I’m going to use Midjourney to add art to my Substack, but sometimes you get obsessed with stuff. I decided to generate images of female faces with the prompt:
beautiful [ethnicity/nationality] woman, portrait, photograph, cinematic, white wall
Then I picked what I thought was the most neutral face focused of the four images. I upscaled that, and remastered it. I’ve output the ones that aren’t ridiculous. For whatever reason, if an ethnic group is too obscure, the women turn out to look East Asian. No idea why. I’ve put the nationalities on top, and then various Indian ethnicities. Some of the outputs make a lot of sense. Some of the others, not so much. And many, I do not know.
Warning it will take a while to load all the images.
11 thoughts on “Faces of women of the world”
Midjourney is fun as a tool lol but damn I don’t think the thing is too accurate for Bangladesh/Bengali and most certainly not for Jatt or something hahaha
the jat looks too asian, which means it didn’t have enough input
why is the Bangladesh one off? the right one in particular seems right
maybe as per him the BD lady looks a bit less E.Asian
and yeah this is sure gonna trigger the resident Jatts like Racelearner bhai here lol
I guess yeah on second look the Bangladesh one does look pretty typical. The Bengali one looks too off tho, I still think that.
On another note, have you ever modelled us Bengalis on qpAdmin? What is our breakdown in terms of Onge-related, Iran/IVC Diaspora, Steppe, and Asian..if you have modelled us :0
use the search box. i have. basically we’re bihari peasants + 10-20% east asian. some of us have brahmin ancestry so that will skew, but that’s very small %
yeah I know the model thing, I was only curious about the qpadmin components. ik about the thing you said about the bihar peasants, the 85% patel/15% Burmese, 70%reddy/15% punhabi/15% burmese stuff you mentioned too, saw those
but yeah my bad lol just saw one, and it was from 2020 when I searched up qpadmin. In your opinion, do you think the Bengali percentages are the same today even with newer samples and technology?
Jat, Bengali, Maratha, Bihari …….. girls i’ve seen a lot, the average just is off, with Jaat, too off.
Biharis are much thinner, Bengali more rounder, Marathi have drier Skin.
It’s interesting that even with “beautiful” in the prompt, it doesn’t go for eye symmetry (eyeballing it, less eye symmetry than real people have). Christ Pantokrator icons in the training data?
The trick is – Instead of using endonyms, use typical first names from that region or ethnicity. You will be gratified!
Patel and Gujarati one are decent, especially the prior. Many look off
Comments are closed.