Bit early for it, but it’s supposed to drop well below freezing tonight, and then snow for a while on Monday.

(Update: I thought they'd make a nice Christmas card...)

Soft logistics

I guess it’ll be a few more days before I find out how well Amazon packaged the squishably-soft silicone item compared to the robust boxing of the two glass items. Because it went back to the local depot Friday afternoon, hasn’t been updated since, and Amazon added their automatic five-day extension before I can even try to get my money back and order another one.

(if it does show up, there’s no guarantee it’s the same one that went out the first time; they’ve reused tracking numbers before)

Resting Waifus

I wanted to refine and upscale the 162 retro-sf waifu wallpapers I made a while back, but I definitely did not want to drag each image into the SwarmUI window, click “reuse parameters”, click “direct apply” on the preset containing the new settings, and then click “Generate”. That’s how I’ve been doing it for small sets, but it’s tedious and annoying, so I wanted to script it: extract the original parameters from the PNG as JSON, add a few new fields, then send a REST call to the SwarmUI server and download the results.

I knocked it together in Bash using exiftool, jq, and curl, and it worked great… unless the image was made with a LoRA. Which almost all of my wall-waifus are. I banged my head against the keyboard for a while before giving up and posting a stripped-down repeat-by to the Discord. Within half an hour, the developer had responded: the JSON the app stores in an image’s metadata is not the format used by the REST API; you can’t just round-trip it. (he acknowledges this is a should-really-fix-sometime issue)

Specifically, fields that are returned as arrays must be sent as comma-separated strings:

# extracted metadata
...
"loras": [
  "Qwen/Pin-up_Girl_-_CE_-_V01e_-_Qwen",
  "Qwen/Qwen_Sex-_Nudes-_Other_Fun_Stuff_-SNOFS-_-_v1-1"
],
"loraweights": [
  "1",
  "0.5"
],

# /API/GenerateText2Image
...
"loras": "Qwen/Pin-up_Girl_-_CE_-_V01e_-_Qwen,Qwen/Qwen_Sex-_Nudes-_Other_Fun_Stuff_-SNOFS-_-_v1-1",
"loraweights": "1,0.5",

Fortunately, jq can do this for you as a one-liner:

JSON=$(jq -c '.loras |= join(",")' <<<"$JSON")
JSON=$(jq -c '.loraweights |= join(",")' <<<"$JSON")

This is not the only underdocumented aspect of the REST API; there are very few examples, none of which give comprehensive lists of valid parameters or complete output. If the anime drought continues, I may pull down a copy of the SwarmUI repo and send patches for the API docs.

I’ll add the script to my Github repo once I finish tinkering with options. I’ve already added an option for the variation-related params, since I’ve had to use that feature a lot when an almost perfect pic is ruined by bizarre anatomical malfunctions. I think I also want to try re-rendering at a larger size instead of scaling as much (1080x1920 render + 2x upscale instead of 576x1024 + 3.75x), in the hopes of reducing finger and toe damage. Newer models can cope with the higher initial resolution. (additional options will wait until I’ve converted it to Python; for a quick hack, Bash is fine, but it’s clunky at handling JSON and REST calls)

X: The Algorithm

It’s been pretty bad in the past, filling my “for you” feed with assorted scams, engagement farmers, and hate-filled Leftist activists, but at the moment, it seems to be pretty well centered around the type of things posted by the 24 accounts I follow:

• 6 Japanese models/actresses
• 4 artists (2 Japanese)
• 4 novelists (1 who fled to Bluesky but never deleted his account)
• 2 contrarians
• 2 friends
• 2 anime series
• 2 waifu-posters (long idle)
• 1 cat-poster
• 1 app

Basically I get anime pics, RPG pics, cat pics, random snark and memes, and Japanese women in bikinis. This I can scroll for a while.

Truth in advertising, unfortunately

I was throwing a bunch of leftovers into a big pot of slumgullion, and decided to add a can of chili. The label read Stout Beef Chili, and despite it being waaaaay down the list of ingredients, the smell of beer was overwhelming. It cooked out somewhat, but it’s still pretty strong when you open the container. Enough that I can’t imagine using the other can that I bought, and will likely pitch it.

This is the quality of ‘thinking’ that AI provides…

(actual country of origin for “Ackers Science” and “Ackers BORO3.3” products? China, of course)

MasterCook, Cooked

After months of relentlessly pushing their new GenAI-enhanced version and their cloud subscription service, the current owner of the venerable MasterCook recipe-management software has sold the rights to some entity called Cook’n, which appears to be junking the software and only bought the customer list. They’re honoring subscriptions, but charging $10 to migrate you to their cloud.

