model weights upload in pytorch and onnx formats

LINKNET/CEM/LinkNet_RGB_CEM_A/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_CEM_A
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - cem
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_cem
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/CEM/LinkNet_RGB_CEM_A/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,cem]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_CEM_A
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,cem],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_CEM_A,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_CEM_A
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/CEM/LinkNet_RGB_CEM_A/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,cem]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_CEM_A
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/CEM/LinkNet_RGB_CEM_A/final_checkpoint_model_40ep.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a9ed4d07a14c66854ba77f3509716b7a3b8fdfd20eb722df718d144deac5b38a
+size 10591877

LINKNET/CEM/LinkNet_RGB_CEM_A/final_checkpoint_model_40ep.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:983240a72f36e1b74d2e86dcd94d2ef2e569658d5df1efb56baa7a927b0701ae
+size 3503504

LINKNET/CEM/LinkNet_RGB_CEM_A/results_test_40ep.json

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+{"auprc": 0.426147024268304, "auprc_easy": 0.7016938852902975, "auprc_hard": 0.46762925772752423, "precision": 0.31898900866508484, "precision_easy": 0.7068076729774475, "precision_hard": 0.2314203977584839, "recall": 0.5972452163696289, "recall_easy": 0.5731120109558105, "recall_hard": 0.6934260725975037, "f1score": 0.415864497423172, "f1score_easy": 0.6329771876335144, "f1score_hard": 0.34702613949775696, "TP": 113866, "TP_easy": 87348, "TP_hard": 26518, "TN": 89219503, "TN_easy": 7937821, "TN_hard": 35525272, "FP": 243093, "FP_easy": 36233, "FP_hard": 88070, "FN": 76786, "FN_easy": 65062, "FN_hard": 11724, "iou": 0.2625182867050171, "iou_easy": 0.4630333483219147, "iou_hard": 0.20994046330451965, "balanced_accuracy": 0.7972639799118042, "balanced_accuracy_easy": 0.7842841148376465, "balanced_accuracy_hard": 0.845476508140564, "cohen_kappa": 0.41424065828323364, "cohen_kappa_easy": 0.6267074942588806, "cohen_kappa_hard": 0.3459741473197937, "tile_FPR": 0.6800000071525574}

LINKNET/CEM/LinkNet_RGB_CEM_B/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_CEM_B
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - cem
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_cem
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/CEM/LinkNet_RGB_CEM_B/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,cem]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_CEM_B
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,cem],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_CEM_B,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_CEM_B
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/CEM/LinkNet_RGB_CEM_B/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,cem]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_CEM_B
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/CEM/LinkNet_RGB_CEM_B/final_checkpoint_model_40ep.ckpt

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LINKNET/CEM/LinkNet_RGB_CEM_B/final_checkpoint_model_40ep.onnx

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LINKNET/CEM/LinkNet_RGB_CEM_B/results_test_40ep.json

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LINKNET/CEM/LinkNet_RGB_CEM_C/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_CEM_C
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - cem
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_cem
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/CEM/LinkNet_RGB_CEM_C/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,cem]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_CEM_C
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,cem],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_CEM_C,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_CEM_C
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/CEM/LinkNet_RGB_CEM_C/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,cem]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_CEM_C
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

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LINKNET/CEM/LinkNet_RGB_CEM_C/results_test_40ep.json

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+{"auprc": 0.16035815627018224, "auprc_easy": 0.6172272024214699, "auprc_hard": 0.5200401554928316, "precision": 0.23335282504558563, "precision_easy": 0.7416125535964966, "precision_hard": 0.4092662036418915, "recall": 0.4521746337413788, "recall_easy": 0.40827372670173645, "recall_hard": 0.6271377205848694, "f1score": 0.3078395426273346, "f1score_easy": 0.5266276001930237, "f1score_hard": 0.49530163407325745, "TP": 86208, "TP_easy": 62225, "TP_hard": 23983, "TN": 89179372, "TN_easy": 7952374, "TN_hard": 35578725, "FP": 283224, "FP_easy": 21680, "FP_hard": 34617, "FN": 104444, "FN_easy": 90185, "FN_hard": 14259, "iou": 0.18192100524902344, "iou_easy": 0.3574300706386566, "iou_hard": 0.3291700482368469, "balanced_accuracy": 0.7245044708251953, "balanced_accuracy_easy": 0.7027774453163147, "balanced_accuracy_hard": 0.8130828142166138, "cohen_kappa": 0.30589228868484497, "cohen_kappa_easy": 0.5202381610870361, "cohen_kappa_hard": 0.4946455955505371, "tile_FPR": 0.49714285135269165}

