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Kaludi/CSGO-Minimap-Layout-Generation
CSGO-Minimap-Layout-Generation is a text-to-image model from Kaludi. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
Downloads · 30 days
16
1% of all-time downloads
All-time downloads
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.ckpt2.1 GB · 100%
From the Hugging Face model README

This is an improved AI model of my previous model trained on CS:GO's radar top view images of many maps which can now produce custom map layouts in seconds. This model does not produce red or green boxes like in my previous model. The tag for this model is "radar-topview". If you'd like to get a map layout similar to a specific map, you can add the map name before "radar-topview". So if I wanted a map generation similar to dust2, I would write "dust2-radar-topview".
Try the following prompt to get the best results:
"fps radar-topview game map, flat shading, soft shadows, global illumination"
"fps radar topview map, polygonal, gradient background, pastel colors, soft shadows, global illumination, straight lines, insanely detailed"
Map Radar Topviews this AI was trained on:
de_dust2
de_inferno
de_nuke
de_mirage
de_cache
de_train
de_cobblestone
de_castle
de_overpass
Have fun generating map layouts!
Download csgoTopViewMapLayout.ckpt) (2.9GB)
This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion Pipeline.
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
import torch
prompt = (
"fps radar-topview game map, flat shading, soft shadows, global illumination")
model_id = "Kaludi/CSGO-Improved-Radar-Top-View-Map-Layouts"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
image = pipe(prompt, num_inference_steps=30).images[0]
image.save("./result.jpg")
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies: