](https://imgpile.com/images/DRSe7M.png) SDXL
[Facial Feature Examples](https://i.imgur.com/Tc8YpXS.jpg) SD1.5
**Through the Years*\*
Just like before I thought it would be fun to try out the model would look like in each of the decades.
[Through the Years Examples](https://imgur.com/a/R13gz11) Z-Image
[Through the Years Examples](https://imgur.com/LoaMzgn) Flux
[Through the Years Examples](https://imgur.com/LtyflGV) SDXL
[Through the Years Examples](https://i.imgur.com/V482oMw.jpg) SD1.5
The 15 yo boy jumpscared me lol Specifically, in the first image
There are a few places where the results don't match anything around them and for no good reason.
Not sure why you’d say that about Jim Halpert from the Office
Jim Halpert is a fictional character. That's the guy who plays him, John Krasinski.
Here is one of the images that should get you the workflow I used for the xy grids. Forewarned that is a mess though:
https://preview.redd.it/q1tdx3tlj26g1.png?width=5150&format=png&auto=webp&s=e079d071cda531fc0777823f55b1ea6bb5888bdd
I hate reddit image I can't even scroll through it. And Imgur is currently slow af (around 700kb/s) for some reason.
Braided bangs and dude turns black
Thanks for posting this. Also lol @ hooded eyes.
“Long nose” 😂🤣😂
LOL at "Guernsey"
My apologies to the proud people of Guernsey.
Thanks for posting this comprehensive collection. It's interesting to see that for simple prompts like these, SDXL and even SD 1.5 still can fare quite well.
Wow! Z-Image blows FLUX out of the water in the emotions field. I mean Z-Image is not perfect but it's much better that FLUX in these examples. I'm guessing FLUX 2 has to be a lot better, right?.
I actually haven't tried Flux 2. Maybe once I build out a faster and more scalable xy grid process I'll give it a try.
SDXL with Lora is absolutely capable of making good images with simple prompts but it really struggles with more complex and specific stuff. I’m hoping Lora’s get Z-image to be as constistent
[deleted]
fixed - thanks
It is trying to get it to not do the correct race or nationality that is often the problem. As we see here where it only randomly switches with a few hair and eye color prompts. It knows what they look like, but it is very reluctant to let go of the Asian bias unless you describe the person (or sometimes scene) in some detail.
This made me just aware that I don't want to get old. Lol
That bias of the Asian, female model look with too clean, slightly over-exposed face is just too strong. It's jarring when the prompt is able guide away from it and suddenly generates a real-looking human instead.
It's really detrimental to more subtle prompts that just get lost in this huge hole in latent space that is the "Asian female model from the magazine cover".
https://preview.redd.it/k3j2b6wdk36g1.png?width=1080&format=png&auto=webp&s=e760fcd3162ea1ff2ebb8b24eaf8db58c9c0ec9c
I made this on Z-image with my own trained lora, does anyone has solutions about the death stare expression? I've been tried some expressions prompt but ended up with those no-soul expression. should I re-train the lora with expressions dataset images? or there is other solutions?
Yeah, if you didn't include any smiling ones, then this will be the go-to look :)
https://preview.redd.it/090hy3zgv36g1.png?width=1220&format=png&auto=webp&s=937275fa77a7def9d0e21df9f57424435ac1c9a3
actually it does fine with smiling
Problem solved!
Was waiting for blue and green hair
Good stuff. I am saving this
This is great! Thanks
Merci pour le partage c'est super intéressant
Workflow?
It is one of the comments below. I think there is a way to see the original image and you can drag it in to comfy. Because I have so many nested samplers it is too big for regular pastebin. If you look at it though it really is just the default z-image workflow with a setup to handle XY plotting.
I think this works: https://www.reddit.com/media?url=https%3A%2F%2Fi.redd.it%2Flets-make-some-realistic-humans-now-with-z-image-tutorial-v0-q1tdx3tlj26g1.png%3Fauto%3Dwebp%26s%3D1641a5640f2d71dcc6046fac9c1dea216e108cdf
So it really can't do dark skin. I thought it was a problem with my prompts.
It can perflectly do dark skin.
I already made african, indian, native american, polynesian and all sort of metis from diverse mixed ethnicities with darker skin than west people.
Would you mind sharing your prompt for getting dark skin, such as those who live in South Sudan? This is the best I can do, and I hate the idea of using 'black paint skin" in a prompt.
https://preview.redd.it/4mnh5ix8j76g1.png?width=3072&format=png&auto=webp&s=6766d15259257aa30fd10070ad59caacdd0e872e
Use the name of the countries :)
You must be specific with Zimage.
I tried that in the link to the countries, but it still won't match the very dark skin tone that can be found in Sudan.
Make your own LoRa is this very dark tone of Sudan is so important for you :)
Zimage turbo is only 6B parameters, than 2 time less than Flux.1dev, so don't expect to achieve all the request with only the turbo model.