LINKNET/CEM/LinkNet_RGB_CEM_D/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_CEM_D
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - cem
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_cem
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/CEM/LinkNet_RGB_CEM_D/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,cem]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_CEM_D
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,cem],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_CEM_D,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_CEM_D
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/CEM/LinkNet_RGB_CEM_D/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,cem]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_CEM_D
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/CEM/LinkNet_RGB_CEM_D/final_checkpoint_model_40ep.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3e170bf1d3c5e97cb103ded48410f90b1fa90a956fefbb7962fe8588f2cf7daa
+size 10591877

LINKNET/CEM/LinkNet_RGB_CEM_D/final_checkpoint_model_40ep.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3249e151404c5f58f20141c560f0fd8dbc71f063b10442412a34760dfe71ede5
+size 3503504

LINKNET/CEM/LinkNet_RGB_CEM_D/results_test_40ep.json

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+{"auprc": 0.30514615087272895, "auprc_easy": 0.6127196774969026, "auprc_hard": 0.3317879505245254, "precision": 0.16546858847141266, "precision_easy": 0.5542868375778198, "precision_hard": 0.11491871625185013, "recall": 0.6059731841087341, "recall_easy": 0.5669247508049011, "recall_hard": 0.761597216129303, "f1score": 0.2599535882472992, "f1score_easy": 0.5605345964431763, "f1score_hard": 0.19970379769802094, "TP": 115530, "TP_easy": 86405, "TP_hard": 29125, "TN": 88879927, "TN_easy": 7904574, "TN_hard": 35389027, "FP": 582669, "FP_easy": 69480, "FP_hard": 224315, "FN": 75122, "FN_easy": 66005, "FN_hard": 9117, "iou": 0.14939463138580322, "iou_easy": 0.38940465450286865, "iou_hard": 0.11092829704284668, "balanced_accuracy": 0.799730122089386, "balanced_accuracy_easy": 0.7791057825088501, "balanced_accuracy_hard": 0.8776493072509766, "cohen_kappa": 0.2574729919433594, "cohen_kappa_easy": 0.5520384311676025, "cohen_kappa_hard": 0.19820916652679443, "tile_FPR": 0.7428571581840515}

LINKNET/CEM/LinkNet_RGB_CEM_E/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_CEM_E
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - cem
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_cem
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/CEM/LinkNet_RGB_CEM_E/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,cem]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_CEM_E
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,cem],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_CEM_E,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_CEM_E
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/CEM/LinkNet_RGB_CEM_E/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,cem]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_CEM_E
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_cem
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/CEM/LinkNet_RGB_CEM_E/final_checkpoint_model_40ep.ckpt

