Instructions to use GDAOSU/Olbedo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GDAOSU/Olbedo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GDAOSU/Olbedo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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# Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments
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[](https://gdaosu.github.io/olbedo/)
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[](https://huggingface.co/spaces/GDAOSU/olbedo)
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[](https://huggingface.co/GDAOSU/olbedo)
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# Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments
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[Shuang Song](https://openreview.net/profile?id=~Shuang_Song10)¹‡,
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[Debao Huang](https://debaohuang.github.io/)¹‡,
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[Deyan Deng](https://openreview.net/profile?id=~Deyan_Deng1)¹,
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[Haolin Xiong](https://openreview.net/profile?id=~Haolin_Xiong1)²,
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[Yang Tang](https://openreview.net/profile?id=~Yang_Tang4)¹,
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[Yajie Zhao](https://openreview.net/profile?id=~Yajie_Zhao1)²,
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[Rongjun Qin](https://openreview.net/profile?id=~Rongjun_Qin1)¹*
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¹ The Ohio State University · ² University of Southern California
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‡ Equal contribution · * Corresponding author
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[](https://gdaosu.github.io/olbedo/)
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[](https://huggingface.co/spaces/GDAOSU/olbedo)
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[](https://huggingface.co/GDAOSU/olbedo)
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