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Python gen_image_ops.adjust_hue函数代码示例

本文整理汇总了Python中tensorflow.python.ops.gen_image_ops.adjust_hue函数的典型用法代码示例。如果您正苦于以下问题:Python adjust_hue函数的具体用法?Python adjust_hue怎么用?Python adjust_hue使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。


在下文中一共展示了adjust_hue函数的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: _adjustHueTf

 def _adjustHueTf(self, x_np, delta_h):
   with self.test_session():
     x = array_ops.placeholder(dtypes.float32)
     with self.test_scope():
       y = gen_image_ops.adjust_hue(x, delta_h)
     y_tf = y.eval({x: x_np})
   return y_tf
开发者ID:BhaskarNallani,项目名称:tensorflow,代码行数:7,代码来源:image_ops_test.py

示例2: adjust_hue

def adjust_hue(image, delta, name=None):
  """Adjust hue of an RGB image.

  This is a convenience method that converts an RGB image to float
  representation, converts it to HSV, add an offset to the hue channel, converts
  back to RGB and then back to the original data type. If several adjustments
  are chained it is advisable to minimize the number of redundant conversions.

  `image` is an RGB image.  The image hue is adjusted by converting the
  image to HSV and rotating the hue channel (H) by
  `delta`.  The image is then converted back to RGB.

  `delta` must be in the interval `[-1, 1]`.

  Args:
    image: RGB image or images. Size of the last dimension must be 3.
    delta: float.  How much to add to the hue channel.
    name: A name for this operation (optional).

  Returns:
    Adjusted image(s), same shape and DType as `image`.
  """
  with ops.name_scope(name, 'adjust_hue', [image]) as name:
    image = ops.convert_to_tensor(image, name='image')
    # Remember original dtype to so we can convert back if needed
    orig_dtype = image.dtype
    flt_image = convert_image_dtype(image, dtypes.float32)

    # TODO(zhengxq): we will switch to the fused version after we add a GPU
    # kernel for that.
    fused = os.environ.get('TF_ADJUST_HUE_FUSED', '')
    fused = fused.lower() in ('true', 't', '1')

    if not fused:
      hsv = gen_image_ops.rgb_to_hsv(flt_image)

      hue = array_ops.slice(hsv, [0, 0, 0], [-1, -1, 1])
      saturation = array_ops.slice(hsv, [0, 0, 1], [-1, -1, 1])
      value = array_ops.slice(hsv, [0, 0, 2], [-1, -1, 1])

      # Note that we add 2*pi to guarantee that the resulting hue is a positive
      # floating point number since delta is [-0.5, 0.5].
      hue = math_ops.mod(hue + (delta + 1.), 1.)

      hsv_altered = array_ops.concat_v2([hue, saturation, value], 2)
      rgb_altered = gen_image_ops.hsv_to_rgb(hsv_altered)
    else:
      rgb_altered = gen_image_ops.adjust_hue(flt_image, delta)

    return convert_image_dtype(rgb_altered, orig_dtype)
开发者ID:kdavis-mozilla,项目名称:tensorflow,代码行数:50,代码来源:image_ops_impl.py

示例3: testBatchAdjustHue

  def testBatchAdjustHue(self):
    x_shape = [2, 1, 2, 3]
    x_data = [0, 5, 13, 54, 135, 226, 37, 8, 234, 90, 255, 1]
    x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)

    delta = 0.25
    y_data = [13, 0, 11, 226, 54, 221, 234, 8, 92, 1, 217, 255]
    y_np = np.array(y_data, dtype=np.uint8).reshape(x_shape)

    with self.test_session():
      x = array_ops.placeholder(x_np.dtype, shape=x_shape)
      flt_x = image_ops.convert_image_dtype(x, dtypes.float32)
      with self.test_scope():
        y = gen_image_ops.adjust_hue(flt_x, delta)
      y = image_ops.convert_image_dtype(y, x.dtype, saturate=True)
      y_tf = y.eval({x: x_np})
      self.assertAllEqual(y_tf, y_np)
开发者ID:BhaskarNallani,项目名称:tensorflow,代码行数:17,代码来源:image_ops_test.py


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