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+size 10591877

LINKNET/CEM/LinkNet_RGB_CEM_E/final_checkpoint_model_40ep.onnx

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+size 3503504

LINKNET/CEM/LinkNet_RGB_CEM_E/results_test_40ep.json

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+{"auprc": 0.17507702877871295, "auprc_easy": 0.5061055621446362, "auprc_hard": 0.33074220773588225, "precision": 0.14373405277729034, "precision_easy": 0.5283378958702087, "precision_hard": 0.12006955593824387, "recall": 0.4416581094264984, "recall_easy": 0.399343878030777, "recall_hard": 0.6102975606918335, "f1score": 0.21688471734523773, "f1score_easy": 0.45487257838249207, "f1score_hard": 0.20066116750240326, "TP": 84203, "TP_easy": 60864, "TP_hard": 23339, "TN": 88960974, "TN_easy": 7919719, "TN_hard": 35442302, "FP": 501622, "FP_easy": 54335, "FP_hard": 171040, "FN": 106449, "FN_easy": 91546, "FN_hard": 14903, "iou": 0.12163247168064117, "iou_easy": 0.2943916320800781, "iou_hard": 0.11151938885450363, "balanced_accuracy": 0.7180255651473999, "balanced_accuracy_easy": 0.696264922618866, "balanced_accuracy_hard": 0.8027474284172058, "cohen_kappa": 0.21436381340026855, "cohen_kappa_easy": 0.4459260106086731, "cohen_kappa_hard": 0.19922566413879395, "tile_FPR": 0.6399999856948853}

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_tileMag1c_1perc_A
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - mag1c_tile_sampled-0.01
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_mag1c_1perc
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_tileMag1c_1perc_A
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_tileMag1c_1perc_A,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_tileMag1c_1perc_A
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_tileMag1c_1perc_A
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/final_checkpoint_model_40ep.ckpt

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LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/final_checkpoint_model_40ep.onnx

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+oid sha256:a85658456004d2f1db89a5c5c32bf259e7fe0a90ee5afe35970a707c6cd93203
+size 3503504

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_A/results_test_40ep.json

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+{"auprc": 0.30707565451258856, "auprc_easy": 0.6610068525311543, "auprc_hard": 0.2687316599204637, "precision": 0.3240155279636383, "precision_easy": 0.7024475932121277, "precision_hard": 0.24275700747966766, "recall": 0.5662725567817688, "recall_easy": 0.5415589809417725, "recall_hard": 0.6647664904594421, "f1score": 0.41218364238739014, "f1score_easy": 0.611599326133728, "f1score_hard": 0.3556419909000397, "TP": 107961, "TP_easy": 82539, "TP_hard": 25422, "TN": 89237360, "TN_easy": 7939091, "TN_hard": 35534042, "FP": 225236, "FP_easy": 34963, "FP_hard": 79300, "FN": 82691, "FN_easy": 69871, "FN_hard": 12820, "iou": 0.2595915198326111, "iou_easy": 0.44050636887550354, "iou_hard": 0.21628013253211975, "balanced_accuracy": 0.7818774580955505, "balanced_accuracy_easy": 0.7685872316360474, "balanced_accuracy_hard": 0.8312698602676392, "cohen_kappa": 0.41058915853500366, "cohen_kappa_easy": 0.6051517724990845, "cohen_kappa_hard": 0.354627788066864, "tile_FPR": 0.4571428596973419}

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_B/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_tileMag1c_1perc_B
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - mag1c_tile_sampled-0.01
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_mag1c_1perc
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_B/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_tileMag1c_1perc_B
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_tileMag1c_1perc_B,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_tileMag1c_1perc_B
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_B/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_tileMag1c_1perc_B
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_tileMag1c_1perc_C
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - mag1c_tile_sampled-0.01
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_mag1c_1perc
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/.hydra/hydra.yaml

