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Organize configs into subfolder, easier API for set GPUs for training.
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‎configs/benchmark.yaml ‎configs/benchmark/defaults.yaml

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‎configs/benchmark_diffusercam_mirflickr.yaml ‎configs/benchmark/diffusercam.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_diffusercam_mirflickr
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# python scripts/eval/benchmark_recon.py -cn diffusercam
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defaults:
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- benchmark
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- defaults
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- _self_
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dataset: HFDataset
@@ -24,15 +24,15 @@ algorithms: [
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## -- reconstructions trained on DiffuserCam measured
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"hf:diffusercam:mirflickr:U5+Unet8M",
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"hf:diffusercam:mirflickr:Unet8M+U5",
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"hf:diffusercam:mirflickr:TrainInv+Unet8M",
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"hf:diffusercam:mirflickr:MMCN4M+Unet4M",
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"hf:diffusercam:mirflickr:MWDN8M",
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# "hf:diffusercam:mirflickr:Unet8M+U5",
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# "hf:diffusercam:mirflickr:TrainInv+Unet8M",
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# "hf:diffusercam:mirflickr:MMCN4M+Unet4M",
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# "hf:diffusercam:mirflickr:MWDN8M",
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"hf:diffusercam:mirflickr:Unet4M+U5+Unet4M",
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"hf:diffusercam:mirflickr:Unet4M+TrainInv+Unet4M",
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"hf:diffusercam:mirflickr:Unet2M+MMCN+Unet2M",
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"hf:diffusercam:mirflickr:Unet2M+MWDN6M",
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"hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
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# "hf:diffusercam:mirflickr:Unet4M+TrainInv+Unet4M",
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# "hf:diffusercam:mirflickr:Unet2M+MMCN+Unet2M",
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# "hf:diffusercam:mirflickr:Unet2M+MWDN6M",
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# "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",
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"hf:diffusercam:mirflickr:Unet4M+U5+Unet4M_psfNN",
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# # -- benchmark PSF error

‎configs/benchmark_digicam_mirflickr_single.yaml ‎configs/benchmark/digicam.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_mirflickr_single
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# python scripts/eval/benchmark_recon.py -cn digicam
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defaults:
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- benchmark
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- defaults
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- _self_
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dataset: HFDataset
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# # -- reconstructions trained on measured data
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"hf:digicam:mirflickr_single_25k:U5+Unet8M_wave",
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"hf:digicam:mirflickr_single_25k:Unet8M+U5_wave",
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"hf:digicam:mirflickr_single_25k:TrainInv+Unet8M_wave",
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"hf:digicam:mirflickr_single_25k:MMCN4M+Unet4M_wave",
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"hf:digicam:mirflickr_single_25k:MWDN8M_wave",
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"hf:digicam:mirflickr_single_25k:Unet4M+TrainInv+Unet4M_wave",
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# "hf:digicam:mirflickr_single_25k:Unet8M+U5_wave",
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# "hf:digicam:mirflickr_single_25k:TrainInv+Unet8M_wave",
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# "hf:digicam:mirflickr_single_25k:MMCN4M+Unet4M_wave",
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# "hf:digicam:mirflickr_single_25k:MWDN8M_wave",
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# "hf:digicam:mirflickr_single_25k:Unet4M+TrainInv+Unet4M_wave",
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"hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave",
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"hf:digicam:mirflickr_single_25k:Unet2M+MMCN+Unet2M_wave",
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"hf:digicam:mirflickr_single_25k:Unet2M+MWDN6M_wave",
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"hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
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# "hf:digicam:mirflickr_single_25k:Unet2M+MMCN+Unet2M_wave",
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# "hf:digicam:mirflickr_single_25k:Unet2M+MWDN6M_wave",
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# "hf:digicam:mirflickr_single_25k:Unet4M+U10+Unet4M_wave",
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"hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_psfNN",
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"hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips",
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"hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips_rotate10",
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"hf:digicam:mirflickr_single_25k:Unet8M_wave_v2",
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# "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips",
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# "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_flips_rotate10",
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# "hf:digicam:mirflickr_single_25k:Unet8M_wave_v2",
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# ## -- reconstructions trained on other datasets/systems
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# "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",

