Adding new reconstruction methods and exposing different parameters for PSF simulation.

.github/workflows/python_pycsou.yml

@@ -20,7 +20,7 @@ jobs:
       fail-fast: false
       max-parallel: 12
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-12, windows-latest]
         python-version: [3.9, "3.10"]
     steps:
     - uses: actions/checkout@v3

CHANGELOG.rst

@@ -15,6 +15,17 @@ Added
 
 - Option to pass background image to ``utils.io.load_data``.
 - Option to set image resolution with ``hardware.utils.display`` function.
+- Auxiliary of reconstructing output from pre-processor (not working).
+- Option to set focal range for MultiLensArray.
+- Optional to remove deadspace modelling for programmable mask.
+- Compensation branch for unrolled ADMM: https://ieeexplore.ieee.org/abstract/document/9546648
+- Multi-Wiener deconvolution network: https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-23-39088&id=541387
+- Option to skip pre-processor and post-processor at inference time.
+- Option to set difference learning rate schedules, e.g. ADAMW, exponential decay, Cosine decay with warmup.
+- Various augmentations for training: random flipping, random rotate, and random shifts. Latter two don't work well since new regions appear that throw off PSF/LSI modeling.
+- HFSimulated object for simulating lensless data from ground-truth and PSF.
+- Option to set cache directory for Hugging Face datasets.
+- Option to initialize training with another model.
 
 Changed
 ~~~~~~~
@@ -24,7 +35,9 @@ Changed
 Bugfix
 ~~~~~~
 
-- Nothing
+- Computation of average metric in batches.
+- Support for grayscale PSF for RealFFTConvolve2D.
+- Calling model.eval() before inference, and model.train() before training.
 
 
 1.0.7 - (2024-05-14)

README.rst

@@ -44,7 +44,7 @@ The toolkit includes:
 * Camera assembly tutorials (`link <https://lensless.readthedocs.io/en/latest/building.html>`__).
 * Measurement scripts (`link <https://lensless.readthedocs.io/en/latest/measurement.html>`__).
 * Dataset preparation and loading tools, with `Hugging Face <https://huggingface.co/bezzam>`__ integration (`slides <https://docs.google.com/presentation/d/18h7jTcp20jeoiF8dJIEcc7wHgjpgFgVxZ_bJ04W55lg/edit?usp=sharing>`__ on uploading a dataset to Hugging Face with `this script <https://github.com/LCAV/LenslessPiCam/blob/main/scripts/data/upload_dataset_huggingface.py>`__).
-* `Reconstruction algorithms <https://lensless.readthedocs.io/en/latest/reconstruction.html>`__ (e.g. FISTA, ADMM, unrolled algorithms, trainable inversion, pre- and post-processors).
+* `Reconstruction algorithms <https://lensless.readthedocs.io/en/latest/reconstruction.html>`__ (e.g. FISTA, ADMM, unrolled algorithms, trainable inversion, , multi-Wiener deconvolution network, pre- and post-processors).
 * `Training script <https://github.com/LCAV/LenslessPiCam/blob/main/scripts/recon/train_learning_based.py>`__ for learning-based reconstruction.
 * `Pre-trained models <https://github.com/LCAV/LenslessPiCam/blob/main/lensless/recon/model_dict.py>`__ that can be loaded from `Hugging Face <https://huggingface.co/bezzam>`__, for example in `this script <https://github.com/LCAV/LenslessPiCam/blob/main/scripts/recon/diffusercam_mirflickr.py>`__.
 * Mask `design <https://lensless.readthedocs.io/en/latest/mask.html>`__ and `fabrication <https://lensless.readthedocs.io/en/latest/fabrication.html>`__ tools.

configs/benchmark.yaml

@@ -9,15 +9,23 @@ hydra:
 
 dataset: DiffuserCam   # DiffuserCam, DigiCamCelebA, HFDataset
 seed: 0
+batchsize: 1    # must be 1 for iterative approaches
 
 huggingface:
   repo: "bezzam/DigiCam-Mirflickr-MultiMask-25K"
+  cache_dir: null    # where to read/write dataset. Defaults to `"~/.cache/huggingface/datasets"`.
+  psf: null   # null for simulating PSF
   image_res: [900, 1200]  # used during measurement
   rotate: True   # if measurement is upside-down
+  flipud: False
+  flip_lensed: False   # if rotate or flipud is True, apply to lensed
   alignment:
     top_left: [80, 100]  # height, width
     height: 200
   downsample: 1
+  downsample_lensed: 1
+  split_seed: null
+  single_channel_psf: False
 
 device: "cuda"
 # numbers of iterations to benchmark
@@ -33,6 +41,8 @@ algorithms: ["ADMM", "ADMM_Monakhova2019", "FISTA"] #["ADMM", "ADMM_Monakhova201
 baseline: "MONAKHOVA 100iter"
 
 save_idx: [0, 1, 2, 3, 4]   # provide index of files to save e.g. [1, 5, 10]
+gamma_psf: 1.5    # gamma factor for PSF
+
 
