repository for Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models
git clone https://github.com/ArcherFMY/SD-T2I-360PanoImage.git
cd SD-T2I-360PanoImage
pip install -r requirements.txt
Download models from Baidu Disk. 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, and unzip it into the 'models' directory. Or download the models from Hugging Face
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
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
see here for more information.
This code is released under the Apache License 2.0 (refer to the LICENSE file for details).