While we're here... I'm not a flower specialist. So I asked #ChatGPT to provide me with some ideas of well-known flower species.
Prompt: "list the names of 20 of the most beautiful flowers"
Done.
"Iris flower, pixel art, 8-bit, sRGB, icon"
"Peony flower, pixel art, 8-bit, sRGB, icon"
"Lavender flower, pixel art, 8-bit, sRGB, icon"
Note: it looks like the AI took "lavender" as the color of the flower, not precisely its type (genus/species).
"Hibiscus flower, pixel art, 8-bit, sRGB, icon"
"Chrysanthemum, pixel art, 8-bit, sRGB, icon"
"Clematis flower, pixel art, 8-bit, sRGB, icon
"Poppy flower, pixel art, 8-bit, sRGB, icon"
"Carnation flower, pixel art, 8-bit, sRGB, icon"
"Passion flower, pixel art, 8-bit, sRGB, icon"
I can access all my AI-generated images under the "Images" tab and also via the "Generator" icon itself.
I can easily see the prompts I used, compare batches, or download individual images (more filtering/sorting features are coming shortly).
While not all output images are perfect (some prompts could have been more precise, and some flowers could have looked better), it's still an excellent example of how to use Stable Diffusion finetunes (with @Scenario_gg) to explore a specific graphic direction, consistently.
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2D battle backgrounds in mobile games typically feature a static image or animation that provides a visual backdrop for the action taking place on the screen.
There are 30 "battle backgrounds“ packs on the Unity asset store ($10 to $25 for a set of 5-10 backgrounds)
Let me share some landscapes for a comic book, that I'm creating right now with @Scenario_gg. All with the same, consistent style.🎨
End-less-fun-machine.
The prompts are pasted below 👇
"A landscape in Ireland. The sky is grey and cloudy. There's a dark lake in the background. The grass is dark green with lots of dry stone walls."
"A Normandy lanscape near Etretat. The massive white cliffs dominate a rocky beach, and the sea is green-gray. The sky is grey with white clouds, it's raining"
I actually generated more than 200 buildings (and even some vehicles), from which I picked a smaller dataset, keeping enough variability within a certain consistent style.
I will keep the remaining data for new trainings in the coming days :)