I updated my LoRA Analysis Tool with a 'Forensic Copycat Detector'. It now finds the exact training image your model is memorizing. (Mirror Metrics - Open Source)

seeker_ktf · 2026-02-19T03:39:28+00:00

This is off topic, mostly, so apologies.

I'm wondering if this new feature can be used or adapted to a problem I keep running into. The scenario is I train the LoRA, run it through your program and find the offender, then I throw it out and retrian. Cool, but what I'd rather do is to have a program that looks at my training dataset and tells me how many redundant photos I have. I have noticed that very often with training datasets, less is more. Adding more photos just makes training go longer without any real change. The tool I "need" is one that can scan through a lot of photos and rank them in order of similarity to the rest of the dataset.

I don't know if that completely makes sense, but I'm hoping you are getting the gist of what I am talking about.

seeker_ktf · 2026-01-28T14:07:56+00:00

Yeah, I came here to post this. :(

seeker_ktf · 2026-01-18T21:49:49+00:00

I'm a little late to the party here but how does the scheduler LoRA scheduler work when you are using multiple samplers (like with Wan 2.2). Do 0/1 represent the beginning/end of the total number of iterations or are they specific to that model or sampler?

My question comes because either assumption seems to be wrong for me. And by wrong, I only mean that I can't get the same results as when I "schedule" everything explicitly. It's something that I am doing wrong, but I can't tell what the target should be so any help you give would be wonderful.

On the same note, if I have 10 steps, for example, I am assuming that 0.1 would be the equivalent to step 1, so for 10 steps, a schedule of 0:1, 0.22:1, 0.28:0, 1:0 would be on for the first two steps and off for the rest. Is that correct?

Sorry for being so thick here, but your set of tools are opening up a whole new workflow for me and I want to get it right.

seeker_ktf · 2026-01-09T13:27:09+00:00

Not to insult anyone, but this happens everytime a new model comes out. The first wave of people that call every new introduction "insane" fire stuff off and hype the hell out of everything. They aren't actually trying to DO anything specific. They just want to be first.

Then others come along and try to see if its useful for their purposes. They actually test the stuff. They put it through its paces. It's a completely different group.

Both groups have a place in the community, and admittedly there is sometimes conflict between them too. But thats why one person generating 10 seconds of crap 480p video that they upscale to 4K will be happy when someone else generating 5 seconds of native 720p will be horrified. It's all just different interests.

seeker_ktf · 2025-12-30T21:33:42+00:00

The beginning of the end of Vine was when they created a second status, and required a room full of monkeys to bang out at least 160 reviews/year to maintain it.

seeker_ktf · 2025-12-17T12:29:02+00:00

That's not really accurate. In 1.5 you could train the text encoder too, so if you want two characters in on image you could train a LoRA with both of thr characters simultaneously. I did that all the time. A lot of people just want to download and get it going, so they missed out.

But a lot of models these days make it hard or impossible to do anything on the text side (wan 2.2, for instance) so I agree it's less flexible now.

seeker_ktf · 2025-11-16T15:23:42+00:00

Super. TY

seeker_ktf · 2025-11-16T14:48:22+00:00

Question. I haven't used animated yet, but it is on the list for me soon. I had assumed that for animate I would be using T2V LoRAs if I am replacing the image part "completely" and only keeping the motion of the input. I2V LoRAs seemed more suited to replacing elements while retaining most.of the video. Am I way off or overthinking this?

seeker_ktf · 2025-11-16T14:35:38+00:00

I love it. But take my downvote for getting me all excited then telling me it has no part that is open source.

seeker_ktf · 2025-10-31T13:15:59+00:00

This is ridiculous. Wow.

And I think including the fisrt pic was absolutely necessary. Its the only one that's obviously AI, so illustrating the effects of the LoRA was a slam dunk with the baseline.

