Feature/add more examples

docs/examples.md

@@ -6,12 +6,10 @@ For some examples of training using the existing tasks, check out the following
 
 Under `examples/confs`
 
-* Flood Segmentation with ViT: `segmentation_config_vit.yaml`
+* Flood Segmentation with ViT: `sen1floods11_vit.yaml`
 
 * Multitemporal Crop Segmentation: `multitemporal_crop.yaml`
 
-* Scene Classification: `eurosat.yaml`
+* Burn Scar Segmentation: `burn_scars.yaml`
 
-* Usage of an SMP backbone `geobench/segmentation/m_chesapeake_landcover_smp_resnet_unet.yaml`
-
-* Usage of a timm backbone `geobench/classification/m_bigearthnet_timm_resnet.yaml`
+* Scene Classification: `eurosat.yaml`

examples/confs/burn_scars.yaml

@@ -0,0 +1,131 @@
+# lightning.pytorch==2.1.1
+seed_everything: 0
+trainer:
+  accelerator: auto
+  strategy: auto
+  devices: auto
+  num_nodes: 1
+  precision: 16-mixed
+  logger:
+    class_path: TensorBoardLogger
+    init_args:
+      save_dir: <path>
+      name: fire_scars
+  callbacks:
+    - class_path: RichProgressBar
+    - class_path: LearningRateMonitor
+      init_args:
+        logging_interval: epoch
+    - class_path: EarlyStopping
+      init_args:
+        monitor: val/loss
+        patience: 40
+
+  max_epochs: 200
+  check_val_every_n_epoch: 1
+  log_every_n_steps: 50
+  enable_checkpointing: true
+  default_root_dir: <path>
+
+# dataset available: https://huggingface.co/datasets/ibm-nasa-geospatial/hls_burn_scars
+data:
+  class_path: GenericNonGeoSegmentationDataModule
+  init_args:
+    batch_size: 4
+    num_workers: 8
+    dataset_bands:
+      - BLUE
+      - GREEN
+      - RED
+      - NIR_NARROW
+      - SWIR_1
+      - SWIR_2
+    output_bands:
+      - BLUE
+      - GREEN
+      - RED
+      - NIR_NARROW
+      - SWIR_1
+      - SWIR_2
+    rgb_indices:
+      - 0
+      - 1
+      - 2
+    train_transform:
+      - class_path: albumentations.RandomCrop
+        init_args:
+          height: 224
+          width: 224
+      - class_path: albumentations.HorizontalFlip
+        init_args:
+          p: 0.5
+      - class_path: ToTensorV2
+    no_data_replace: 0
+    no_label_replace: -1
+    train_data_root: <data_path>/training
+    train_label_data_root: <data_path>/training
+    val_data_root: <data_path>/validation
+    val_label_data_root: <data_path>/validation
+    test_data_root: <data_path>/validation
+    test_label_data_root: <data_path>/validation
+    img_grep: "*_merged.tif"
+    label_grep: "*.mask.tif"
+    means:
+      - 0.033349706741586264
+      - 0.05701185520536176
+      - 0.05889748132001316
+      - 0.2323245113436119
+      - 0.1972854853760658
+      - 0.11944914225186566
+    stds:
+      - 0.02269135568823774
+      - 0.026807560223070237
+      - 0.04004109844362779
+      - 0.07791732423672691
+      - 0.08708738838140137
+      - 0.07241979477437814
+    num_classes: 2
+
+model:
+  class_path: terratorch.tasks.SemanticSegmentationTask
+  init_args:
+    model_args:
+      decoder: FCNDecoder
+      pretrained: true
+      backbone: prithvi_vit_100
+      decoder_channels: 256
+      in_channels: 6
+      bands:
+        - BLUE
+        - GREEN
+        - RED
+        - NIR_NARROW
+        - SWIR_1
+        - SWIR_2
+      num_frames: 1
+      num_classes: 2
+      head_dropout: 0.1
+      decoder_num_convs: 4
+      head_channel_list:
+        - 256
+    loss: dice
+    plot_on_val: 10
+    ignore_index: -1
+    freeze_backbone: false
+    freeze_decoder: false
+    model_factory: PrithviModelFactory
+    tiled_inference_parameters:
+      h_crop: 512
+      h_stride: 496
+      w_crop: 512
+      w_stride: 496
+      average_patches: true
+optimizer:
+  class_path: torch.optim.Adam
+  init_args:
+    lr: 1.5e-5
+    weight_decay: 0.05
+lr_scheduler:
+  class_path: ReduceLROnPlateau
+  init_args:
+    monitor: val/loss

