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repository for 360 panorama image generation based on Stable Diffusion
| Date | Stars |
|---|---|
| 2026-07-31 | 324 |
| 2026-08-02 | 324 |
| 2026-08-06 | 324 |
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growth rate 0.00%/day
# SD-T2I-360PanoImage
repository for [**Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models** ](https://arxiv.org/pdf/2311.13141.pdf)
## News!!!
- 2024.5.20. I recommend to install 0.20.0<= diffusers <= 0.26.0. The higher diffusers version will get an over-saturated SR result.
- 2024.5.17. A ComfyUI plugin of this repo is released!
See https://github.com/ArcherFMY/Diffusion360_ComfyUI for more information
## Text-to-360Panorama
# 
# 
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## Single-Image-to-360Panorama
# 
## Requirements
- torch
- torchvision
- torchaudio
- diffusers
- accelerate
- xformers
- triton
- transformers
- realesrgan
- py360convert
## Installation
```
git clone https://github.com/ArcherFMY/SD-T2I-360PanoImage.git
cd SD-T2I-360PanoImage
pip install -r requirements.txt
```
## Getting Started
### Download Models
Download models from [Baidu Disk](https://pan.baidu.com/s/1i_ypdWHknp2kqbjl0_zAuw?pwd=w2vr). Unzip `models.zip` into the root directory of the project.
```
${ROOT}
|-- data
| |-- a-living-room.png
| |...
|-- models
| |-- sd-base
| |-- sr-base
| |-- sr-control
| |-- RealESRGAN_x2plus.pth
|-- txt2panoimg
|-- img2panoimg
|...
```
For users who want the Single-Image-to-360Panorama models, please download the additional models from [Baidu Disk](https://pan.baidu.com/s/1kJxXeMXLASYjMThDPl50xQ?pwd=tput), and unzip it into the 'models' directory.
Or download the models from [Hugging Face](https://huggingface.co/archerfmy0831/sd-t2i-360panoimage)
### Inference
#### Text-to-360Panorama
```
import torch
from txt2panoimage import Text2360PanoramaImagePipeline
prompt = 'The living room'
input = {'prompt': prompt, 'upscale': False}
model_id = './models'
txt2panoimg = Text2360PanoramaImagePipeline(model_id, torch_dtype=torch.float16)
output = txt2panoimg(input)
output.save('result.png')
```
see more in `demo_t2p.py`
#### Single-Image-to-360Panorama
```
import torch
from diffusers.utils import load_image
from img2panoimg import Image2360PanoramaImagePipeline
image = load_image("./data/i2p-image.jpg").resize((512, 512))
mask = load_image("./data/i2p-mask.jpg")
prompt = 'The office room'
input = {'prompt': prompt, 'image': image, 'mask': mask, 'upscale': False}
model_id = 'models'
img2panoimg = Image2360PanoramaImagePipeline(model_id, torch_dtype=torch.float16)
output = img2panoimg(input)
output.save('result.png')
```
see more in `demo_i2p.py`
### Use Text-to-360Panorama in ModelScope
see [here](https://www.modelscope.cn/models/damo/cv_diffusion_text-to-360panorama-image_generation/summary) for more information.
## License
This code is released under the Apache License 2.0 (refer to the LICENSE file for details).
Excerpt of 2,924 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8cc6e1fc15ed80e2, desc:image generation, desc:stable diffusion