stereo-magnification-tensorflow

最新推荐文章于 2024-08-30 07:39:17 发布

Sag_ittarius

最新推荐文章于 2024-08-30 07:39:17 发布

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CC 4.0 BY-SA版权

分类专栏： tensorflow

本文链接：https://blog.youkuaiyun.com/u012871045/article/details/95490538

本文介绍了在TensorFlow中实现立体放大技术的过程中遇到的问题及解决方案，包括loader.py中影响程序运行的关键参数设置，train.py中对datasets.py的路径配置，homography.py中处理homography时的形状获取问题，以及针对多个txt文件的数据分析和训练策略。

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loader.py

flags.DEFINE_integer('min_stride', 3, 'Minimum stride for sequence.')
flags.DEFINE_integer('max_stride', 5, 'Maximum stride for sequence.')

该参数会影响程序能否运行，具体体现在loader.py中：

    def prepare_for_training(sequences):
      """Steps applied to training dataset only."""
      # Random shuffling, random subsequences and random reversal for training.
      # Also we make it repeat indefinitely.
      shuffled = sequences.shuffle(1000).repeat(epochs)
      # Discard sequences that are too short to generate a subsequence at
      # max stride.
      required_length = (sequence_length - 1) * max_stride + 1
      filtered = shuffled.filter(
          lambda sequence: tf.greater_equal(sequence.length(), required_length))
      subsequences = filtered.map(
          lambda sequence: sequence.random_subsequence(sequence_length, min_stride, max_stride)
      )