Is their product comparable? No idea; I’ve seen so many products advertise MasterCook compatibility without actually implementing the full feature set that I gave up years ago.

Fulfillment Roulette

I ordered three things from Amazon. One is made of squishably soft silicone, the other two are made from borosilicate glass. Each one has its own tracking number, suggesting they did not combine them into one box, despite me checking the “take your time” button on shipping.

Now, which one will have the sturdiest package when it arrives tonight?

(I didn’t ask for Ricotta to serve dubious concoctions in champagne flutes, but I guess I didn’t not ask for it, either; this is what happens when you fall back to a model with less-capable parsing because it has the anime LoRAs you need for specific characters)

🎶 “One of these things is not like the other…” 🎶

The Oregon Highlander

I saw the name of this illegal alien convicted sex offender who was advising Oregon on healthcare, and my first thought was not “yeah, that tracks”, but rather:

I guess being chief metallurgist to King Charles V of Spain doesn’t pay what it used to.

(“there can be only one!”)

Somebody didn’t get the memo…

😁

Experimental girl-swapping

The Flux models have plasticky skin, fewer trained art styles, and better-than-SDXL-but-not-by-much prompting. Qwen Image has excellent prompting and posing, but a strong tendency to converge on a handful of styles, locations, and faces. One of the more recent Flux models is Krea, which is supposed to be heavily trained on photographic and art styles. The full version is also 22 GB, so I wasn’t sure how well it would perform on my 24 GB RTX 4090 at all.

It was surprisingly quick, and it did style the images more than Qwen or standard Flux, but it definitely didn’t have the kind of LLM-based prompting that makes Qwen stand out.

So I crossed my fingers and set things up so that Qwen generated a 36-step 576x1024 image and then handed it off to Krea for 24 steps of refining and upscaling to 4K. Performance was quite good, but the results were… rough. One gal had a second face growing out of her ankle, another had an eye for a nipple, another had blue feet and something hideous growing out of her mutated hand, etc, etc.

TL/DR: I have yet to find a refine-only model that works well with Qwen as its base; the ones that don’t produce awful images produce low-resolution ones. So that idea was a bust, and not even a bouncy one.

(I need models that are… rock solid)

The “self-portraits” I’ve posted recently were all done with prompts starting with “slightly-cartoonish illustration” to set the style. I also used this phrasing for the Diablo 4 barbarian illustration below them, which isn’t cartoonish at all.

So why is it that the moment I start to describe them in detail, to add variety, my pinup gals go full-bore big-eye anime style? Either 2D or Frozen-style 3D?

TL/DR: mentioning eyes at all, even just their color, is enough to do it. The expressive LLM-generated mood descriptions I’ve been experimenting with were also contributing (and creating some contradictory pose instructions, which I’d already made a note to fix), but all it takes to turn “slightly-cartoonish illustration of a woman cooking” into pop-eyed anime is adding “with blue eyes”.

The following images were all done with the same settings (Qwen Image, CFG 6.5, 42 steps, seed 1019441477):

A slightly-cartoonish illustration of a woman cooking:

A slightly-cartoonish illustration of a woman with blue eyes cooking:

more...

…and setting his clock back an hour this weekend. I had a helluva time getting Qwen Image to even get near Brian Blessed’s Vultan costume from Flash Gordon to dress my not-entirely-accurate avatar up for Halloween.

Claude started out with a spectacularly bad attempt to describe the costume:

When called on it, it “researched” the correct costume and at least got into the general ballpark, but still without getting a single component correct. I couldn’t find a decent high-resolution still to feed in as input, so I just hacked at the prompt until it looked like it was kitbashed from Thor cosplay leftovers.

“Trunk or treat” is an abomination

(You can’t change my mind)

Number of kids who came to my door? Fifteen.

Bags of candy left over? Less than fifteen. I figure my niece’s high school is going to need some donations.

Oddest thing was that a third of the kids showed up without bags for candy (the pros had pillowcases, which I respected). They were in costume, but they expected to receive one or two pieces and hand them off to an adult waiting at the curb. This doesn’t work at my house, where a double handful with my hands isn’t going to fit in theirs. Fortunately I’d been to the grocery and had half a dozen plastic bags to give away.

(“this will look terrific on Arato-senpai!”)

Gals on the right

I decided to take my retro-sf wildcards and use them to generate wide-format wallpaper for my gaming PC, which has for several years been using a photo of a penguin appearing to operate a DSLR camera (I think it came from a Bing wallpaper rotation).

