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evaluate

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List of commits on branch main.
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89a3f07e062dcff6ab4c3907ff6a9fa128f50df7

Merge branch 'main' of github.com:chaithyagr/evaluate into main

committed 2 years ago
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7974de3fd4abc7dabde775db46130bae1114c4fe

added acq-recon

committed 2 years ago
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e6949534e2b023c1c35ceef4bb777899ecbf8aab

Update README.md

cchaithyagr committed 2 years ago
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c9fdb37968e3d403045a9d0cc005ab28a95530d8

Create requirements.txt

cchaithyagr committed 2 years ago
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5cba55a31947582264d9786aa6fe40e6cbc40ff8

Added context

committed 2 years ago
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08647733b740c6358b95b551ffaae28622f4ddfd

Update README.md

cchaithyagr committed 2 years ago

README

The README file for this repository.

Evaluation

Binder

  1. Please fork this repository and clone it locally
  2. Install a local Python environment, ensure you have install numpy, scipy, matplotlib, jupyterlab and scikit-image as requirements.
  3. Run the jupyter lab server from this base repository folder.
  4. Solve the listed problems in mri_acq_recon.ipynb and make separate commits for each problem.
  5. Push your changes and make a pull request of your changes on github.
  6. Finally, launch the second notebook mri_reconstruction_dl_intro.ipynb in google collab Open In Colab and run it through to see the performance of deep learning based models.