parameters: (src, w, h, *args, **kwargs)
return_statement: return _internal._cvimresize(src, w, h, *args, **kwargs)
docstring: r"""Resize image with OpenCV.
  
      .. note:: `imresize` uses OpenCV (not the CV2 Python library). MXNet must have been built
         with USE_OPENCV=1 for `imresize` to work.
  
      Parameters
      ----------
      src : NDArray
          source image
      w : int, required
          Width of resized image.
      h : int, required
          Height of resized image.
      interp : int, optional, default=1
          Interpolation method (default=cv2.INTER_LINEAR).
          Possible values:
          0: Nearest Neighbors Interpolation.
          1: Bilinear interpolation.
          2: Bicubic interpolation over 4x4 pixel neighborhood.
          3: Area-based (resampling using pixel area relation). It may be a
          preferred method for image decimation, as it gives moire-free
          results. But when the image is zoomed, it is similar to the Nearest
          Neighbors method. (used by default).
          4: Lanczos interpolation over 8x8 pixel neighborhood.
          9: Cubic for enlarge, area for shrink, bilinear for others
          10: Random select from interpolation method metioned above.
          Note:
          When shrinking an image, it will generally look best with AREA-based
          interpolation, whereas, when enlarging an image, it will generally look best
          with Bicubic (slow) or Bilinear (faster but still looks OK).
          More details can be found in the documentation of OpenCV, please refer to
          http://docs.opencv.org/master/da/d54/group__imgproc__transform.html.
  
      out : NDArray, optional
          The output NDArray to hold the result.
  
      Returns
      -------
      out : NDArray or list of NDArrays
          The output of this function.
  
      Example
      -------
      >>> with open("flower.jpeg", 'rb') as fp:
      ...     str_image = fp.read()
      ...
      >>> image = mx.img.imdecode(str_image)
      >>> image
      <NDArray 2321x3482x3 @cpu(0)>
      >>> new_image = mx.img.resize(image, 240, 360)
      >>> new_image
      <NDArray 240x360x3 @cpu(0)>
docstring_summary: r"""Resize image with OpenCV.
docstring_tokens: r Resize image with OpenCV .
function: def imresize(src, w, h, *args, **kwargs):
      r"""Resize image with OpenCV.
  
      .. note:: `imresize` uses OpenCV (not the CV2 Python library). MXNet must have been built
         with USE_OPENCV=1 for `imresize` to work.
  
      Parameters
      ----------
      src : NDArray
          source image
      w : int, required
          Width of resized image.
      h : int, required
          Height of resized image.
      interp : int, optional, default=1
          Interpolation method (default=cv2.INTER_LINEAR).
          Possible values:
          0: Nearest Neighbors Interpolation.
          1: Bilinear interpolation.
          2: Bicubic interpolation over 4x4 pixel neighborhood.
          3: Area-based (resampling using pixel area relation). It may be a
          preferred method for image decimation, as it gives moire-free
          results. But when the image is zoomed, it is similar to the Nearest
          Neighbors method. (used by default).
          4: Lanczos interpolation over 8x8 pixel neighborhood.
          9: Cubic for enlarge, area for shrink, bilinear for others
          10: Random select from interpolation method metioned above.
          Note:
          When shrinking an image, it will generally look best with AREA-based
          interpolation, whereas, when enlarging an image, it will generally look best
          with Bicubic (slow) or Bilinear (faster but still looks OK).
          More details can be found in the documentation of OpenCV, please refer to
          http://docs.opencv.org/master/da/d54/group__imgproc__transform.html.
  
      out : NDArray, optional
          The output NDArray to hold the result.
  
      Returns
      -------
      out : NDArray or list of NDArrays
          The output of this function.
  
      Example
      -------
      >>> with open("flower.jpeg", 'rb') as fp:
      ...     str_image = fp.read()
      ...
      >>> image = mx.img.imdecode(str_image)
      >>> image
      <NDArray 2321x3482x3 @cpu(0)>
      >>> new_image = mx.img.resize(image, 240, 360)
      >>> new_image
      <NDArray 240x360x3 @cpu(0)>
      """
      return _internal._cvimresize(src, w, h, *args, **kwargs)
function_tokens: def imresize ( src , w , h , * args , * * kwargs ) : return _internal . _cvimresize ( src , w , h , * args , * * kwargs )