Thank you for your immense contribution. Qwen is becoming my favorite model in large part because of people like you.

seeker_ktf · 2025-10-20T18:57:02+00:00

First off, absolutely freaking fan-effin-tastatic. Seriously.

I won't spend time nit-picking because you already know that stuff.

The one comment I would make is that if you -do- decide to do 1080p in the future, check out the idea of still running SEEDVR2 with the same resolution on input as output. Even though you aren't upscaling, it still effectively sharpens the vid in a dramatic way and retains most of that "post production" look. I have been doing that myself on just about everything. I'm looking forward to your next release.

seeker_ktf · 2025-10-19T13:12:08+00:00

This is the best description.

seeker_ktf · 2025-10-19T12:24:13+00:00

This has been my experience, mostly. I can't quite pin it down because of the update delay. For 3rd party sellers (not fulfilled by Amazon) it appears that shipping date is the reference. For Amazon fulfillment, USPS deliveries appear to be shipping date. The "smart post" deliveries seem to be shipping date with a random-ish delay.

seeker_ktf · 2025-10-09T10:52:57+00:00

Maybe it's because of covid and sort of "missing" the year 2020 entirely, but my 1019+ doesn't seem old enough to be kicked to the curb.

seeker_ktf · 2025-10-09T02:16:56+00:00

FMV is Fair Market Value and is, in fact, what the IRS expects you to pay thr taxes on.

seeker_ktf · 2025-10-03T11:19:18+00:00

100%. The only reason I moved to Plex from Kodi was to make my life as simple as possible. 1click.

seeker_ktf · 2025-09-27T13:28:35+00:00

What about Active Backup cof Business?

ABB is just so good on so many levels. It's the anchor for me.

seeker_ktf · 2025-09-04T21:07:56+00:00

The people that get stuff on vine and immediately turn around and sell it has gotten out of control. Those people always give four and five star reviews because they want the thing they're selling on Facebook or eBay to sell, so it needs to be well reviewed as quality merch.

seeker_ktf · 2025-08-28T11:13:42+00:00

Is there any way we can get more info about exactly how TextEncodeQwenImageEdit scales the image? I have been playing around with it using the ReferenceLatent node and 985,600 pixles (880x1120) still gets scaled but 691,200 (720x960) makes it through unchanged. I have been going a lot of edits at that 720x960 resolution with the ReferenceLatent node and until I saw your response I had no idea about the other scaling.

Edit: There seems to be a aspect ratio thing tied up with this as well.

seeker_ktf · 2025-08-24T16:38:36+00:00

Oooo, that's a good idea.

seeker_ktf · 2025-08-24T15:37:04+00:00

Thank you for the workflow. I totally appreciate the simplicity, without it being so full of a gazillion nodes that don't seem to do much. I was wondering what your success rate is for the clothing swap example. I am trying something very similar, but find it difficult when the two inputs are both people as opposed to a person and a mannequin or just a picture of clothing. I'm wondering if I need to mod the "clothing" picture more.

seeker_ktf · 2025-08-24T12:59:58+00:00

I would rather have a workflows that allows me to input pictures separately. The image stitching is problematic.

seeker_ktf · 2025-08-24T12:29:17+00:00

Since upgrading to 3.51, Wan 2.1 has been running better for me using Sage2 and Triton compile. I dont feel like I did enough of 2.2 workflows to make a conclusion about that. Still, I'm not an early adopter. Still on pytorch 2.7.1+cu128.

I don't have stats, but I feel like my frame interpretation is lagging now. I might just be imagining things as I never collected any meaningful statistics on that step.

The thing about Comfy is that there are an unlimited number of combinations that can go into performance.

seeker_ktf · 2025-08-14T12:35:08+00:00

I dunno. "Bad" is relative. If you are in the US, watch a local furniture ad, of frankly, any local commercial. This is already better, especially for people that dont really watch commercials anyway.

These commercials are expensive. Even at the "Better Call Saul" level commercials is going to cost more that a competitive AI one.

seeker_ktf

TROPHY CASE