denoising testing code

Author: zhangyi-3

.gitignore

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 .*/
 .DS*
+*.pyc

Denoising/Datasets/README.md

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+For training and testing, your directory structure should look like this
+    
+
+`Datasets` <br/>
+ `├──train`  <br/>
+     `├──DFWB`   <br/>
+     `└──SIDD`   <br/>
+          `├──input_crops`   <br/>
+          `└──target_crops`   <br/>
+ `├──val`  <br/>
+     `└──SIDD`   <br/>
+          `├──input_crops`   <br/>
+          `└──target_crops`   <br/>
+ `└──test`  <br/>
+     `├──BSD68`   <br/>
+     `├──CBSD68`   <br/>
+     `├──Kodak`   <br/>
+     `├──McMaster`   <br/>
+     `├──Set12`   <br/>
+     `├──Urban100`   <br/>
+     `├──SIDD`   <br/>
+          `├──ValidationNoisyBlocksSrgb.mat`   <br/>
+          `└──ValidationGtBlocksSrgb.mat`   <br/>
+     `├──DND`   <br/>
+          `├──info.mat`   <br/>
+          `└──images_srgb`   <br/>
+               `├──0001.mat`   <br/>
+               `├──0002.mat`   <br/>
+               `├── ...    `   <br/>
+               `└──0050.mat` 

Denoising/Options/gau_color_15.yml

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+# general settings
+name: gaum-kb333
+model_type: ImageCleanModel
+scale: 1
+num_gpu: 8  # set num_gpu: 0 for cpu mode
+manual_seed: 100
+
+# dataset and data loader settings
+datasets:
+  train:
+    name: TrainSet
+    type: Dataset_GaussianDenoising
+    sigma_type: random
+    sigma_range: 15
+    in_ch: 3    ## RGB image
+    dataroot_gt: s3://zhangyi/images/val
+    dataroot_lq: none
+    geometric_augs: true
+
+    filename_tmpl: '{}'
+    io_backend:
+      type: petrel
+
+    # data loader
+    use_shuffle: true
+    num_worker_per_gpu: 8
+    batch_size_per_gpu: 8
+
+    ### -------------Progressive training--------------------------
+    mini_batch_sizes: [8,5,3,2,1,1]             # Batch size per gpu
+    iters: [92000,64000,48000,36000,36000,24000]
+    gt_size: 384   # Max patch size for progressive training
+    gt_sizes: [128,160,192,256,320,384]  # Patch sizes for progressive training.
+    ### ------------------------------------------------------------
+
+    ### ------- Training on single fixed-patch size 128x128---------
+    # mini_batch_sizes: [8]
+    # iters: [300000]
+    # gt_size: 128
+    # gt_sizes: [128]
+    ### ------------------------------------------------------------
+
+    dataset_enlarge_ratio: 1
+    prefetch_mode: ~
+
+  val:
+    name: ValSet
+    type: Dataset_GaussianDenoising
+    sigma_test: 25
+    in_ch: 3  ## RGB image
+    dataroot_gt: s3://zhangyi/restormer-train/Denoising/Datasets/test/CBSD68
+    dataroot_lq: none
+    io_backend:
+      type: petrel
+
+# network structures
+network_g:
+  type: KBNet_s
+
+# path
+path:
+  pretrain_network_g: pretrained_models/gau_color_15.pth
+  strict_load_g: true
+  resume_state: ~
+
+# training settings
+train:
+  total_iter: 300000
+  warmup_iter: -1 # no warm up
+  use_grad_clip: true
+
+  # Split 300k iterations into two cycles.
+  # 1st cycle: fixed 3e-4 LR for 92k iters.
+  # 2nd cycle: cosine annealing (3e-4 to 1e-6) for 208k iters.
+  scheduler:
+    type: CosineAnnealingRestartCyclicLR
+    periods: [92000, 208000]
+    restart_weights: [1,1]
+    eta_mins: [0.0003,0.000001]
+
+  mixing_augs:
+    mixup: true
+    mixup_beta: 1.2
+    use_identity: true
+
+  optim_g:
+    type: AdamW
+    lr: !!float 3e-4
+    weight_decay: !!float 1e-4
+    betas: [0.9, 0.999]
+
+  # losses
+  pixel_opt:
+    type: L1Loss
+    loss_weight: 1
+    reduction: mean
+
+# validation settings
+val:
+  window_size: 8
+  val_freq: !!float 4e3
+  save_img: false
+  rgb2bgr: true
+  use_image: false
+  max_minibatch: 8
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false
+
+# logging settings
+logger:
+  print_freq: 1000
+  save_checkpoint_freq: !!float 1e3
+  use_tb_logger: true
+  wandb:
+    project: ~
+    resume_id: ~
+
+# dist training settings
+dist_params:
+  backend: nccl
+  port: 29500

