parameters: (images, contrast_factor)
docstring: Adjust contrast of RGB or grayscale images.
  
    This is a convenience method that converts an RGB image to float
    representation, adjusts its contrast, and then converts it back to the
    original data type. If several adjustments are chained it is advisable to
    minimize the number of redundant conversions.
  
    `images` is a tensor of at least 3 dimensions.  The last 3 dimensions are
    interpreted as `[height, width, channels]`.  The other dimensions only
    represent a collection of images, such as `[batch, height, width, channels].`
  
    Contrast is adjusted independently for each channel of each image.
  
    For each channel, this Op computes the mean of the image pixels in the
    channel and then adjusts each component `x` of each pixel to
    `(x - mean) * contrast_factor + mean`.
  
    Args:
      images: Images to adjust.  At least 3-D.
      contrast_factor: A float multiplier for adjusting contrast.
  
    Returns:
      The contrast-adjusted image or images.
docstring_summary: Adjust contrast of RGB or grayscale images.
docstring_tokens: Adjust contrast of RGB or grayscale images .
function: def adjust_contrast(images, contrast_factor):
    """Adjust contrast of RGB or grayscale images.
  
    This is a convenience method that converts an RGB image to float
    representation, adjusts its contrast, and then converts it back to the
    original data type. If several adjustments are chained it is advisable to
    minimize the number of redundant conversions.
  
    `images` is a tensor of at least 3 dimensions.  The last 3 dimensions are
    interpreted as `[height, width, channels]`.  The other dimensions only
    represent a collection of images, such as `[batch, height, width, channels].`
  
    Contrast is adjusted independently for each channel of each image.
  
    For each channel, this Op computes the mean of the image pixels in the
    channel and then adjusts each component `x` of each pixel to
    `(x - mean) * contrast_factor + mean`.
  
    Args:
      images: Images to adjust.  At least 3-D.
      contrast_factor: A float multiplier for adjusting contrast.
  
    Returns:
      The contrast-adjusted image or images.
    """
    with ops.name_scope(None, 'adjust_contrast',
                        [images, contrast_factor]) as name:
      images = ops.convert_to_tensor(images, name='images')
      # Remember original dtype to so we can convert back if needed
      orig_dtype = images.dtype
      flt_images = convert_image_dtype(images, dtypes.float32)
  
      # pylint: disable=protected-access
      adjusted = gen_image_ops._adjust_contrastv2(flt_images,
                                                  contrast_factor=contrast_factor,
                                                  name=name)
      # pylint: enable=protected-access
  
      return convert_image_dtype(adjusted, orig_dtype, saturate=True)
function_tokens: def adjust_contrast ( images , contrast_factor ) : with ops . name_scope ( None , 'adjust_contrast' , [ images , contrast_factor ] ) as name : images = ops . convert_to_tensor ( images , name = 'images' ) # Remember original dtype to so we can convert back if needed orig_dtype = images . dtype flt_images = convert_image_dtype ( images , dtypes . float32 ) # pylint: disable=protected-access adjusted = gen_image_ops . _adjust_contrastv2 ( flt_images , contrast_factor = contrast_factor , name = name ) # pylint: enable=protected-access return convert_image_dtype ( adjusted , orig_dtype , saturate = True )