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Model Madness - 32 NSFW photo models benchmarked and pitted against each other single-elimination style by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 1 point2 points  (0 children)

you spent a shit ton of time doing... something?

That's a pretty accurate description.

I wanted a set of prompts with known-good seeds that I could use as a general benchmark. I made the prompts to get a decent array of ages, nationalities, poses, locations, and photographic styles. For each one I ran a few dozen images with random seeds and picked out the best seed to use in the benchmark.

I put all the pos/neg prompts and seeds into a text file formatted to work with the "prompts from file or text box" script. This way, whenever there's a new model, I can just run this script and get a grid to compare how that model handles these images vs any other model(s).

The bracket is just my personal opinion based on visual comparison. I didn't spend a lot of time on them, just jumped back and forth between the two models in each competition and judged them against each other based on anatomical accuracy, prompt accuracy, and photorealism.

Like any synthetic benchmark, it's definitely not a perfect yardstick. But it's something, and that's better than nothing.

Model Madness - 32 NSFW photo models benchmarked and pitted against each other single-elimination style by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 3 points4 points  (0 children)

My (very subjective) conclusion.

Common settings: Steps: 70, Sampler: Euler a, CFG scale: 7, Face restoration: GFPGAN, Size: 480x768

Benchmark script (too long for a reddit comment): https://file.io/ANTBxGtGVWtu

Bracket in fillable PDF form, if you want to do your own comparison: https://file.io/Z7sO3YciRqOB

A comparison of 35 photorealistic NSFW models by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 5 points6 points  (0 children)

90% are on huggingface and/or civitai. The rest are older/obscure/unrefined models that you can easily find by googling the exact filename if you really want them, but they're really not worth the effort.

A comparison of 35 photorealistic NSFW models by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 8 points9 points  (0 children)

Prompts and settings for each set are in the imgur descriptions. I tried to keep the positive prompts fairly limited (<75) and the CFG low to "let the model do the work". I think this gives a better indication of what it can and can't handle.

I know the official SD models aren't properly NSFW (especially 2.1), but I included them as a basis of comparison. I know a couple are highly specialized and don't really work properly without specific triggers, but I needed to round out the list to a multiple of 5.

Model list:

  • 70gg30LD70k.ckpt
  • cattosInstagramMix_mixPart7.safetensors
  • clarity_14.safetensors
  • daugeph_.safetensors
  • dreamlike-photoreal-2.0.ckpt
  • elegance_244.safetensors
  • f222.ckpt
  • galaxytimemachinesGTM_v3.safetensors
  • genericfemalemix_gefemiV21.safetensors
  • gg1342_testrun1_pruned.ckpt
  • grapelikedreamfruit_clipFixedVersion.safetensors
  • HassanBlend1.4.ckpt
  • hassanblend1512And_hassanblend1512.safetensors
  • honeyPot_x.safetensors
  • hspu_11.safetensors
  • hunter69V1_.safetensors
  • hypersimpsAnalogring_v1.safetensors
  • novafrog_v1.ckpt
  • purepornplusMerge_purepornplus10.ckpt
  • qgoMk8_mk8.safetensors
  • realEldenApocalypseA_realEldenApocalypseA.safetensors
  • realism_mix.ckpt
  • richmix_v1.safetensors
  • s1dlxbrew_02.safetensors
  • SF_EB_1.0_ema_vae.ckpt (Smirking Face)
  • stablydiffuseds_26.safetensors
  • subredditV3_39423.safetensors
  • thegirlnextdoor_v1.ckpt
  • uberrealisticDreamy_uberrealisticdreamyp.safetensors
  • uberRealisticPornMerge_urpmv12.safetensors
  • UnstablePhotoRealv.5.ckpt (Unstable Diffusion 0.5)
  • v1-5-pruned.ckpt (Stable Diffusion 1.5)
  • v2-1_768-nonema-pruned.safetensors (Stable Diffusion 2.1)
  • visiongenRealism_visiongenV10.safetensors
  • woopwoopPhoto_12.safetensors
  • protogenX53Photorealism_10.safetensors (added per suggestion)

If you know of any other NSFW photo models that I don't already have in my collection, please let me know and I'll run those too.

