Instructions to use Intel/dpt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-large")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-large") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-large") - Notebooks
- Google Colab
- Kaggle
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README.md
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DPT uses the Vision Transformer (ViT) as backbone and adds a neck + head on top for monocular depth estimation.
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 as backbone and adds a neck + head on top for monocular depth estimation.
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## Intended uses & limitations
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