examples/confs/multi_temporal_crop.yaml

@@ -0,0 +1,169 @@
+# lightning.pytorch==2.1.1
+seed_everything: 0
+trainer:
+  accelerator: auto
+  strategy: auto
+  devices: auto
+  num_nodes: 1
+  precision: 16-mixed
+  logger:
+    class_path: TensorBoardLogger
+    init_args:
+      save_dir: <path>
+      name: replicate
+  callbacks:
+    - class_path: RichProgressBar
+    - class_path: LearningRateMonitor
+      init_args:
+        logging_interval: epoch
+
+  max_epochs: 200
+  check_val_every_n_epoch: 1
+  log_every_n_steps: 50
+  enable_checkpointing: true
+  default_root_dir: <path>
+
+# data available at: https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M-multi-temporal-crop-classification
+data:
+  class_path: GenericNonGeoSegmentationDataModule
+  init_args:
+    batch_size: 8
+    num_workers: 12
+    train_transform:
+      - class_path: FlattenTemporalIntoChannels
+      - class_path: albumentations.Flip
+      - class_path: ToTensorV2
+      - class_path: UnflattenTemporalFromChannels
+        init_args:
+          n_timesteps: 3
+
+    dataset_bands:
+      - BLUE
+      - GREEN
+      - RED
+      - NIR_NARROW
+      - SWIR_1
+      - SWIR_2
+    output_bands:
+      - BLUE
+      - GREEN
+      - RED
+      - NIR_NARROW
+      - SWIR_1
+      - SWIR_2
+    rgb_indices:
+      - 2
+      - 1
+      - 0
+    reduce_zero_label: True
+    expand_temporal_dimension: True
+    train_data_root: <data_path>/training_chips
+    train_label_data_root: <data_path>/training_chips
+    val_data_root: <data_path>/validation_chips
+    val_label_data_root: <data_path>/validation_chips
+    test_data_root: <data_path>/validation_chips
+    test_label_data_root: <data_path>/validation_chips
+    train_split: <data_path>/training_chips/training_data.txt
+    test_split: <data_path>/validation_chips/validation_data.txt
+    val_split: <data_path>/validation_chips/validation_data.txt
+    img_grep: "*_merged.tif"
+    label_grep: "*.mask.tif"
+    means:
+      - 494.905781
+      - 815.239594
+      - 924.335066
+      - 2968.881459
+      - 2634.621962
+      - 1739.579917
+    stds:
+      - 284.925432
+      - 357.84876
+      - 575.566823
+      - 896.601013
+      - 951.900334
+      - 921.407808
+    num_classes: 13
+
+model:
+  class_path: terratorch.tasks.SemanticSegmentationTask
+  init_args:
+    model_args:
+      decoder: FCNDecoder
+      pretrained: true
+      backbone: prithvi_vit_100
+      in_channels: 6
+      rescale: False
+      bands:
+        - BLUE
+        - GREEN
+        - RED
+        - NIR_NARROW
+        - SWIR_1
+        - SWIR_2
+      num_frames: 3
+      num_classes: 13
+      head_dropout: 0.1
+      decoder_channels: 512
+      head_channel_list:
+        - 128
+        - 64
+    loss: ce
+    class_names:
+      - Natural Vegetation
+      - Forest
+      - Corn
+      - Soybeans
+      - Wetlands
+      - Developed/Barren
+      - Open Water
+      - Winter Wheat
+      - Alfalfa
+      - Fallow/Idle Cropland
+      - Cotton
+      - Sorghum
+      - Other
+    # aux_heads:
+    # - name: aux_head
+    #     decoder: FCNDecoder
+    #     decoder_args:
+    #       decoder_channels: 256
+    #       decoder_in_index: 2
+    #       decoder_num_convs: 2
+    #       head_channel_list:
+    #         - 64
+    # aux_loss:
+    #   aux_head: 1.0
+    class_weights:
+      - 0.386375
+      - 0.661126
+      - 0.548184
+      - 0.640482
+      - 0.876862
+      - 0.925186
+      - 3.249462
+      - 1.542289
+      - 2.175141
+      - 2.272419
+      - 3.062762
+      - 3.626097
+      - 1.198702
+
+    ignore_index: -1
+    freeze_backbone: false
+    freeze_decoder: false
+    model_factory: PrithviModelFactory
+    tiled_inference_parameters:
+      h_crop: 224
+      h_stride: 196
+      w_crop: 224
+      w_stride: 196
+      average_patches: true
+optimizer:
+  class_path: torch.optim.AdamW
+  init_args:
+    lr: 1.5e-5
+    weight_decay: 0.05
+lr_scheduler:
+  class_path: ReduceLROnPlateau
+  init_args:
+    monitor: val/loss