@Kierkegaard420 I just had a look at your upscaling workflow, it's strange how you're using a still image to match the colors for a video. I don't think that should work but I'm gonna try anyway, for science. For matching image colors my favorite node is Image Color Match from comfyui-easy-use package, with the default wavelet method. It's really the best I've found so far but it couldn't handle a batch of images from a video, maybe there is a way

@Kierkegaard420 It didn't work, as expected. Back to color correct manually, sigh. lol

@Kierkegaard420 idk if that second one was supposed to have a workflow or you were just proving the point. But in just a couple I2V tests I had almost perfect likeness with both at full strength. However, in general, when dealing with movement and physics it's High, and when dealing with style and quality and it's Low (for example, a nipple tuner would go on low, while this BreastPlay-high lora could be the only lora in the High slot and it would still work perfectly). You could however turn down the low lora to "somewhere" between 0.3 and 0.8. Sounds like someone liked 0.6. Since it's the low half, it should hopefully keep its "style and quality" opinions about the face at a lower strength, while retaining the movement and physics quality from the high lora.

This is just my experience. I don't know if this is documented somewhere for real. Maybe.

@Kierkegaard420 I've got no issues, as you can see from the ~100 videos I've posted so far. Half strength seems to work well (~.5)

@Kierkegaard420 Just using half strength (.5) on both high and low for your two models, and lightx2v 480 Wan 2.1 lora at 2 strength on both high and low models since it doesn't introduce any slow motion compared to the 2.2 lightning loras. I'm using context options on Kijai's WanVideoWrapper and multiple prompts for different segments all in one video generation. That's what those | symbols are for. 81 frame segments at a total of 329 frames for twenty seconds. I would say 75% of my generations turned out great. No facial distortion or quality degradation.

It simply looks like most of the training set contains slow movement. I don't think the training data is at a different FPS than any other lora, although I can't know that for sure. In my tests the motion was slow, but it wasn't "slowed", if you know what I mean. Like look at the blinks and the muscle twitches, they're all pretty much normal.

@Kierkegaard420 @makiaeveli Got it, thanks.

Thanks for the strength, I was trying all around that

You can just prompt that?!

https://civitai.com/models/705447/fondled

Tried this recently in 2.2 (add it to both high and low, and mess with strength), and it works well, as an option. (The examples are synthetic, but I tried it with realistic scenarios and it worked great.)

None of that is to discourage a 2.2 solution, just letting you know you have an option now.

Thank you for the LoRA and for considering file size in the equation.

@Kierkegaard420 Why is it registered as I2V base model then?

@wewewew Gotta set it like that for people to be able to use it with the on-site generator on I2V. In my testing it performs much better on I2V than T2V regardless so I2V is the way to go.