深度学习分割，图像增强

喜欢ヅ旅行 2022-05-27 04:19 188阅读 0赞

图像增强方法

*  tf.random\_crop()
 *  tf.image.random\_flip\_left\_right()：
 *  tf.image.random\_hue()  
    
    
     *  random\_contrast()
     *  random\_brightness()
     *  random\_saturation()

if augment_level > 0:
            image = tf.image.random_brightness(image, max_delta=30)
            image = tf.image.random_contrast(image, lower=0.75, upper=1.25)
        if augment_level > 1:
            image = tf.image.random_hue(image, max_delta=0.15)
            image = tf.image.random_saturation(image, lower=0.5, upper=1.6)
    		
    		
    		
    
    def random_brightness(image, max_delta, seed=None):
      """Adjust the brightness of images by a random factor.
      Equivalent to `adjust_brightness()` using a `delta` randomly picked in the
      interval `[-max_delta, max_delta)`.
      Args:
        image: An image.
        max_delta: float, must be non-negative.
        seed: A Python integer. Used to create a random seed. See
          @{tf.set_random_seed}
          for behavior.
      Returns:
        The brightness-adjusted image.
      Raises:
        ValueError: if `max_delta` is negative.
      """
      if max_delta < 0:
        raise ValueError('max_delta must be non-negative.')
    
      delta = random_ops.random_uniform([], -max_delta, max_delta, seed=seed)
      return adjust_brightness(image, delta)
      
    def random_contrast(image, lower, upper, seed=None):
      """Adjust the contrast of an image by a random factor.
      Equivalent to `adjust_contrast()` but uses a `contrast_factor` randomly
      picked in the interval `[lower, upper]`.
      Args:
        image: An image tensor with 3 or more dimensions.
        lower: float.  Lower bound for the random contrast factor.
        upper: float.  Upper bound for the random contrast factor.
        seed: A Python integer. Used to create a random seed. See
          @{tf.set_random_seed}
          for behavior.
      Returns:
        The contrast-adjusted tensor.
      Raises:
        ValueError: if `upper <= lower` or if `lower < 0`.
      """
      if upper <= lower:
        raise ValueError('upper must be > lower.')
    
      if lower < 0:
        raise ValueError('lower must be non-negative.')
    
      # Generate an a float in [lower, upper]
      contrast_factor = random_ops.random_uniform([], lower, upper, seed=seed)
      return adjust_contrast(image, contrast_factor)
    
    
    def random_hue(image, max_delta, seed=None):
      """Adjust the hue of an RGB image by a random factor.
      Equivalent to `adjust_hue()` but uses a `delta` randomly
      picked in the interval `[-max_delta, max_delta]`.
      `max_delta` must be in the interval `[0, 0.5]`.
      Args:
        image: RGB image or images. Size of the last dimension must be 3.
        max_delta: float.  Maximum value for the random delta.
        seed: An operation-specific seed. It will be used in conjunction
          with the graph-level seed to determine the real seeds that will be
          used in this operation. Please see the documentation of
          set_random_seed for its interaction with the graph-level random seed.
      Returns:
        Adjusted image(s), same shape and DType as `image`.
      Raises:
        ValueError: if `max_delta` is invalid.
      """
      if max_delta > 0.5:
        raise ValueError('max_delta must be <= 0.5.')
    
      if max_delta < 0:
        raise ValueError('max_delta must be non-negative.')
    
      delta = random_ops.random_uniform([], -max_delta, max_delta, seed=seed)
      return adjust_hue(image, delta)
    
    def random_saturation(image, lower, upper, seed=None):
      """Adjust the saturation of an RGB image by a random factor.
      Equivalent to `adjust_saturation()` but uses a `saturation_factor` randomly
      picked in the interval `[lower, upper]`.
      Args:
        image: RGB image or images. Size of the last dimension must be 3.
        lower: float.  Lower bound for the random saturation factor.
        upper: float.  Upper bound for the random saturation factor.
        seed: An operation-specific seed. It will be used in conjunction
          with the graph-level seed to determine the real seeds that will be
          used in this operation. Please see the documentation of
          set_random_seed for its interaction with the graph-level random seed.
      Returns:
        Adjusted image(s), same shape and DType as `image`.
      Raises:
        ValueError: if `upper <= lower` or if `lower < 0`.
      """
      if upper <= lower:
        raise ValueError('upper must be > lower.')
    
      if lower < 0:
        raise ValueError('lower must be non-negative.')
    
      # Pick a float in [lower, upper]
      saturation_factor = random_ops.random_uniform([], lower, upper, seed=seed)
      return adjust_saturation(image, saturation_factor)