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--- |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- image-to-image |
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dataset_info: |
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features: |
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- name: lensless |
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dtype: image |
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- name: lensed |
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dtype: image |
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splits: |
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- name: train |
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num_bytes: 5600452730.0 |
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num_examples: 24000 |
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- name: test |
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num_bytes: 230987060.0 |
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num_examples: 999 |
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download_size: 5873531153 |
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dataset_size: 5831439790.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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tags: |
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- lensless |
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- computational-imaging |
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--- |
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# For future training, it is recommended to use [this normalized version](https://huggingface.co/datasets/bezzam/DiffuserCam-Lensless-Mirflickr-Dataset-NORM) of the dataset. |
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More accessible (6GB instead of 100GB) copy of: https://waller-lab.github.io/LenslessLearning/dataset.html |
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Original license: https://github.com/Waller-Lab/LenslessLearning/blob/master/LICENSE |
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This dataset was prepared with [this script](https://github.com/LCAV/LenslessPiCam/blob/main/scripts/data/upload_diffusercam_huggingface.py). |
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After cloning and installing [LenslessPiCam](https://github.com/LCAV/LenslessPiCam), ADMM reconstruction can be applied to the dataset with [this script](https://github.com/LCAV/LenslessPiCam/blob/main/scripts/recon/dataset.py) (handles dataset downloading from Hugging Face). |
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```bash |
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python scripts/recon/dataset.py |
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``` |
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The models in [this collection](https://huggingface.co/collections/bezzam/diffusercam-mirflickr-65c05164df72cf99e5066658) use the [original DiffuserCam MirFlickr dataset](https://waller-lab.github.io/LenslessLearning/dataset.html) during training. |
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This dataset tries to replicate that version of the dataset (using NPY files during training). |
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One slight different is that we were required to subtract the mininum of value the numpy arrays so that they could be stored as viewable images. |
