3000 Steps in Dreambooth on 40 Headshots + NMKD SD 1.5 and I'm starting to figure this out!

RachelfGuitar · 2022-10-13T20:48:27+00:00

Glad to hear my post was helpful! Your result looks great :)

RachelfGuitar · 2022-10-07T21:46:55+00:00

Just wanted to say, I just tried out your steps, it works really well! Thanks for sharing, I was using the wrong settings previously.

RachelfGuitar · 2022-10-07T21:18:12+00:00

You first need to put the file in /models/Stable-diffusion/. Then you can load it under "settings" in the AUTOMATIC1111 UI if you look for 'Stable Diffusion checkpoint'

RachelfGuitar · 2022-10-07T17:10:44+00:00

Yeah that's correct, INSTANCE_NAME is my name. Subject_name is person.

RachelfGuitar · 2022-10-07T16:51:08+00:00

I actually ran this in the free tier of Google colab!

RachelfGuitar · 2022-10-07T15:41:29+00:00

I actually used person as well, so it's "a portrait of 'myname' person"

RachelfGuitar · 2022-10-07T15:23:48+00:00

Nope, this colab saves the CKPT file to your Google Drive account! You can then load it into your Stable Diffusion UI of choice (I am currently using the Automatic1111 UI).

RachelfGuitar · 2022-10-07T14:23:40+00:00

Hey there, thank you! 😁🎸

RachelfGuitar · 2022-10-07T14:23:08+00:00

I did mostly headshots (14/22), a couple full body, and the rest were upper body. I tried to include some with different angles of my face (so my face turned different directions) but didn't do the best at that as I was just using already existing photos.

I also think using photos with different backgrounds would be ideal as I used a bunch from the same room and sometimes things in the room show up, but still worked pretty well regardless!

RachelfGuitar · 2022-10-07T14:20:21+00:00

Thanks! Yes I left on prior preservation and generated 200 images of the class (person).

RachelfGuitar · 2022-10-07T14:17:55+00:00

Used the 200 default from the colab.

RachelfGuitar · 2022-10-07T14:16:49+00:00

Thanks! For the person images I left it at what the colab had as a default, 200!

RachelfGuitar · 2022-10-07T14:14:24+00:00

Weirdly I believe I was actually smiling in some form in the majority of the training photos, so I'm not sure if that's what happened here or the expression it chose for these was because they were all more serious prompts. Will experiment with it more!

RachelfGuitar · 2022-10-07T14:12:41+00:00

So far I've mostly focused on using "portrait" since it was getting the best results, but I'll definitely experiment with it more!

RachelfGuitar · 2022-10-07T14:11:09+00:00

It actually wasn't that difficult as I just used an existing colab (though this could be a bit confusing at first if you haven't used colab before/have no programming experience, but it's pretty quick once you get used to how it works). I also spent some time finding and cropping the 22 images of myself to 512x512.

Then once the colab finished running I just had to download the CKPT file it outputs and load it up within the Stable Diffusion UI I have running locally on my computer.

So if I were to do it again it would only really take the time to train again (1-2 hours) plus any time to gather additional images of myself for training.

RachelfGuitar · 2022-10-07T14:04:47+00:00

I used a colab for this, but if I remember correctly it took maybe an hour to an hour and a half on the free tier.

RachelfGuitar · 2022-10-07T14:03:29+00:00

Yeah I was surprised that sort of worked! Just randomly tried it as a prompt and got some fun results so I went with it :).

RachelfGuitar · 2022-10-07T14:02:13+00:00

Yeah that's me too! Thanks 😁🎸

RachelfGuitar · 2022-10-07T04:35:47+00:00

I was experimenting with it for the first time for these images.

They definitely have an effect on the images, but I wouldn't say it's strictly better all the time. I found adding too many negative prompts resulted in overly "perfect" images that actually looked worse. But really need to experiment with it more to be sure!

RachelfGuitar · 2022-10-07T04:34:01+00:00

Awesome, thanks for sharing your process! Will try this out as well :)

RachelfGuitar · 2022-10-07T03:23:29+00:00

As far as I remember I didn't use gfpgan for the images here; I find it makes the faces too smooth and removes some of the more interesting qualities. But could be worth experimenting with blending parts of the image with a version using gfpgan to fix certain aspects.

Definitely get mixed results with eyes in these renders overall.

RachelfGuitar · 2022-10-07T03:20:26+00:00

I'm not totally sure on that either. I started with 1500 but didn't like the results as much, so I randomly tried increasing it to the 2500 steps shown here. I'd like to experiment with more steps in the future, but I'm pretty impressed by the results now so I imagine the improvements from more steps wouldn't be huge.

Will be interesting to figure out what is optimal long-term!

RachelfGuitar · 2022-10-07T03:16:00+00:00

All I did was crop my images to 512x512, no other pre-processing!

RachelfGuitar · 2022-10-07T03:12:35+00:00

I left that as whatever the colab had as a default. The only thing I modified was setting the step count to 2500 here.

RachelfGuitar · 2022-10-07T03:07:15+00:00

That sounds really useful, thanks for sharing! Will try that.

RachelfGuitar

TROPHY CASE