random_seed: 42
dataset_config {
  augment: true
  dataset: "custom"
  input_image_type: "color"
  train_images_path: "/workspace/computer_vision_master_datastore/InstanceSegmentation/HNT/572/data/images/train"
  train_masks_path: "/workspace/computer_vision_master_datastore/InstanceSegmentation/HNT/572/data/masks/train"
  val_images_path: "/workspace/computer_vision_master_datastore/InstanceSegmentation/HNT/572/data/images/train"
  val_masks_path: "/workspace/computer_vision_master_datastore/InstanceSegmentation/HNT/572/data/masks/train"
  test_images_path: "/workspace/computer_vision_master_datastore/InstanceSegmentation/HNT/572/data/images/train"
  data_class_config {
    target_classes {
      name: "buildings"
      mapping_class: "buildings"
    }
    target_classes {
      name: "manmade structure"
      label_id: 1
      mapping_class: "manmade structure"
    }
    target_classes {
      name: "road"
      label_id: 2
      mapping_class: "road"
    }
    target_classes {
      name: "tracks"
      label_id: 3
      mapping_class: "tracks"
    }
    target_classes {
      name: "trees"
      label_id: 4
      mapping_class: "trees"
    }
    target_classes {
      name: "crops"
      label_id: 5
      mapping_class: "crops"
    }
    target_classes {
      name: "waterway"
      label_id: 6
      mapping_class: "waterway"
    }
    target_classes {
      name: "standing water"
      label_id: 7
      mapping_class: "standing water"
    }
    target_classes {
      name: "vehicle large"
      label_id: 8
      mapping_class: "vehicle large"
    }
    target_classes {
      name: "vehicle small"
      label_id: 9
      mapping_class: "vehicle small"
    }
    target_classes {
      name: "background"
      label_id: 10
      mapping_class: "background"
    }
  }
  augmentation_config {
    spatial_augmentation {
      hflip_probability: 0.5
      vflip_probability: 0.5
      crop_and_resize_prob: 0.5
    }
    brightness_augmentation {
      delta: 0.20000000298023224
    }
  }
  resize_padding: true
  resize_method: "BILINEAR"
}
model_config {
  training_precision {
    backend_floatx: FLOAT32
  }
  arch: "vanilla_unet"
  all_projections: true
  model_input_height: 572
  model_input_width: 572
  model_input_channels: 3
}
training_config {
  batch_size: 8
  regularizer {
    type: L2
    weight: 1.9999999949504854e-06
  }
  optimizer {
    adam {
      epsilon: 9.99999993922529e-09
      beta1: 0.8999999761581421
      beta2: 0.9990000128746033
    }
  }
  checkpoint_interval: 10
  log_summary_steps: 10
  learning_rate: 0.004999999888241291
  loss: "cross_dice_sum"
  epochs: 5000
}