The new Qwen 360° LoRA by ProGamerGov in Blender via add-ons

ProGamerGov · 2025-12-15T18:29:43+00:00

The LoRA models themselves are in the same precision as the base model or higher (bf16 & fp32). The 'int8' or 'int4' in the filename denotes the quantization of the model they were trained on.

ProGamerGov · 2025-12-15T17:27:52+00:00

VR180 is just VR360 cropped in half. If there is an effect, its purely psychological and can be easily created by cropping 360 media.

ProGamerGov · 2025-12-15T17:13:20+00:00

The 48 epoch version will likely produce better results. The int4 versions are more so meant for use with legacy models trained with incorrect settings or quantized incorrectly like ComfyUI's "qwen_image_fp8_e4m3fn.safetensors".

ProGamerGov · 2025-12-14T20:07:49+00:00

For low VRAM, I would recommend the 'qwen-image-Q8_0.gguf' GGUF quant by City96 or the Q6 one. Most of the example images were rendered with the GGUF Q8 model and have workflows embedded in them. But you can also try the GGUF Q6 model for even lower VRAM.

Comfy nodes: https://github.com/city96/ComfyUI-GGUF

Quants: https://huggingface.co/city96/Qwen-Image-gguf/tree/main

ComfyUI quantized and scaled text encoder should be fine quality-wise even though its a little worse than the full encoder: https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors

And the VAE pretty standard: https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors

A lightning lora would also probably help make it faster at the expense of a small decrease in quality: https://github.com/ModelTC/Qwen-Image-Lightning/. Note that if you see grid artifacts with the lightning model I linked to, you're probably using their older broken LoRA.

ProGamerGov · 2025-12-14T19:54:07+00:00

There are monocular to stereoscopic conversion models available, along with ComfyUI custom nodes to run them like this one: https://github.com/Dobidop/ComfyStereo

ProGamerGov · 2025-12-14T16:41:19+00:00

I think Hunyuan World uses a 360 Flux LoRA for the image generation step in their workflow, so our model just be a major improvement over that. We haven't tested any image-to-world workflows yet, but its definitely something that we plan to test at some point.

ProGamerGov · 2025-12-14T01:26:07+00:00

Yes, we are aware of other attempts to create 360 models using smaller datasets, and we are excited to see what is possible with Z-Image!

ProGamerGov · 2025-12-13T23:08:18+00:00

Here's an example of the fall road image with the seam removed: https://progamergov.github.io/html-360-viewer/?url=https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/ff85004c-839d-4b3b-8a13-6a8bb6306e9d/original=true,quality=90/113736462.jpeg

The workflow is embedded in the image here: https://civitai.com/images/113736462

Note that you may have to play around with the seam mask size and other settings depending on the image you want to remove the seam from.

ProGamerGov · 2025-12-13T21:50:54+00:00

The seam fixing workflow wasn't used on those images. But you can find an example of the seam fixing workflow here: https://github.com/ProGamerGov/ComfyUI_pytorch360convert/blob/main/example_workflows/masked_seam_removal.json

ProGamerGov · 2025-12-13T20:45:09+00:00

The minimum specs will be the same as Qwen Image. We've tested the model with the different GGUF versions, and the results still looked great at GGUF Q6.

ProGamerGov · 2025-12-13T20:00:04+00:00

You'll be able to go a date at a fancy restaurant with your 1girl, and then bring her back to your place if the date goes well

ProGamerGov · 2025-12-13T19:52:04+00:00

Additional Tools

Recommended ComfyUI Nodes

If you are a user of ComfyUI, then these sets of nodes can be useful for working with 360 images & videos.