 # Hyperparameters
 nesterov:
@@ -86,7 +96,8 @@ simulation:
   # mask2sensor: 9e-3     # mask2sensor: 4e-3  
   # -- for CelebA
   scene2mask: 0.25   # [m]
-  mask2sensor: 0.002   # [m]     
+  mask2sensor: 0.002   # [m] 
+  deadspace: True    # whether to account for deadspace for programmable mask      
   # see waveprop.devices
   use_waveprop: False    # for PSF simulation
   sensor: "rpi_hq"

configs/benchmark_diffusercam_mirflickr.yaml

@@ -0,0 +1,63 @@
+# python scripts/eval/benchmark_recon.py -cn benchmark_diffusercam_mirflickr
+defaults:
+  - benchmark
+  - _self_
+
+dataset: HFDataset
+batchsize: 4
+device: "cuda:0"
+
+huggingface:
+  repo: "bezzam/DiffuserCam-Lensless-Mirflickr-Dataset-NORM"
+  psf: psf.tiff
+  image_res: null
+  rotate: False   # if measurement is upside-down
+  alignment: null
+  downsample: 2
+  downsample_lensed: 2
+  flipud: True
+  flip_lensed: True 
+  single_channel_psf: True
+
+algorithms: [
+  "ADMM",
+
+  ## -- reconstructions trained on DiffuserCam measured
+  "hf:diffusercam:mirflickr:U5+Unet8M",
+  "hf:diffusercam:mirflickr:TrainInv+Unet8M",
+  "hf:diffusercam:mirflickr:MMCN4M+Unet4M",
+  "hf:diffusercam:mirflickr:MWDN8M",
+  "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M",
+  "hf:diffusercam:mirflickr:Unet4M+TrainInv+Unet4M",
+  "hf:diffusercam:mirflickr:Unet2M+MMCN+Unet2M",
+  "hf:diffusercam:mirflickr:Unet2M+MWDN6M",
+  "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M_ft_tapecam",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M_ft_tapecam_post",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M_ft_tapecam_pre",
+
+  # ## -- reconstruction trained on DiffuserCam simulated
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_tapecam",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_tapecam_post",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_tapecam_pre",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_digicam_multi_post",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_digicam_multi_pre",
+  # "hf:diffusercam:mirflickr_sim:Unet4M+U5+Unet4M_ft_digicam_multi",
+
+  # ## -- reconstructions trained on other datasets/systems
+  # "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
+  # "hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_aux1",
+  # "hf:digicam:mirflickr_multi_25k:Unet4M+U10+Unet4M_wave",
+  # "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave",
+]
+
+save_idx: [0, 1, 3, 4, 8, 45, 58, 63]
+n_iter_range: [100]    # for ADMM
+

