---
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
---

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1t59uyZMMyCUYVHGXdqdlNlDlb--FL_3P?usp=sharing)

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).

![DigiCam setup](setup.png)

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).
```bash
python scripts/recon/dataset.py -cn recon_celeba_digicam
```

The [simulated PSF](https://huggingface.co/datasets/bezzam/DigiCam-CelebA-10K/blob/main/psf_simulated.png) can be obtained and compared with the measured one with the following command:
```bash
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
```