@@ -0,0 +1,183 @@
+hydra:
+  run:
+    dir: experiments_v2/${experiment_name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+    - wandb.wandb_project=Runs08_FastProds
+    - model.architecture=linknet
+    - model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+    - model.positive_weight=1
+    - experiment_name=LinkNet_RGB_tileMag1c_1perc_C
+    - dataset.augment_rotation_load_surrounding_area=0.4
+    - dataset.normalisation.mode_input=from_data
+    - dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+    - dataset.normalisation.max_style=max_outliers
+    - dataset.normalisation.max_outlier_percentile=5
+    - dataloader.num_workers=8
+    - dataloader.train_batch_size=32
+    - dataloader.val_batch_size=32
+    - training.val_check_interval=0.5
+    - training.max_epochs=40
+    - dataset.format=AVIRIS
+    - model.multiply_loss_by_mag1c=True
+    - model.weighted_random_sampler=True
+    - training.visualiser.bands=[first1,labelbinary,prediction,differences]
+    - dataset.train_csv=train_valids_only.csv
+    - dataset.test_csv=test.csv
+    - dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+    - dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+    - dataset.tiler.tile_size=128
+    - dataset.tiler.tile_overlap=64
+    - model.lr=0.001
+    - model.log_train_images_every_batch_i=5000
+    - model.auto_continue=True
+  job:
+    name: train
+    chdir: true
+    override_dirname: dataloader.num_workers=8,dataloader.train_batch_size=32,dataloader.val_batch_size=32,dataset.augment_rotation_load_surrounding_area=0.4,dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder,dataset.format=AVIRIS,dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01],dataset.normalisation.max_outlier_percentile=5,dataset.normalisation.max_style=max_outliers,dataset.normalisation.mode_input=from_data,dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc,dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS,dataset.test_csv=test.csv,dataset.tiler.tile_overlap=64,dataset.tiler.tile_size=128,dataset.train_csv=train_valids_only.csv,experiment_name=LinkNet_RGB_tileMag1c_1perc_C,model.architecture=linknet,model.auto_continue=True,model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100,model.log_train_images_every_batch_i=5000,model.lr=0.001,model.multiply_loss_by_mag1c=True,model.positive_weight=1,model.weighted_random_sampler=True,training.max_epochs=40,training.val_check_interval=0.5,training.visualiser.bands=[first1,labelbinary,prediction,differences],wandb.wandb_project=Runs08_FastProds
+    id: ???
+    num: ???
+    config_name: settings
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/scripts
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /data/coml-gen-ae/hert6112/python_codes/hyperspectral_models/experiments_v2/LinkNet_RGB_tileMag1c_1perc_C
+    choices:
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/.hydra/overrides.yaml

@@ -0,0 +1,29 @@
+- dataset.input_products.specific_products=[640,550,460,mag1c_tile_sampled-0.01]
+- wandb.wandb_project=Runs08_FastProds
+- model.architecture=linknet
+- model.hyperstarcop.backbone=timm-mobilenetv3_small_minimal_100
+- model.positive_weight=1
+- experiment_name=LinkNet_RGB_tileMag1c_1perc_C
+- dataset.augment_rotation_load_surrounding_area=0.4
+- dataset.normalisation.mode_input=from_data
+- dataset.normalisation.save_load_from=normaliser_fastprods_rgb_mag1c_1perc
+- dataset.normalisation.max_style=max_outliers
+- dataset.normalisation.max_outlier_percentile=5
+- dataloader.num_workers=8
+- dataloader.train_batch_size=32
+- dataloader.val_batch_size=32
+- training.val_check_interval=0.5
+- training.max_epochs=40
+- dataset.format=AVIRIS
+- model.multiply_loss_by_mag1c=True
+- model.weighted_random_sampler=True
+- training.visualiser.bands=[first1,labelbinary,prediction,differences]
+- dataset.train_csv=train_valids_only.csv
+- dataset.test_csv=test.csv
+- dataset.root_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+- dataset.feature_folder=/data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+- dataset.tiler.tile_size=128
+- dataset.tiler.tile_overlap=64
+- model.lr=0.001
+- model.log_train_images_every_batch_i=5000
+- model.auto_continue=True

LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/final_checkpoint_model_40ep.ckpt

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LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/final_checkpoint_model_40ep.onnx

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LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_C/results_test_40ep.json

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LINKNET/Mag1c-SAS/LinkNet_RGB_Mag1cSAS_D/.hydra/config.yaml

