Instructions to use LiheYoung/depth-anything-base-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiheYoung/depth-anything-base-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="LiheYoung/depth-anything-base-hf")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("LiheYoung/depth-anything-base-hf") model = AutoModelForDepthEstimation.from_pretrained("LiheYoung/depth-anything-base-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Depth Anything model. It was introduced in the paper [Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data](https://arxiv.org/abs/2401.10891) by Lihe Yang et al. and first released in [this repository](https://github.com/LiheYoung/Depth-Anything).
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Disclaimer: The team releasing Depth Anything did not write a model card for this model so this model card has been written by the Hugging Face team.
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## Model description
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Depth Anything model. It was introduced in the paper [Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data](https://arxiv.org/abs/2401.10891) by Lihe Yang et al. and first released in [this repository](https://github.com/LiheYoung/Depth-Anything).
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[Online demo](https://huggingface.co/spaces/LiheYoung/Depth-Anything) is also provided.
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Disclaimer: The team releasing Depth Anything did not write a model card for this model so this model card has been written by the Hugging Face team.
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## Model description
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