Yoso Normal V1 5

🚀 StableNormal

StableNormal reduces diffusion variance for stable and sharp normal generation.

🚀 Quick Start

This repository contains the weights of StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal.

📦 Installation

See the Github repository: https://github.com/Stable-X/StableNormal regarding installation instructions.

💻 Usage Examples

Basic Usage

import torch
from PIL import Image

# Load an image
input_image = Image.open("path/to/your/image.jpg")

# Create predictor instance
predictor = torch.hub.load("hugoycj/StableNormal", "StableNormal_turbo", trust_repo=True, yoso_version='yoso-normal-v1-5')

# Generate normal map using alpha channel for masking
normal_map = predictor(rgba_image, data_type="object")  # Will mask out background, if alpha channel is avalible, else use birefnet
normal_map = predictor(rgba_image, data_type="outdoor")  # Will use Mask2Former to mask out sky and plants
normal_map = predictor(rgba_image, data_type="indoor") # Will not mask out

# Apply the model to the image
normal_image = predictor(input_image)

# Save or display the result
normal_image.save("output/normal_map.png")

📄 License

This project is licensed under the Apache-2.0 license.