Keypoint Detection
Transformers
Safetensors
LightGlue
keypoint-matching
model_hub_mixin
pytorch_model_hub_mixin
Instructions to use ETH-CVG/lightglue_disk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ETH-CVG/lightglue_disk with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForKeypointMatching processor = AutoImageProcessor.from_pretrained("ETH-CVG/lightglue_disk") model = AutoModelForKeypointMatching.from_pretrained("ETH-CVG/lightglue_disk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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model = LightGlueForKeypointMatching.from_pretrained("ETH-CVG/lightglue_disk", trust_remote_code=True)
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```
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# LightGlue
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The LightGlue model was proposed
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model = LightGlueForKeypointMatching.from_pretrained("ETH-CVG/lightglue_disk", trust_remote_code=True)
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```
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_Also, the commit allowing DISK to work with LightGlue is not yet included in a version of transformers, please install transformers from the main branch_
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```
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uv pip install git+https://github.com/huggingface/transformers.git
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```
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# LightGlue
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The LightGlue model was proposed
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