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granite-geospatial-uki

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+ # lightning.pytorch==2.1.1
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+ seed_everything: 0
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+ trainer:
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+ accelerator: gpu # we can also use auto or cpu
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+ strategy: auto
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+ devices: auto
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+ num_nodes: 1
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+ logger: True # will use tensorboardlogger
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+
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+ callbacks:
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+ - class_path: RichProgressBar
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+ - class_path: LearningRateMonitor
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+ init_args:
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+ logging_interval: epoch
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+ - class_path: EarlyStopping
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+ init_args:
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+ monitor: val/loss
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+ patience: 30
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+
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+ max_epochs: 200
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+ check_val_every_n_epoch: 1
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+ log_every_n_steps: 1
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+ enable_checkpointing: true
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+ default_root_dir: ./../data/fine_tuning/granite_geospatial_uki_flood_detection_v2
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+ data:
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+ class_path: GenericNonGeoSegmentationDataModule
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+ init_args:
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+ batch_size: 4
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+ num_workers: 1
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+ constant_scale: 0.0001
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+ dataset_bands: # what bands are in your data
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+ - VV
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+ - VH
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+ - BLUE
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+ - GREEN
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+ - RED
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+ - NIR_NARROW
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+ - SWIR_1
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+ - SWIR_2
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+ - CLOUD
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+ output_bands: # which bands do you want to fine-tune
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+ - BLUE
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+ - GREEN
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+ - RED
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+ - NIR_NARROW
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+ - SWIR_1
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+ - SWIR_2
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+ - VV
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+ - VH
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+ - CLOUD
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+ rgb_indices:
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+ - 4
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+ - 3
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+ - 2
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+ train_data_root: ./../data/regions/combined_uki_spain/images/
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+ train_label_data_root: ./../data/regions/combined_uki_spain/labels/
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+ val_data_root: ./../data/regions/combined_uki_spain/images/
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+ val_label_data_root: ./../data/regions/combined_uki_spain/labels/
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+ test_data_root: ./../data/regions/combined_uki_spain/images/
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+ test_label_data_root: ./../data/regions/combined_uki_spain/labels/
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+ train_split: ./../data/regions/combined_uki_spain/splits/flood_train_data.txt
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+ test_split: ./../data/regions/combined_uki_spain/splits/flood_test_data.txt
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+ val_split: ./../data/regions/combined_uki_spain/splits/flood_val_data.txt
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+ img_grep: "*_image.tif"
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+ label_grep: "*_label.tif"
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+ no_label_replace: -1
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+ no_data_replace: 0
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+ means:
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+ - 0.1290484133335582 # BLUE
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+ - 0.13423481405157794 # GREEN
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+ - 0.1328938801112928 # RED
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+ - 0.20036851044035797 # NIR_NARROW
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+ - 0.13804629743141042 # SWIR_1
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+ - 0.10409700513471637 # SWIR_2
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+ - -0.0018052691820029847 # VV
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+ - -0.0023712696527645486 # VH
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+ - 0.000024014472961425782 #CLOUD
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+
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+ stds:
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+ - 0.25406999374272976
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+ - 0.22949378991348005
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+ - 0.21689414406289836
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+ - 0.22552362238920548
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+ - 0.1600542128720416
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+ - 0.12602917719190815
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+ - 0.0011294842635096356
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+ - 0.0008879269711519241
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+ - 0.00004271712050839232
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+
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+ num_classes: 2
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+
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+ model:
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+ class_path: terratorch.tasks.SemanticSegmentationTask
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+ init_args:
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+ model_args:
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+ decoder: FCNDecoder
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+ backbone_pretrained: true
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+ backbone: granite_geospatial_uki
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+ backbone_pretrained_cfg_overlay:
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+ file: ./../data/checkpoints/granite_geospatial_uki.pt
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+ backbone_pretrain_img_size: 512
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+ decoder_channels: 256
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+ # in_channels: 9
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+ backbone_bands:
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+ - BLUE
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+ - GREEN
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+ - RED
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+ - NIR_NARROW
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+ - SWIR_1
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+ - SWIR_2
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+ - VV
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+ - VH
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+ - CLOUD
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+ # num_frames: 1
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+ num_classes: 2
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+ head_dropout: 0.1
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+ decoder_num_convs: 4
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+ head_channel_list:
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+ - 256
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+ necks:
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+ - name: SelectIndices
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+ indices:
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+ - -1
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+ - name: ReshapeTokensToImage
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+ loss: ce
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+ aux_heads:
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+ - name: aux_head
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+ decoder: FCNDecoder
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+ decoder_args:
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+ decoder_channels: 256
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+ decoder_in_index: -1
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+ decoder_num_convs: 2
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+ head_dropout: 0.1
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+ aux_loss:
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+ aux_head: 1.0
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+ ignore_index: -1
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+ class_weights:
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+ - 0.3
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+ - 0.7
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+ freeze_backbone: false
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+ freeze_decoder: false
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+ model_factory: EncoderDecoderFactory
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+ tiled_inference_parameters:
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+ h_crop: 512
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+ h_stride: 496
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+ w_crop: 512
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+ w_stride: 496
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+ average_patches: true
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+ optimizer:
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+ class_path: torch.optim.AdamW
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+ init_args:
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+ lr: 6.e-5
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+ weight_decay: 0.05
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+ lr_scheduler:
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+ class_path: ReduceLROnPlateau
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+ init_args:
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+ monitor: val/loss