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Tensorflow Object Detection API でのデータ拡張(data augmentation)

Last updated at Posted at 2021-03-10

pipeline.config ファイルの train_config に data_augmentation_options を記述します。
関数名と引数を指定すると、main.py実行でデータ拡張オプションを適用してくれます。

pipeline.config
train_config {
  batch_size: 1
  data_augmentation_options {
    random_horizontal_flip {
    }
  }
  data_augmentation_options {
    random_crop_image {
      min_object_covered: 0.0
      min_aspect_ratio: 0.75
      max_aspect_ratio: 3.0
      min_area: 0.75
      max_area: 1.0
      overlap_thresh: 0.0
    }
  }

可能なオプションは以下。

🐣


フリーランスエンジニアです。
お仕事のご相談こちらまで
rockyshikoku@gmail.com

Core MLを使ったアプリを作っています。
機械学習関連の情報を発信しています。

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