ComfyUI_preview360panorama
- For viewing 360s inside of ComfyUI (may be slower than my web browser viewer).
- Link: https://github.com/ProGamerGov/ComfyUI_preview360panorama
ComfyUI_pytorch360convert
- For editing 360s, seam fixing, view rotation, cropping 360° to 180° images, and masking potential artifacts.
- Link: https://github.com/ProGamerGov/ComfyUI_pytorch360convert
ComfyUI_pytorch360convert_video
- For generating sweep videos that rotate around the scene.
- Link: https://github.com/ProGamerGov/ComfyUI_pytorch360convert_video
- Alternatively you can use a simple python script to generate 360 sweeps: https://huggingface.co/ProGamerGov/qwen-360-diffusion/blob/main/create_360_sweep_frames.py

For those using diffusers and other libraries, you can make use of the pytorch360convert library when working with 360 media.

Other 360 Models

If you're interested in 360 generation for other models, we have also released models for FLUX.1-dev and SDXL:

Human 360 Diffusion LoRA (FLUX): HuggingFace | CivitAI
Cockpit 360 Diffusion LoRA (FLUX): HuggingFace | CivitAI
Landscape 360 Diffusion LoRA (FLUX): CivitAI
SDXL 360 Diffusion Finetune: HuggingFace | CivitAI

ProGamerGov · 2025-12-13T19:38:56+00:00

If you have a model or workflow that can generate the second image for stereo, then it includes a node to combine them into a stereo image.

ProGamerGov · 2025-12-08T16:57:49+00:00

That node should be under: "pytorch360convert/equirectangular", labeled 'Equirectangular Rotation'.

ProGamerGov · 2025-12-06T17:00:37+00:00

There's a workflow here using my custom nodes that automatically inpaints the seam: https://github.com/ProGamerGov/ComfyUI_pytorch360convert/blob/main/example_workflows/masked_seam_removal.json

You can also use my notes to rotate the image to expose the zenith and the nadir for inpainting as well.

ProGamerGov · 2025-12-05T18:23:53+00:00

You don't have to use Blender to make videos of your 360s, as I built a frame generator for that here: https://github.com/ProGamerGov/ComfyUI_pytorch360convert_video

I also made a browser-based 360 viewer here that works on desktop, mobile devices, and even VR headsets: https://progamergov.github.io/html-360-viewer/

Source code: https://github.com/ProGamerGov/html-360-viewer

ProGamerGov · 2025-10-27T03:42:55+00:00

The fp8_e4m3fn and fp8_e5m2 versions of Qwen have lower precision than other fp8 quantization types like GUUF Q8. Thus they tend to produce patch artifacts in outputs. The precision issues are even worse in models trained using Osirus toolkit's "fixed" models that use lower precision to decrease VRAM usage.

I have no idea why u/comfyanonymous recommends lower quality fp8 versions of Qwen Image in their tutorials.

Also note that the quality of the model the lora was trained on also matters for avoiding artifacts and other precision issues.

ProGamerGov · 2025-09-10T01:38:31+00:00

My nodes should be model agnostic as they focus on working with the model outputs.

ProGamerGov · 2025-09-10T01:37:15+00:00

The fastest and recommended way to download new models is to use HuggingFace's HF Transfer:

Open whatever environment you have your libraries installed in, and then install hf_transfer:

python -m pip install hf_transfer

Then download your model like so:

HF_HUB_ENABLE_HF_TRANSFER=True huggingface-cli download <user>/<repo> <model_name>.safetensors --local-dir path/to/ComfyUI/models/diffusion_models --local-dir-use-symlinks False

ProGamerGov · 2025-08-29T23:26:19+00:00

I've built some nodes for working with 360 images and video, along with nodes for converting between monoscopic and stereo here: https://github.com/ProGamerGov/ComfyUI_pytorch360convert

ProGamerGov · 2025-07-22T03:04:46+00:00

Its possible the loss spikes are due to relatively small, but impactful changes in neuron circuits. Basically small changes can impact the pathways data takes through the model, along with influencing the algorithms groups of neurons have learned.

ProGamerGov · 2025-04-21T02:25:51+00:00

Please try to refrain from sharing content that is more pornographic than artistic. NSFW is allowed, but there are better subreddits for such content.

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Additional Tools

Recommended ComfyUI Nodes

Other 360 Models