configs/benchmark_digicam_celeba.yaml

@@ -0,0 +1,62 @@
+# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_celeba
+defaults:
+  - benchmark
+  - _self_
+
+
+dataset: HFDataset
+batchsize: 10
+device: "cuda:0"
+
+algorithms: [
+  "ADMM",
+
+  ## -- reconstructions trained on measured data
+  "hf:digicam:celeba_26k:U5+Unet8M_wave",
+  "hf:digicam:celeba_26k:TrainInv+Unet8M_wave",
+  "hf:digicam:celeba_26k:MWDN8M_wave",
+  "hf:digicam:celeba_26k:MMCN4M+Unet4M_wave",
+  "hf:digicam:celeba_26k:Unet2M+MWDN6M_wave",
+  "hf:digicam:celeba_26k:Unet4M+TrainInv+Unet4M_wave",
+  "hf:digicam:celeba_26k:Unet2M+MMCN+Unet2M_wave",
+  "hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave",
+  "hf:digicam:celeba_26k:Unet4M+U10+Unet4M_wave",
+
+  # # -- reconstructions trained on other datasets/systems
+  # "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
+]
+
+save_idx: [0, 2, 3, 4, 9]
+n_iter_range: [100]    # for ADMM
+
+huggingface:
+  repo: bezzam/DigiCam-CelebA-26K
+  psf: psf_simulated_waveprop.png    # psf_simulated_waveprop.png, psf_simulated.png, psf_measured.png
+  split_seed: 0
+  test_size: 0.15
+  downsample: 2
+  image_res: null
+
+  alignment:
+    top_left: null
+    height: null
+
+    # cropping when there is no downsampling
+    crop:
+      vertical: [0, 525]
+      horizontal: [265, 695]
+
+    # for prepping ground truth data
+    simulation:
+      scene2mask: 0.25   # [m]
+      mask2sensor: 0.002   # [m]
+      object_height: 0.33   # [m]
+      sensor: "rpi_hq"
+      # shifting when there is no files to downsample
+      vertical_shift: -117
+      horizontal_shift: -25

configs/benchmark_digicam_mirflickr_multi.yaml

@@ -0,0 +1,60 @@
+# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_mirflickr_multi
+defaults:
+  - benchmark
+  - _self_
+
+
+dataset: HFDataset
+batchsize: 4
+device: "cuda:0"
+
+huggingface:
+  repo: "bezzam/DigiCam-Mirflickr-MultiMask-25K"
+  psf: null   # null for simulating PSF
+  image_res: [900, 1200]  # used during measurement
+  rotate: True   # if measurement is upside-down
+  flipud: False
+  flip_lensed: False   # if rotate or flipud is True, apply to lensed
+  alignment:
+    top_left: [80, 100]  # height, width
+    height: 200
+  downsample: 1
+
+algorithms: [
+  "ADMM",
+
+  ## -- reconstructions trained on measured data 
+  "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave",
+  "hf:digicam:mirflickr_multi_25k:Unet4M+U10+Unet4M_wave",
+  "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_aux1",
+  "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_flips",
+
+  # ## -- reconstructions trained on other datasets/systems
+  # "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
+  # "hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_aux1",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips_rotate10",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_ft_flips",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_ft_flips_rotate10",
+]
+
+# # -- to only use output from unrolled
+# hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_aux1:
+#   skip_post: True
+#   skip_pre: True
+
+save_idx: [1, 2, 4, 5, 9, 24, 33, 61]
+n_iter_range: [100]    # for ADMM
+
+# simulating PSF
+simulation:
+  use_waveprop: True
+  deadspace: True
+  scene2mask: 0.3
+  mask2sensor: 0.002

configs/benchmark_digicam_mirflickr_single.yaml

@@ -0,0 +1,58 @@
+# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_mirflickr_single
+defaults:
+  - benchmark
+  - _self_
+
+dataset: HFDataset
+batchsize: 4
+device: "cuda:0"
+
+huggingface:
+  repo: "bezzam/DigiCam-Mirflickr-SingleMask-25K"
+  cache_dir: /dev/shm
+  psf: null   # null for simulating PSF
+  image_res: [900, 1200]  # used during measurement
+  rotate: True   # if measurement is upside-down
+  flipud: False
+  flip_lensed: False   # if rotate or flipud is True, apply to lensed
+  alignment:
+    top_left: [80, 100]  # height, width
+    height: 200
+  downsample: 1
+
+
+algorithms: [
+  "ADMM",
+
+  # -- reconstructions trained on measured data
+  "hf:digicam:mirflickr_single_25k:U5+Unet8M_wave",
+  "hf:digicam:mirflickr_single_25k:TrainInv+Unet8M_wave",
+  "hf:digicam:mirflickr_single_25k:MMCN4M+Unet4M_wave",
+  "hf:digicam:mirflickr_single_25k:MWDN8M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet4M+TrainInv+Unet4M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet2M+MMCN+Unet2M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet2M+MWDN6M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips",
+  "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips_rotate10",
+
+  # ## -- reconstructions trained on other datasets/systems
+  # "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
+  # "hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:diffusercam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave",
+]
+
+save_idx: [1, 2, 4, 5, 9]
+n_iter_range: [100]    # for ADMM
+
+# simulating PSF
+simulation:
+  use_waveprop: True
+  deadspace: True
+  scene2mask: 0.3
+  mask2sensor: 0.002