Whats the flag in the tram?
Idk...
Depends on preference but I usually go for bread with more fiber cause after eating this you will be hungry again in 20mins.
But at least there arent many holes the size of our solar system so you can spread the butter/margarine quite nicely.
It feels just like yesterday when the number hardly ever crossed 1k. Now its special when its not above 1.5k.
Crazy how fast the people-grinder fired up.
Isn't that a good thing? Cause it makes russia at least somehow feel some consequences?
...together with his gay lover
cross-posted from: https://lemmy.world/post/19439809
So begins the reddit stash dump.
The greens got to design some legislation
Fuck Nestle.
And since Starbucks is owned by Neste: Fuck Starbucks.
Yeah, you can see that organic maps is sadly not there yet in terms of driving-interface, but hopefully its getting there soon.
Afaik the app is far younger than magic earth and for what it is its super good. I'm so stoked to see how organic maps is gonna develop in the coming years
Hey guys I kind of have a little probleme here:
So during the upgrading of Mint 21.3 to Mint 22 there appeared some errors, and while trying to fix them a lot of library-packages were deleted and most of the programs gone.
Now after that I tried to reset my system back to tze last timeshift-backup but timeshift only ever deleted more packages and never installed the old files from the backup (i guess).
So now this is where I am at, a kernel panic and nothing boots. I guess i need a new (fresh) install and could try to use the backup of timeshift on that one?
Or is there any other elegant way to get out of this?
Thanks already for reading and tips <3
My dude did you even read the article?
Besser ist es, die Freiwilligendienstler saugen mit ihrer überbezahlten "Arbeit" schon viel zu lange die Staatskassen leer. Wird Zeit dass die auch mal was richtiges machen /s
Thats fuckin amazing.
I can still remember when we celebrated linux being at 0.8% and it was not long ago.
Hey guys,
I have been experimenting with self-supervised visual learning a bit. Until now I have only ever used U-Nets and related architectures.
No matter what specific task, images or other parameters I changed I always encountered these stains on my output-images (here marked with green), although sometimes more, sometimes less.
Now I wondered if anybody could tell me where they came from and how I could prevent them?
In the attached picture the input (left) and target (right) are the same, so that I can be sure these stains do not come from a badly designed learning task, yet they still appear (output is the middle image).
Thanks in advance and all the best :D
Edit: added line breaks
Thats where I have seen it before!
Maybe its also both, so the conductor can have plausible deniability but also display white-blue-white?