Instructions to use zju-community/efficientloftr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zju-community/efficientloftr with Transformers:
# Load model directly from transformers import AutoImageProcessor, AutoModelForKeypointMatching processor = AutoImageProcessor.from_pretrained("zju-community/efficientloftr") model = AutoModelForKeypointMatching.from_pretrained("zju-community/efficientloftr") - Notebooks
- Google Colab
- Kaggle
Update README.md
#1
by wyf2020 - opened
README.md
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@@ -71,8 +71,8 @@ image2 = Image.open(requests.get(url_image2, stream=True).raw)
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images = [image1, image2]
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processor = AutoImageProcessor.from_pretrained("zju-community/
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model = AutoModel.from_pretrained("zju-community/
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inputs = processor(images, return_tensors="pt")
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with torch.no_grad():
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images = [image1, image2]
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processor = AutoImageProcessor.from_pretrained("zju-community/efficientloftr")
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model = AutoModel.from_pretrained("zju-community/efficientloftr")
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inputs = processor(images, return_tensors="pt")
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with torch.no_grad():
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