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