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
Update README.md
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README.md
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@@ -64,6 +64,7 @@ prediction = torch.nn.functional.interpolate(
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mode="bicubic",
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align_corners=False,
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)
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# visualize the prediction
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output = prediction.squeeze().cpu().numpy()
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mode="bicubic",
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align_corners=False,
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)
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```
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# visualize the prediction
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output = prediction.squeeze().cpu().numpy()
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