@@ -0,0 +1,167 @@
+experiment_name: LinkNet_RGB_tileMag1c_1perc_D
+experiment_path: ''
+seed: None
+resume_from_checkpoint: false
+experiment_folder: /home/vitek/Vitek/Work/hyperspectral_utils/experiments
+wandb:
+  wandb_project: Runs08_FastProds
+  wandb_entity: previtus
+dataloader:
+  train_batch_size: 32
+  val_batch_size: 32
+  num_workers: 8
+dataset:
+  input_products:
+    specific_products:
+    - 640
+    - 550
+    - 460
+    - mag1c_tile_sampled-0.01
+    band_ranges: []
+  output_products:
+  - labelbinary
+  multitemporal:
+    enabled: false
+    bases:
+    - B
+    - A
+    multitemporal_idx_as_y: None
+  auxiliary_products: []
+  root_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/zaitra_colab/STARCOP_FAST_PRODS
+  train_csv: train_valids_only.csv
+  val_csv: ''
+  test_csv: test.csv
+  custom_csv: ''
+  feature_folder: /data/coml-gen-ae/hert6112/datasets/STARCOP/features_folder
+  tiler:
+    mode: regular
+    input_size: 512
+    tile_size: 128
+    tile_overlap: 64
+    train: true
+    test: false
+    val: false
+    emit_thr_for_valid_data_in_tile: 0.9
+    perpixel_how_many_from_each: 100
+  augment: true
+  augment_rotation_load_surrounding_area: 0.4
+  normalisation:
+    mode_input: from_data
+    save_load_from: normaliser_fastprods_rgb_mag1c_1perc
+    max_style: max_outliers
+    max_outlier_percentile: 5
+    override_products: []
+  feature_extractor: []
+  format: AVIRIS
+  num_channels: None
+  presave_to_scratch: false
+  path_to_scratch: ''
+model:
+  architecture: linknet
+  num_classes: 1
+  optimizer: adam
+  lr: 0.001
+  loss: BCEWithLogitsLoss
+  task: segmentation
+  multiply_loss_by_mag1c: true
+  positive_weight: 1
+  weighted_random_sampler: true
+  extra_metrics: []
+  log_train_loss_every_batch_i: 100
+  log_train_images_every_batch_i: 5000
+  hyperstarcop:
+    backbone: timm-mobilenetv3_small_minimal_100
+    pretrained: None
+    activation: None
+    custom_config:
+      conv1x1:
+        encoder_stage0_replace_conv1x1: false
+        encoder_stage0_side_conv1x1: 0
+      fuse_mf:
+        late: false
+        fadein_start_epoch: None
+        fadein_end_epoch: None
+      siamese:
+        siamese: false
+        method: concat
+      custom_channels:
+        encoder: None
+        decoder: None
+        encoder_depth: None
+        output_bands: None
+  transformer:
+    backbone: nvidia/mit-b0
+    pretrained: false
+    custom_config:
+      conv1x1:
+        SegformerOverlapPatchEmbeddings: false
+      strides:
+        keep_default: true
+        strides_custom:
+        - 4
+        - 2
+        - 2
+        - 2
+      upscale:
+        preclassifier: false
+        decimate_channels_ratio: 2
+        upscale_layers: 2
+      loss_overrides:
+        multilabel_override: false
+        loss_override_to: BCEWithLogitsLoss
+    custom_config_features:
+      conv1x1: false
+      stride: false
+      upscale: false
+  efficientvit:
+    backbone: b1
+    custom_config:
+      conv1x1: false
+      head_stride: 8
+      upscale_layers: 0
+      loss_overrides:
+        multilabel_override: false
+        num_classes: 1
+  classical_baseline:
+    threshold: 500
+  load_path: ''
+  auto_continue: true
+training:
+  accelerator: gpu
+  devices: 1
+  max_epochs: 40
+  finetuning: false
+  val_check_interval: 0.5
+  train_log_every_n_steps: 50
+  visualiser:
+    samples_per_batch: 4
+    wait_global_steps: 5
+    bands:
+    - first1
+    - labelbinary
+    - prediction
+    - differences
+    target: wandb
+evaluation:
+  train: false
+  test: true
+  val: true
+  plot_save: false
+  plot_show: false
+matched_filter:
+  num_iter: 30
+debug:
+  no_normalisation: false
+  no_tiling: false
+  recalculate_normalisation: false
+payload:
+  bands: 4
+  resolution: 128
+  batch_size: 1
+  device: CPU
+  num_images: 16
+  save_folder: /home/vitek/Vitek/Work/hyperspectral_models/results/timing_logs
+  timing_rand_data: false
+  timing_model_from: manual
+  warmup: 2
+  how_many: 10