‎configs/benchmark_digicam_celeba.yaml ‎configs/benchmark/digicam_celeba.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_celeba
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defaults:
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- benchmark
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- defaults
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- _self_
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dataset: HFDataset
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batchsize: 10
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device: "cuda:1"
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device: "cuda"
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algorithms: [
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# "ADMM",
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## -- reconstructions trained on measured data
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"hf:digicam:celeba_26k:U5+Unet8M_wave",
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"hf:digicam:celeba_26k:Unet8M+U5_wave",
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"hf:digicam:celeba_26k:TrainInv+Unet8M_wave",
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"hf:digicam:celeba_26k:MWDN8M_wave",
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"hf:digicam:celeba_26k:MMCN4M+Unet4M_wave",
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"hf:digicam:celeba_26k:Unet2M+MWDN6M_wave",
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"hf:digicam:celeba_26k:Unet4M+TrainInv+Unet4M_wave",
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"hf:digicam:celeba_26k:Unet2M+MMCN+Unet2M_wave",
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# "hf:digicam:celeba_26k:Unet8M+U5_wave",
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# "hf:digicam:celeba_26k:TrainInv+Unet8M_wave",
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# "hf:digicam:celeba_26k:MWDN8M_wave",
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# "hf:digicam:celeba_26k:MMCN4M+Unet4M_wave",
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# "hf:digicam:celeba_26k:Unet2M+MWDN6M_wave",
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# "hf:digicam:celeba_26k:Unet4M+TrainInv+Unet4M_wave",
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# "hf:digicam:celeba_26k:Unet2M+MMCN+Unet2M_wave",
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"hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave",
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"hf:digicam:celeba_26k:Unet4M+U5+Unet4M_wave_psfNN",
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"hf:digicam:celeba_26k:Unet4M+U10+Unet4M_wave",
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# "hf:digicam:celeba_26k:Unet4M+U10+Unet4M_wave",
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# # -- reconstructions trained on other datasets/systems
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# "hf:diffusercam:mirflickr:Unet4M+U10+Unet4M",

‎configs/benchmark_digicam_mirflickr_multi.yaml ‎configs/benchmark/digicam_multimask.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_mirflickr_multi
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# python scripts/eval/benchmark_recon.py -cn digicam_multimask
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defaults:
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- benchmark
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- defaults
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- _self_
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dataset: HFDataset
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batchsize: 4
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device: "cuda:0"
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downsample: 1
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algorithms: [
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"ADMM",
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# "ADMM",
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## -- reconstructions trained on measured data
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"hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave",
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"hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_psfNN",
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"hf:digicam:mirflickr_multi_25k:Unet4M+U10+Unet4M_wave",
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"hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_aux1",
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"hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_flips",
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"hf:digicam:mirflickr_multi_25k:Unet8M_wave_v2",
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# "hf:digicam:mirflickr_multi_25k:Unet4M+U10+Unet4M_wave",
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# "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_aux1",
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# "hf:digicam:mirflickr_multi_25k:Unet4M+U5+Unet4M_wave_flips",
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# "hf:digicam:mirflickr_multi_25k:Unet8M_wave_v2",
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# ## -- reconstructions trained on other datasets/systems
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# "hf:digicam:mirflickr_single_25k:Unet4M+U5+Unet4M_wave_psfNN",

‎configs/benchmark_digicam_mirflickr_pnp.yaml ‎configs/benchmark/digicam_parameter_and_perturb.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_digicam_mirflickr_pnp
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# python scripts/eval/benchmark_recon.py -cn digicam_parameter_and_perturb
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defaults:
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- benchmark
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- defaults
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- _self_
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‎configs/benchmark/multilens_ambient.yaml

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# python scripts/eval/benchmark_recon.py -cn multilens_ambient
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defaults:
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- defaults
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- _self_
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6+
dataset: HFDataset
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batchsize: 8
8+
device: "cuda:0"
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huggingface:
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repo: Lensless/MultiLens-Mirflickr-Ambient
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cache_dir: /dev/shm
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psf: psf.png
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image_res: [600, 600] # used during measurement
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rotate: False # if measurement is upside-down
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alignment:
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top_left: [118, 220] # height, width
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height: 123
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use_background: True
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21+
## -- reconstructions trained with same dataset/system
22+
algorithms: [
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# "ADMM",
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"hf:multilens:mirflickr_ambient:U5+Unet8M",
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# "hf:multilens:mirflickr_ambient:U5+Unet8M_direct_sub",
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# "hf:multilens:mirflickr_ambient:U5+Unet8M_learned_sub",
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"hf:multilens:mirflickr_ambient:Unet4M+U5+Unet4M",
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# "hf:multilens:mirflickr_ambient:Unet4M+U5+Unet4M_direct_sub",
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# "hf:multilens:mirflickr_ambient:Unet4M+U5+Unet4M_learned_sub",
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"hf:multilens:mirflickr_ambient:Unet4M+U5+Unet4M_concat",
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# "hf:multilens:mirflickr_ambient:TrainInv+Unet8M",
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# "hf:multilens:mirflickr_ambient:TrainInv+Unet8M_learned_sub",
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# "hf:multilens:mirflickr_ambient:Unet4M+TrainInv+Unet4M",
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# "hf:multilens:mirflickr_ambient:Unet4M+TrainInv+Unet4M_learned_sub",
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# "hf:multilens:mirflickr_ambient:Unet4M+TrainInv+Unet4M_concat",
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# "hf:multilens:mirflickr_ambient:TrainInv+Unet8M_direct_sub",
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# "hf:multilens:mirflickr_ambient:Unet4M+TrainInv+Unet4M_direct_sub",
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]
39+
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save_idx: [
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1, 2, 4, 5, 9, 64, # bottom right
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# 2141, 2155, 2162, 2225, 2502, 2602, # top right (door, flower, cookies, wolf, plush, sky)
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# 3262, 3304, 3438, 3451, 3644, 3667 # bottom left (pancakes, flower, grapes, pencils, bird, sign)
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]
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n_iter_range: [100] # for ADMM

