/SuperGlue-for-SAM

Using SuperGlue (from Magic Leap team) to use for instance matching.

Primary LanguagePythonOtherNOASSERTION

SuperGlue for SAM

Adapted from SuperGlue-for-Visual-Place-Recognition

Dependencies

  • Python 3
  • PyTorch
  • OpenCV
  • Matplotlib
  • NumPy
  • Pandas

Added Contents

  • superglue_detect_cereal.py: To be run once SAM has been used to detect cereal boxes and instance images have been found and created.

This is to be run on the instance images (which are the query images), against the input reference images (the provided zip of product thumbnails).

Input arguments:

  • --input_dir: Path to database image directory
  • --query_dir: Path to query image directory
  • --output_dir: Path to store npz and visualization files

BibTeX Citation

If you use any ideas from the paper or code from this repo, please consider citing:

@inproceedings{sarlin20superglue,
  author    = {Paul-Edouard Sarlin and
               Daniel DeTone and
               Tomasz Malisiewicz and
               Andrew Rabinovich},
  title     = {{SuperGlue}: Learning Feature Matching with Graph Neural Networks},
  booktitle = {CVPR},
  year      = {2020},
  url       = {https://arxiv.org/abs/1911.11763}
}

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