It wasn’t obvious when I was generating tall images, but Qwen Image has a strong bias toward putting the subject dead center. You can tell it to put her on the right side of the image, but explicit instructions to “place the main subject on the left side of the image” are almost always ignored, if not reversed. Compositionally speaking, this is kind of frustrating. It’s possible, just quite difficult to arrange in the prompt.

Of course, this is the same model that thinks freckles are the size and color of pennies, and “faint scars” should be rendered as deep gaping wounds. Seriously, what was Alibaba using for training data, medical-school cadavers?

Competition!

For the past few years, providers have been promising to have high-speed fiber Internet service in my area. Cincinnati-based AltaFiber seemed to be expanding rapidly, then went quiet, but for the past few weeks there’s been major digging going on along the nearest main street near my house, and yesterday I spotted little flags and paint markers in the utility easement at the edge of my back yard, and sure enough, Friday afternoon some big equipment arrived and spent the afternoon pulling cable from one end of the street to the other, accompanied by little door cards announcing the imminent arrival of AT&T fiber.

Since it’s not available yet, they won’t give me the details of the package, but that’s okay, I don’t actually want it. What I want, and had wanted from Alta, was leverage to use in a call to my current provider. They offer new customers more speed for less money than the package I’m paying for.

Usually I pick up my niece after school one day a week, to help out with my brother’s schedule. This week they’re extra-busy dealing with nephew’s issues, so I’m picking her up at school, dropping her off at after-school sports, and then picking her up a few hours later.

The sports facility in question is shared with the University of Dayton’s teams. Which means that I get to see healthy college girls in sportswear while I wait to pick her up.

“No, no, I don’t mind showing up early to get a good parking spot.”

Today He Learned…

“Always mount a scratch monkey.” (classical reference, versus what really happened)

Reddit post on r/ClaudeAI, in which a user discovers that blindly letting GenAI run commands will quickly lead to disaster:

Claude: “I should have warned you and asked if you wanted to backup the data first before deleting the volume. That was a significant oversight on my part.”

(and that’s why I isolated Claude Code in a disposable virtual linux machine that only has access to copies of source trees, that get pushed to a server from outside the virtual; if I ever have it write something that talks to a database other than SQLite, that will be running in another disposable virtual machine)

Fapper’s Progress…

(that’s “FAbricated PinuP craftER”, of course)

TL/DR: I switched to tiled refining to get upscaled pics that look more like the ones I selected out of the big batches. I also used a different upscaler and left the step count at the original 37, because at higher steps, the upscaler and the LoRA interacted badly, creating mottled skin tones (some of which can be seen in the previously-posted set). As a bonus, total time to refine/upscale dropped from 10 minutes to 6.

SwarmUI only comes with a few usable upscalers, but it turns out there are a lot of them out there, both general-purpose and specialty, and side-by-side testing suggested that 8x_NMKD-Superscale was the best for my purposes. The various “4x” ones I had used successfully before were magnifying flaws in this LoRA.

(note that many upscalers are distributed as .pth files, which may contain arbitrary Python code; most communities have switched to distributing as .safetensors or .gguf, so if you download a scaler, do so from a reputable source)

Some of the seemingly-random changes come simply from increasing the step count. Higher step counts typically produce more detailed images, but not only are there diminishing returns, there’s always the chance it will randomly veer off in a new direction. A picture that looks good at 10 steps will usually look better at 20 or 30, but pushing it to 60 might replace the things that you originally liked.

For instance, here’s a looped slideshow of the same gal at odd step counts ranging from 5 to 99. I picked her based on how she looked at 37 steps (with multiple chains and a heart-shaped cutout over her stomach), but you can see that while some things are pretty stable, it never completely settles down. I’m hard-pressed to say which one is objectively the best step count to use, which is problematic when generating large batches.

Skipping the refining step completely produces terrible upscaled images, but the higher the percentage that the refiner gets, the less the LoRA’s style is preserved. The solution to that problem appears to be turning on “Refiner Do Tiling”, which means rendering the upscaled version in overlapping chunks and compositing them together. My first test of this at 60% preserved the style and added amazing detail to the outfit, without changing her face or pose. It added an extra joint to one of her knees, but lowering the refiner percentage back to 40% fixed that.

More tinkering soon. Something I haven’t tried yet is using a different model for the refining steps. A lot of people suggest creating the base image with Qwen to use its reliable posing and composition, and then refining with another high-end model to add diversity. This is guaranteed to produce significant changes in the final output, possibly removing what I liked in the first place. Swapping models in and out of VRAM is also likely to slow things down, potentially a lot. Worth a shot, though; SwarmUI is smart enough to partially offload models into system RAM, so it may not need to do complete swaps between base model and refiner.