‎configs/benchmark_tapecam_mirflickr.yaml ‎configs/benchmark/tapecam.yaml

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# python scripts/eval/benchmark_recon.py -cn benchmark_tapecam_mirflickr
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# python scripts/eval/benchmark_recon.py -cn tapecam
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defaults:
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- benchmark
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- defaults
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- _self_
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dataset: HFDataset
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batchsize: 4
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device: "cuda:1"
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device: "cuda:0"
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huggingface:
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repo: "bezzam/TapeCam-Mirflickr-25K"
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# -- reconstructions trained on measured data
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"hf:tapecam:mirflickr:U5+Unet8M",
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"hf:tapecam:mirflickr:Unet8M+U5",
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"hf:tapecam:mirflickr:TrainInv+Unet8M",
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"hf:tapecam:mirflickr:MMCN4M+Unet4M",
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# "hf:tapecam:mirflickr:Unet8M+U5",
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# "hf:tapecam:mirflickr:TrainInv+Unet8M",
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# "hf:tapecam:mirflickr:MMCN4M+Unet4M",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M",
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"hf:tapecam:mirflickr:Unet4M+TrainInv+Unet4M",
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"hf:tapecam:mirflickr:Unet2M+MMCN+Unet2M",
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"hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M_aux1",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
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# "hf:tapecam:mirflickr:Unet4M+TrainInv+Unet4M",
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# "hf:tapecam:mirflickr:Unet2M+MMCN+Unet2M",
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# "hf:tapecam:mirflickr:Unet4M+U10+Unet4M",
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# "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
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# "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_aux1",
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# "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips",
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# "hf:tapecam:mirflickr:Unet4M+U5+Unet4M_flips_rotate10",
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"hf:tapecam:mirflickr:Unet4M+U5+Unet4M_psfNN",
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# # below models need `single_channel_psf = True`

‎configs/benchmark_multilens_mirflickr_ambient.yaml

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‎configs/collect_dataset.yaml ‎configs/dataset/collect_dataset.yaml

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‎configs/collect_dataset_background.yaml ‎configs/dataset/collect_dataset_background.yaml

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‎configs/collect_mirflickr_fza.yaml ‎configs/dataset/collect_mirflickr_fza.yaml

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‎configs/collect_mirflickr_multimask.yaml ‎configs/dataset/collect_mirflickr_multimask.yaml

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‎configs/collect_mirflickr_singlemask.yaml ‎configs/dataset/collect_mirflickr_singlemask.yaml

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‎configs/upload_dataset_huggingface.yaml ‎configs/dataset/upload_dataset_huggingface.yaml

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‎configs/upload_diffusercam_huggingface.yaml ‎configs/dataset/upload_diffusercam_huggingface.yaml

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‎configs/upload_digicam_10k.yaml ‎configs/dataset/upload_digicam_10k.yaml

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‎configs/upload_digicam_26k.yaml ‎configs/dataset/upload_digicam_26k.yaml

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‎configs/upload_digicam_mirflickr_multimask.yaml ‎configs/dataset/upload_digicam_mirflickr_multimask.yaml

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‎configs/upload_digicam_mirflickr_singlemask.yaml ‎configs/dataset/upload_digicam_mirflickr_singlemask.yaml

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‎configs/upload_multilens_mirflickr_ambient.yaml ‎configs/dataset/upload_multilens_mirflickr_ambient.yaml

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‎configs/upload_tapecam_mirflickr.yaml ‎configs/dataset/upload_tapecam_mirflickr.yaml

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‎configs/upload_tapecam_mirflickr_ambient.yaml ‎configs/dataset/upload_tapecam_mirflickr_ambient.yaml

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‎configs/diffusercam_mirflickr_single_admm.yaml

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‎configs/fine-tune_PSF.yaml

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‎configs/finetune_tape_for_diffuser.yaml

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‎configs/admm_pnp.yaml ‎configs/recon/admm_pnp.yaml

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‎configs/apgd_l1.yaml ‎configs/recon/apgd_l1.yaml

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# python scripts/recon/apgd_pycsou.py -cn apgd_l1
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defaults:
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- defaults_recon
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- defaults
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- _self_
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preprocess:

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