message: Add example usage for tf.keras.preprocessing.image.load_img.
diff: @@ -41,7 +41,6 @@ random_channel_shift = image.random_channel_shift
  apply_brightness_shift = image.apply_brightness_shift
  random_brightness = image.random_brightness
  apply_affine_transform = image.apply_affine_transform
  -load_img = image.load_img
  @keras_export('keras.preprocessing.image.array_to_img')
  @@ -158,6 +157,44 @@ def save_img(path,
  scale=scale, **kwargs)
  +def load_img(path, grayscale=False, color_mode='rgb', target_size=None,
  + interpolation='nearest'):
  + """Loads an image into PIL format.
  +
  + Usage:
  +
  + ```
  + image = tf.keras.preprocessing.image.load_img(image_path)
  + input_arr = keras.preprocessing.image.img_to_array(image)
  + input_arr = np.array([input_arr]) # Convert single image to a batch.
  + predictions = model.predict(input_arr)
  + ```
  +
  + Arguments:
  + path: Path to image file.
  + grayscale: DEPRECATED use `color_mode="grayscale"`.
  + color_mode: One of "grayscale", "rgb", "rgba". Default: "rgb".
  + The desired image format.
  + target_size: Either `None` (default to original size)
  + or tuple of ints `(img_height, img_width)`.
  + interpolation: Interpolation method used to resample the image if the
  + target size is different from that of the loaded image.
  + Supported methods are "nearest", "bilinear", and "bicubic".
  + If PIL version 1.1.3 or newer is installed, "lanczos" is also
  + supported. If PIL version 3.4.0 or newer is installed, "box" and
  + "hamming" are also supported. By default, "nearest" is used.
  +
  + Returns:
  + A PIL Image instance.
  +
  + Raises:
  + ImportError: if PIL is not available.
  + ValueError: if interpolation method is not supported.
  + """
  + return image.load_img(path, grayscale=grayscale, color_mode=color_mode,
  + target_size=target_size, interpolation=interpolation)
  +
  +
  @keras_export('keras.preprocessing.image.Iterator')
  class Iterator(image.Iterator, data_utils.Sequence):
  pass
  