World Initializer Image To Panorama

🚀 GenEx-World-Initializer 🧭🌍

GenEx World Initializer is a panorama generation pipeline built upon the FluxFillPipeline. It can transform a single view image into a 360° panoramic image through vision-conditioned inpainting.

• 🖼️ Input: One image (any size, will be center-cropped to a square)
• 🧠 Prompt: Optional text to guide panoramic generation
• 🎯 Output: 2048 × 1024 equirectangular image
• 🧩 Mask: Uses a fixed panoramic mask

🚀 Quick Start

📦 Installation

The following dependencies are required:

diffusers>=0.33.1
transformers
numpy
pillow
sentencepiece 

💻 Usage Examples

Basic Usage

from diffusers import DiffusionPipeline
from PIL import Image
import torch

pipe = DiffusionPipeline.from_pretrained(
    "genex-world/World-Initializer-image-to-panorama",
    custom_pipeline="genex_world_initializer_pipeline",  
    torch_dtype=torch.bfloat16,
    trust_remote_code=True
).to("cuda")

# Load your image (any resolution)
image = Image.open("example_input.jpg")

# Run inference
front_view, output = pipe(image=image)
output.images[0]

🏁 Mask

The following mask is used to train the inpainting diffuser and is used for inference automatically.

📄 License

This project is licensed under the cc-by-4.0 license.

✨ BibTex

@misc{lu2025genexgeneratingexplorableworld,
      title={GenEx: Generating an Explorable World}, 
      author={Taiming Lu and Tianmin Shu and Junfei Xiao and Luoxin Ye and Jiahao Wang and Cheng Peng and Chen Wei and Daniel Khashabi and Rama Chellappa and Alan Yuille and Jieneng Chen},
      year={2025},
      eprint={2412.09624},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.09624}, 
}