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
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- model_hub_mixin
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library_name: transformers
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license:
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pipeline_tag: keypoint-detection
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---
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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This is a LightGlue variant trained on DISK, which requires `kornia` to be installed and is usable with transformers with the following lines of code
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```python
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from transformers import LightGlueForKeypointMatching
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- model_hub_mixin
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library_name: transformers
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license: apache-2.0
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pipeline_tag: keypoint-detection
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---
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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This is a LightGlue variant trained on DISK, with a commecially permissive license, which requires `kornia` to be installed and is usable with transformers with the following lines of code
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```python
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from transformers import LightGlueForKeypointMatching
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