Merge branch 'modular_exp' into privacy

LCAV · Nov 14, 2024 · 061b21d · 061b21d
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diff --git a/README.rst b/README.rst
@@ -20,6 +20,10 @@ LenslessPiCam
       :target: https://lensless.readthedocs.io/en/latest/examples.html
       :alt: notebooks
 
+.. image:: https://img.shields.io/badge/Google_Slides-yellow
+      :target: https://docs.google.com/presentation/d/1PcNhMfjATSwcpbHUMrmc88ciQmheBJ7alz8hel8xnGU/edit?usp=sharing
+      :alt: slides
+
 .. image:: https://huggingface.co/datasets/huggingface/badges/resolve/main/powered-by-huggingface-dark.svg
       :target: https://huggingface.co/bezzam
       :alt: huggingface

diff --git a/configs/benchmark.yaml b/configs/benchmark.yaml
@@ -10,6 +10,7 @@ hydra:
 dataset: DiffuserCam   # DiffuserCam, DigiCamCelebA, HFDataset
 seed: 0
 batchsize: 1    # must be 1 for iterative approaches
+snr: null
 
 huggingface:
   repo: "bezzam/DigiCam-Mirflickr-MultiMask-25K"
@@ -42,6 +43,7 @@ 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]
+save_intermediate: False   # save intermediate results, i.e. after pre-processor and after camera inversion
 gamma_psf: 1.5    # gamma factor for PSF
 
 
@@ -57,6 +59,14 @@ admm:
   mu3: 4e-5
   tau: 0.0001
 
+# parameterize and perturb (Gilton et. al.)
+pnp: null
+# pnp:
+#   mu: 1e-3   # weight for distance from original model parameters
+#   lr: 3e-3   # learning rate for SGD
+#   n_iter: 100   # number of iterations
+#   model_path: null    # leave null to be overwritten in script
+
 
 # for DigiCamCelebA
 files:

diff --git a/configs/benchmark_diffusercam_mirflickr.yaml b/configs/benchmark_diffusercam_mirflickr.yaml
@@ -20,18 +20,20 @@ huggingface:
   single_channel_psf: True
 
 algorithms: [
-  "ADMM",
+  # "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:U5+Unet8M",
+  "hf:diffusercam:mirflickr:Unet8M+U5",
+  # "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",

diff --git a/configs/benchmark_digicam_celeba.yaml b/configs/benchmark_digicam_celeba.yaml
@@ -9,18 +9,19 @@ batchsize: 10
 device: "cuda:0"
 
 algorithms: [
-  "ADMM",
+  # "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",
+  # "hf:digicam:celeba_26k:U5+Unet8M_wave",
+  "hf:digicam:celeba_26k:Unet8M+U5_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",
@@ -37,6 +38,7 @@ 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
+  cache_dir: /dev/shm
   split_seed: 0
   test_size: 0.15
   downsample: 2

diff --git a/configs/benchmark_digicam_mirflickr_single.yaml b/configs/benchmark_digicam_mirflickr_single.yaml
@@ -9,7 +9,7 @@ device: "cuda:0"
 
 huggingface:
   repo: "bezzam/DigiCam-Mirflickr-SingleMask-25K"
-  cache_dir: /dev/shm
+  cache_dir: null
   psf: null   # null for simulating PSF
   image_res: [900, 1200]  # used during measurement
   rotate: True   # if measurement is upside-down
@@ -22,20 +22,21 @@ huggingface:
 
 
 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",
+  # "ADMM",
+
+  # # -- reconstructions trained on measured data
+  # "hf:digicam:mirflickr_single_25k:U5+Unet8M_wave",
+  "hf:digicam:mirflickr_single_25k:Unet8M+U5_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",
@@ -47,7 +48,7 @@ algorithms: [
   # "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave",
 ]
 
-save_idx: [1, 2, 4, 5, 9]
+save_idx: [1, 2, 4, 5, 9, 24, 33, 61]
 n_iter_range: [100]    # for ADMM
 
 # simulating PSF

diff --git a/configs/benchmark_tapecam_mirflickr.yaml b/configs/benchmark_tapecam_mirflickr.yaml
@@ -9,7 +9,7 @@ device: "cuda:0"
 
 huggingface:
   repo: "bezzam/TapeCam-Mirflickr-25K"
-  cache_dir: /dev/shm
+  cache_dir: null #/dev/shm
   psf: psf.png
   image_res: [900, 1200]  # used during measurement
   rotate: False   # if measurement is upside-down
@@ -23,16 +23,17 @@ huggingface:
 