Rescue Kittens

I rejected the original refine/upscale for this one because she grew extra fingers. She’s still got an extra on her right hand, but it’s not as visible as the left.

more...

Dear Rally’s,

I pulled up to the drive-through and placed my order with your automated system (not that I had a choice, once I was in line).

J: Number 1 combo, please.

A: would you like to upgrade that to a large for 40 cents? What’s your drink?

J: Yes. Coke Zero.

A: Does that complete your order?

J: No.

A: Okay, your total is $10.95.

J: I wasn’t done. Hello? Anybody there?

J gives up, pulls forward, pays, drives home; discovers it misheard every answer, giving me a medium combo with a regular Coke.

J scans QR code on receipt to give feedback, site never loads after repeated tries. Visits completely different URL on receipt, site never loads. Falls back to the “contact” form on the main web site, which, surprisingly, works.

Public deathmatch

I put the full genai-written project up on Github. Complete with the only Code Of Conduct I find acceptable.

I’ll probably create a grab-bag repo for the other little scripts I’m using for genai image stuff, including the ones I wrote myself, like a caveman.

(it’s been a while since I pushed anything to Github, and somehow my SSH key disappeared on their end, so I had to add it again)

Next genai coding project…

…is gallery-wall, another simple Python/Flask/JS app that lets you freely arrange a bunch of pictures on a virtual wall, using thumbnails embellished with frames and optional mats. It took quite a few passes to get drag-and-drop working correctly, and then I realized Windsurf had switched to a less-capable model than I used for the previous projects. Getting everything working took hours of back-and-forth, with at least one scolding in the middle where it went down a rat-hole insisting that there must be something caching an old version of the Javascript and CSS, when the root cause was incorrect z-ordering. This time even screenshots were only of limited use, and I had to bully it into completely ripping out the two modals and starting over from scratch. Which took several more tries.

Part of this is self-inflicted, since I’m insisting that all Javascript must be self-contained and not pulled in from Teh Interwebs. It’s not a “this wheel is better because I invented it” thing, it’s “I don’t need wheels that can transform into gears and work in combination with transaxles and run-flat tires but sometimes mine crypto on my laptop”. The current Javascript ecosystem is infested with malware and dependency hell, and I want no part of it.

Anyway, I’ll let it bake for a few days before releasing it.

(between Ikea, Michaels, and Amazon, I have lots of simple frames waiting to be filled with the output of my new photo printer; I had to shop around because most common matted frames do not fit the 2:3 aspect ratio used in full-frame sensors, and I don’t want to crop everything; I like the clean look of the Ikea LOMVIKEN frames, but they’re only available in 5x7, 8x8, 8x10, 12x16, and a few larger sizes I can’t print (RÖDALM is too deep, FISKBO is too cheap-looking))

Apparently OpenAI wants subscribers back…

…because they’re promising porn in ChatGPT. For “verified adults”, which probably means something more than “I have a credit card and can pay you”. Also, the “erotica” is still quite likely to be censored, with rules changing constantly as journolistos write “look what I got!” clickbait articles.

They’re also promising to re-enable touchy-feely personalities while pretending that’s not what caused all the “AIddiction” clickbait articles in the first place…

I’m guessing they’ll stick to chat at first, and not loosen the restrictions on image-generation at the same time.

(I’ll likely wait until Spring before giving them another chance; Altman is to Steve Jobs as Bob Guccione was to Hugh Hefner)

“Genai’s strange obsession was…”

“…for certain vegetables and fruits”. The expanded categorized wildcards have produced some violent color and style clashes, which I expected. I can clean up the colors by using variables in the premade costume recipes, but for the style clashes, I may throw the YAML back to Claude and tell it to split each category into “formal”, “casual”, “sporty”, “loungewear”, etc, to reduce the frequency of combat boots with cocktail dresses and fuzzy slippers with jeans.

I’ll need to hand-edit the color list, because while smoke, pearl, porcelain, oatmeal, stone, shadow, snow, rust, clover, terracotta, salmon, mustard, flamingo, bubblegum, brick, jade, olive, avocado, fern, and eggplant are valid color words, they are not safe in the hands of an over-literal diffusion-based image-generator.

Yes, I got literal “avocado shoes”.

For most of them I can probably get away with just appending “-colored”, but I’ll have to test. I’ll need to clean up the materials, too, since “duck cloth” isn’t the only one that produced unexpected results.

With the SF set, you can handwave away many of the fashion disasters by remembering the future fashions in the Seventies Buck Rogers TV series, but there were still some standouts…

I didn’t refine and upscale these; mostly I’m just poking fun at the results, although there are a few that deserve enhancement.

more...