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ProGamerGov/cockpit-360-lora-flux-dev
cockpit-360-lora-flux-dev is a text-to-image model from ProGamerGov. Use it when you need an image from a text prompt. It is set up for diffusers.
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From the Hugging Face model README
This LoRA was trained for 27,250 iterations with rank 64 on a diverse dataset of around 300 images, for the purpose of creating 360 degree panorama images of cockpits and vehicle interiors.
The seam and polar distortion artifacts should be minimal, but some careful editing or in-painting may be required to make the image appear seamless.
There is no trigger phrase, but as with all 360° Flux LoRAs, you should include some variation of '360 degree equirectangular view' in your prompt to improve output quality.
When rendering images, it's recommended that you choose a 2:1 aspect ratio, like 1024x512, 1536x768, or 2048x1024. Afterwards, you can use an upscaler of your choosing to make the resolution high enough for skyboxes, VR, and 2D/3D environments.
To make the viewing and sharing of 360 images & video easier, I built a web browser based HTML 360 viewer that runs locally on your device.
?url= followed by a link to your image in order to automatically load it into the 360 viewer, making sharing your 360 creations extremely easy.If you are a user of ComfyUI, then these sets of nodes can be useful for working with 360 images & videos.
ComfyUI_preview360panorama
ComfyUI_pytorch360convert
For diffusers and other libraries, you can make use of the pytorch360convert library when working with 360 media.
The dataset was weighted towards aircraft cockpits and the front seats of cars.
BibTeX
@software{Egan_Cockpit_360_Diffusion_2025,
author = {Egan, Ben},
license = {MIT},
month = aug,
title = {{Cockpit 360 Diffusion LoRA for FLUX.1-dev}},
url = {https://huggingface.co/ProGamerGov/cockpit-360-lora-flux-dev},
year = {2025}
}
APA
Egan, B. (2025). Cockpit 360 Diffusion LoRA for FLUX.1-dev [Computer software]. https://huggingface.co/ProGamerGov/cockpit-360-lora-flux-dev
Please refer to the CITATION.cff for more information on how to cite this model.
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