 ## -- reconstructions trained with same dataset/system
 algorithms: [
-  "ADMM",
+  # "ADMM",
 
   # -- reconstructions trained on measured data
-  "hf:tapecam:mirflickr:U5+Unet8M",
-  "hf:tapecam:mirflickr:TrainInv+Unet8M",
-  "hf:tapecam:mirflickr:MMCN4M+Unet4M",
-  "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
-  "hf:tapecam:mirflickr:Unet4M+TrainInv+Unet4M",
-  "hf:tapecam:mirflickr:Unet2M+MMCN+Unet2M",
-  "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
+  # "hf:tapecam:mirflickr:U5+Unet8M",
+  "hf:tapecam:mirflickr:Unet8M+U5",
+  # "hf:tapecam:mirflickr:TrainInv+Unet8M",
+  # "hf:tapecam:mirflickr:MMCN4M+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
+  # "hf:tapecam:mirflickr:Unet4M+TrainInv+Unet4M",
+  # "hf:tapecam:mirflickr:Unet2M+MMCN+Unet2M",
+  # "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
   # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
   # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_aux1",
   # "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips",

diff --git a/configs/recon_digicam_mirflickr.yaml b/configs/recon_digicam_mirflickr.yaml
@@ -4,20 +4,20 @@ defaults:
   - _self_
 
 dataset: mirflickr_single_25k   # for loading model, "mirflickr_single_25k" or "mirflickr_multi_25k"
-cache_dir: /dev/shm
+cache_dir: null #/dev/shm
 
-# fn: null  # if not null, download this file from https://huggingface.co/datasets/bezzam/DigiCam-Mirflickr-SingleMask-25K/tree/main
+fn: null  # if not null, download this file from https://huggingface.co/datasets/bezzam/DigiCam-Mirflickr-SingleMask-25K/tree/main
 # fn: raw_box.png 
 # rotate: False
 # alignment:
 #   dim: [190, 260]
 #   top_left: [145, 130]
 
-fn: raw_stuffed_animals.png     
-rotate: False
-alignment:
-  dim: [200, 280]
-  top_left: [115, 120]
+# fn: raw_stuffed_animals.png     
+# rotate: False
+# alignment:
+#   dim: [200, 280]
+#   top_left: [115, 120]
 
 
 # - Learned reconstructions: see "lensless/recon/model_dict.py"
@@ -26,19 +26,20 @@ alignment:
 # model: MMCN4M+Unet4M_wave
 # model: MWDN8M_wave
 # model: U5+Unet8M_wave
+model: Unet8M+U5_wave
 # model: Unet4M+TrainInv+Unet4M_wave
 # model: Unet2M+MMCN+Unet2M_wave
 # model: Unet4M+U5+Unet4M_wave
 # model: Unet4M+U10+Unet4M_wave
 
-# --- dataset: mirflickr_multi_25k
-model: Unet4M+U5+Unet4M_wave
+# # --- dataset: mirflickr_multi_25k
+# model: Unet4M+U5+Unet4M_wave
 
 # # -- for ADMM with fixed parameters
 # model: admm
 # n_iter: 100
 
 device: cuda:0
-n_trials: 1   # to get average inference time
+n_trials: 100   # to get average inference time
 idx: 1    # index from test set to reconstruct
 save: True
diff --git a/docs/source/examples.rst b/docs/source/examples.rst
@@ -7,6 +7,16 @@ but they may not be the best way to get started with the library.
 The following notebooks aim to provide a more interactive and intuitive
 way to explore the different functionalities of the library.
 
+This notebook provides a general overview of main features 
+(downloading/using datasets, PSF analysis/design, image recovery) 
+of the library: 
+(`GitHub <https://github.com/LCAV/LenslessPiCam/blob/main/notebook/lenslesspicam_demo.ipynb>`__,
+`Google Colab <https://colab.research.google.com/drive/1q56Ht647JD5wocnrcT7rH5TCNK7FKmtH?usp=sharing>`__).
+`Here <https://docs.google.com/presentation/d/1PcNhMfjATSwcpbHUMrmc88ciQmheBJ7alz8hel8xnGU/edit?pli=1#slide=id.p>`__
+are accompanying slides that were given at PhD course to introduce computational lensless imaging.
+
+The ones below are more specific and focus on different aspects of lensless cameras.
+
 System / Hardware
 -----------------