Denoising/Options/gau_color_25.yml

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+# general settings
+name: gaum-kb333
+model_type: ImageCleanModel
+scale: 1
+num_gpu: 8  # set num_gpu: 0 for cpu mode
+manual_seed: 100
+
+# dataset and data loader settings
+datasets:
+  train:
+    name: TrainSet
+    type: Dataset_GaussianDenoising
+    sigma_type: random
+    sigma_range: 25
+    in_ch: 3    ## RGB image
+    dataroot_gt: s3://zhangyi/images/val
+    dataroot_lq: none
+    geometric_augs: true
+
+    filename_tmpl: '{}'
+    io_backend:
+      type: petrel
+
+    # data loader
+    use_shuffle: true
+    num_worker_per_gpu: 8
+    batch_size_per_gpu: 8
+
+    ### -------------Progressive training--------------------------
+    mini_batch_sizes: [8,5,3,2,1,1]             # Batch size per gpu
+    iters: [92000,64000,48000,36000,36000,24000]
+    gt_size: 384   # Max patch size for progressive training
+    gt_sizes: [128,160,192,256,320,384]  # Patch sizes for progressive training.
+    ### ------------------------------------------------------------
+
+    ### ------- Training on single fixed-patch size 128x128---------
+    # mini_batch_sizes: [8]
+    # iters: [300000]
+    # gt_size: 128
+    # gt_sizes: [128]
+    ### ------------------------------------------------------------
+
+    dataset_enlarge_ratio: 1
+    prefetch_mode: ~
+
+  val:
+    name: ValSet
+    type: Dataset_GaussianDenoising
+    sigma_test: 25
+    in_ch: 3  ## RGB image
+    dataroot_gt: s3://zhangyi/restormer-train/Denoising/Datasets/test/CBSD68
+    dataroot_lq: none
+    io_backend:
+      type: petrel
+
+# network structures
+network_g:
+  type: KBNet_s
+
+# path
+path:
+  pretrain_network_g: pretrained_models/gau_color_25.pth
+  strict_load_g: true
+  resume_state: ~
+
+# training settings
+train:
+  total_iter: 300000
+  warmup_iter: -1 # no warm up
+  use_grad_clip: true
+
+  # Split 300k iterations into two cycles.
+  # 1st cycle: fixed 3e-4 LR for 92k iters.
+  # 2nd cycle: cosine annealing (3e-4 to 1e-6) for 208k iters.
+  scheduler:
+    type: CosineAnnealingRestartCyclicLR
+    periods: [92000, 208000]
+    restart_weights: [1,1]
+    eta_mins: [0.0003,0.000001]
+
+  mixing_augs:
+    mixup: true
+    mixup_beta: 1.2
+    use_identity: true
+
+  optim_g:
+    type: AdamW
+    lr: !!float 3e-4
+    weight_decay: !!float 1e-4
+    betas: [0.9, 0.999]
+
+  # losses
+  pixel_opt:
+    type: L1Loss
+    loss_weight: 1
+    reduction: mean
+
+# validation settings
+val:
+  window_size: 8
+  val_freq: !!float 4e3
+  save_img: false
+  rgb2bgr: true
+  use_image: false
+  max_minibatch: 8
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false
+
+# logging settings
+logger:
+  print_freq: 1000
+  save_checkpoint_freq: !!float 1e3
+  use_tb_logger: true
+  wandb:
+    project: ~
+    resume_id: ~
+
+# dist training settings
+dist_params:
+  backend: nccl
+  port: 29500