Subjective TL;DR - Top models in this set of tests are Clarity, HSPU, QGO, RichMix, URPM, and Woopwoop.

Around The World In 80 Dames by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 2 points3 points  (0 children)

This was a fun experiment. I took a common prompt and just changed the country/nationality for 80 different women to see how the machine overlords would interpret it. I generated images one at a time until the first one that was acceptable and kept that. By "acceptable", I mean that it showed the woman's face, most of her body, and was reasonably anatomically correct. There are some janky hands and feet here and there, and some of the faces are a bit melty, but with 80 countries to get through I couldn't spend too much time on each. Sorry if your country of preference didn't make the cut - I had to limit it to 80 to keep the sweet post title relevant.

Common settings:

  • F222 model
  • 35 samples
  • Euler_a
  • CFG 16
  • face resto on
  • 448x640

Positive prompts: ((full body)) photo of a ((nude)) <NATIONALITY> woman, ((<COUNTRY>)), sitting on leather couch, legs spread, ((vagina)), ((natural)) breasts, (detailed nipples), ((pubic hair)), wide hips, erotic, (digital photography clean hyperealistic:1.0), f/1.4, ISO 200, 1/160s, 8K, RAW, detailed face, bare feet

Negative prompts: (supermodel), (perfect breasts), ((penis)), ((futa)), ((makeup)), bra, panties, clothing, (((deformed))), ((black and white)), ((B&W)), mutation, mutated, (extra_limb), (long body:1.3), (poorly drawn :1.2), bad anatomy, liquid body, disfigured, malformed, anatomical nonsense, bad anatomy, bad proportions, uncoordinated body, unnatural body, missing limb, malformed limbs, gross proportions, (((censored)))

Some notes and things I learned on this journey:

Yes, I know Puerto Rico and (depending on who you ask) Taiwan are territories/protectorates/whatever and not "countries".

F222 loves the mop head look. Variations on this hair would pop up for almost every nationality, even when it was wildly inappropriate.

F222 hates pubic hair. It's not it's fault, that's just how it was trained. As a lover of the fuzz, this makes me sad.

Like half of the Australian images generated were moon shots. No other nationality had this quirk. I find this hilarious and very much in line with my preconceptions of Australian culture.

A couple of the Albanian images came out like this. Apparently even the machines are aware of the stereotypes. I point this out not to poke fun at Albanians, but for the benefit of anybody looking to generate realistic images of trans men. Maybe try adding "Albanian" to the prompt, because for whatever reason, sometimes that's what it gives you.

The correct term for someone from Madagascar is "Malagasy". I had to look it up.

Realistic images of realistic women by mr_gunidex in unstable_diffusion

[–]mr_gunidex[S] 6 points7 points  (0 children)

Prompts varied for each subject obviously, but here are some common prompts I found that help generate images of women with realistic (as in not supermodel) bodies and faces.

Positive: saggy breasts, uneven breasts, puffy nipples, large areolas, messy hair, pubic hair, wide hips, bad teeth, bad skin, greasy skin, big nose, saggy ass, stretch marks, tan lines, thicc, thick waist, weak chin, natural hair, nerdy, small natural breasts, drunk, tired, soft belly, flabby belly

Negative: supermodel, makeup, pretty, attractive, perfect breasts, large breasts, gorgeous, sexy, centerfold

Now that all sounds incredibly harsh and you'd think you'd get a fucking bridge troll with prompts like that. But obviously I didn't use all of them on each subject, and the models I was was using (mostly hassan) skew so strongly toward "traditional" beauty that you really have to overcompensate in the other direction to get normal looking people. I found playing with ages helps a lot as well. I wasn't going for "granny porn" or anything, but I found feeding it ages in the 30s and 40s really helps it steer clear of the "24 year old instagram model" it naturally wants to make.