Architects' tools
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Hi, my name is Albert Sumin, this is my channel, I am an architect and computational designer at Cloud Cooperation (Vienna, Austria)
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I wanted to post the new LoRA model and workflow for it today, but I ran out of time, so here's a preview for now (everything will be up this week). The idea is to make winter renders from summer ones. It's not absolutely perfect, it's AI after all, so a bit of Photoshop on top to keep important details of buildings.

In Photoshop it is necessary to erase the unwanted from the AI image and adjust the colors and brightness of the result.
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To make it clearer exactly how the images change, here are some gifs:
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by the way, you don't have to strictly repeat existing renders, you can let ControlNet go a bit and get variants
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Finally got around to testing the ChatGPT's new image features (in case you slept through the last week, you can now edit and create pretty much any image you want just using words), and it all looks pretty cool. But let's dig deeper, and see what the drawbacks are. I'll compare it to #comfyui using two examples:
1. Winter render
2. Filling an empty interior with furniture
The first image is an original render from a 3D model in Blender

second image - ChatGPT

third image - SDXL in ComfyUI.

It is obvious that ChatGPT is much more realistic, and it is understandable, after all, the competitor (SDXL) seems to be more than two years old.

If we talk about clear disadvantages, ChatGPT is very slow so far, generation takes 5-10 minutes, while SDXL handles the job in seconds.
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But if you look closely, you can see another problem, ChatGPT changes the proportions of the objects. There is no ControlNet and therefore it's hard for it to keep everything exactly as it is on the source. This is important, because the details in any case in many places are incorrect, and they need to be erased in Photoshop to adjust with the original image. Unfortunately this can not be done with the result from ChatGPT. Because of which it seems there is no sense at all to use the model for such tasks.
second example, we take 4 images, an empty interior, a table, a rug and a sofa, and combine all this into one composition.