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    • Documentation
    • Benchmarking Results
      • What is image augmentation
      • Why you need a dedicated library
      • Why Albumentations
      • Installation
      • Image augmentation for classification
      • Mask augmentation for segmentation
      • Bounding boxes augmentation for object detection
      • Keypoints augmentation
      • Simultaneous augmentation of multiple targets: masks, bounding boxes, keypoints
      • A list of transforms and their supported targets
      • Setting probabilities for transforms
    • Examples
    • FAQ
      • Online classes that cover Albumentations
      • Blog posts, podcasts, talks, and videos about Albumentations
      • Books that mention Albumentations
      • HuggingFace
      • FiftyOne
      • Roboflow
    • Frameworks and libraries that use Albumentations
    • API Reference
      • Full API Reference
      • Core API
      • Augmentations
        • Transforms (augmentations.transforms)
        • Blur transforms
        • Crop transforms
        • Dropout transforms
          • ChannelDropout augmentation (augmentations.dropout.channel_dropout)
          • CoarseDropout augmentation (augmentations.dropout.coarse_dropout)
          • GridDropout augmentation (augmentations.dropout.grid_dropout)
          • MaskDropout augmentation (augmentations.dropout.mask_dropout)
          • XYMasking augmentation (augmentations.dropout.xy_masking)
        • Geometric transforms
        • Domain Adaptation transforms
        • Functional transforms (augmentations.functional)
      • PyTorch Helpers
    • Contributing
      • Coding Guidelines
      • Environment Setup
    • AutoAlbument
      • Benchmarks and a comparison with baseline augmentation strategies
      • Installation
      • How to use AutoAlbument
      • How to use an AutoAlbument Docker image
      • How to use a custom classification or semantic segmentation model
      • Metrics and their meaning
      • Tuning the search parameters
      • Examples
      • Search algorithms
      • FAQ

    Index

    • ChannelDropout augmentation (albumentations.augmentations.dropout.channel_dropout)
    • CoarseDropout augmentation (albumentations.augmentations.dropout.coarse_dropout)
    • GridDropout augmentation (albumentations.augmentations.dropout.grid_dropout)
    • MaskDropout augmentation (albumentations.augmentations.dropout.mask_dropout)
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    Crop transforms (augmentations.crops.transforms)
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    ChannelDropout augmentation (augmentations.dropout.channel_dropout)