README.md

metadata

license: mit
dataset_info:
  features:
    - name: lensless
      dtype: image
    - name: lensed
      dtype: image
    - name: 5_o_Clock_Shadow
      dtype: bool
    - name: Arched_Eyebrows
      dtype: bool
    - name: Attractive
      dtype: bool
    - name: Bags_Under_Eyes
      dtype: bool
    - name: Bald
      dtype: bool
    - name: Bangs
      dtype: bool
    - name: Big_Lips
      dtype: bool
    - name: Big_Nose
      dtype: bool
    - name: Black_Hair
      dtype: bool
    - name: Blond_Hair
      dtype: bool
    - name: Blurry
      dtype: bool
    - name: Brown_Hair
      dtype: bool
    - name: Bushy_Eyebrows
      dtype: bool
    - name: Chubby
      dtype: bool
    - name: Double_Chin
      dtype: bool
    - name: Eyeglasses
      dtype: bool
    - name: Goatee
      dtype: bool
    - name: Gray_Hair
      dtype: bool
    - name: Heavy_Makeup
      dtype: bool
    - name: High_Cheekbones
      dtype: bool
    - name: Male
      dtype: bool
    - name: Mouth_Slightly_Open
      dtype: bool
    - name: Mustache
      dtype: bool
    - name: Narrow_Eyes
      dtype: bool
    - name: No_Beard
      dtype: bool
    - name: Oval_Face
      dtype: bool
    - name: Pale_Skin
      dtype: bool
    - name: Pointy_Nose
      dtype: bool
    - name: Receding_Hairline
      dtype: bool
    - name: Rosy_Cheeks
      dtype: bool
    - name: Sideburns
      dtype: bool
    - name: Smiling
      dtype: bool
    - name: Straight_Hair
      dtype: bool
    - name: Wavy_Hair
      dtype: bool
    - name: Wearing_Earrings
      dtype: bool
    - name: Wearing_Hat
      dtype: bool
    - name: Wearing_Lipstick
      dtype: bool
    - name: Wearing_Necklace
      dtype: bool
    - name: Wearing_Necktie
      dtype: bool
    - name: Young
      dtype: bool
  splits:
    - name: train
      num_bytes: 11236670416.5
      num_examples: 8500
    - name: test
      num_bytes: 1981621309.5
      num_examples: 1500
  download_size: 13157231113
  dataset_size: 13218291726
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
task_categories:
  - image-to-image
  - image-classification
tags:
  - lensless
  - computational-imaging
size_categories:
  - 1K<n<10K

Dataset for the paper: https://opg.optica.org/abstract.cfm?uri=pcAOP-2023-JTu4A.45

Data is measured with a computer monitor at 30 cm as shown below (except for the in-the-wild mug measurement which is measured at 12 cm).

After cloning and installing LenslessPiCam, ADMM reconstruction can be applied to the dataset with this script (handles dataset downloading from Hugging Face).

python scripts/recon/dataset.py -cn recon_celeba_digicam

The simulated PSF can be obtained and compared with the measured one with the following command:

python scripts/sim/digicam_psf.py \
    digicam.pattern=mask_pattern.npy \
    digicam.psf=psf_measured.png \
    digicam.ap_center=[59,76] \
    digicam.ap_shape=[19,26] \
    digicam.rotate=-0.8 \
    digicam.vertical_shift=-20 \
    digicam.horizontal_shift=-100 \
    sim.waveprop=False