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`pygame.mask`
  pygame module for image masks.

  Useful for fast pixel perfect collision detection. A mask uses 1 bit per-pixel to store which parts collide.

  New in pygame 1.8.

  `pygame.mask.``from_surface`()
    Returns a Mask from the given surface.
    from_surface(Surface, threshold = 127) -> Mask

    Makes the transparent parts of the Surface not set, and the opaque parts set.

    The alpha of each pixel is checked to see if it is greater than the given threshold.

    If the Surface is color-keyed, then threshold is not used.

  `pygame.mask.``from_threshold`()
    Creates a mask by thresholding Surfaces
    from_threshold(Surface, color, threshold = (0,0,0,255), othersurface = None, palette_colors = 1) -> Mask

    This is a more-featureful method of getting a Mask from a Surface. If supplied with only one Surface, all pixels within the threshold of the supplied color are set in the Mask. If given the optional othersurface, all pixels in Surface that are within the threshold of the corresponding pixel in othersurface are set in the Mask.

  `pygame.mask.``Mask`
    pygame object for representing 2d bitmasks
    Mask((width, height)) -> Mask
    `get_size`()
      Returns the size of the mask.
      get_size() -> width,height
    `get_at`()
      Returns nonzero if the bit at (x,y) is set.
      get_at((x,y)) -> int

      Coordinates start at (0,0) is top left - just like Surfaces.

    `set_at`()
      Sets the position in the mask given by x and y.
      set_at((x,y),value) -> None
    `overlap`()
      Returns the point of intersection if the masks overlap with the given offset - or None if it does not overlap.
      overlap(othermask, offset) -> x,y

      The overlap tests uses the following offsets (which may be negative):

          +----+----------..
          |A   | yoffset
          |  +-+----------..
          +--|B
          |xoffset
          |  |
          :  :

    `overlap_area`()
      Returns the number of overlapping 'pixels'.
      overlap_area(othermask, offset) -> numpixels

      You can see how many pixels overlap with the other mask given. This can be used to see in which direction things collide, or to see how much the two masks collide. An approximate collision normal can be found by calculating the gradient of the overlap area through the finite difference.

          dx = Mask.overlap_area(othermask,(x+1,y)) - Mask.overlap_area(othermask,(x-1,y))
          dy = Mask.overlap_area(othermask,(x,y+1)) - Mask.overlap_area(othermask,(x,y-1))

    `overlap_mask`()
      Returns a mask of the overlapping pixels
      overlap_mask(othermask, offset) -> Mask

      Returns a Mask the size of the original Mask containing only the overlapping pixels between Mask and othermask.

    `fill`()
      Sets all bits to 1
      fill() -> None

      Sets all bits in a Mask to 1.

    `clear`()
      Sets all bits to 0
      clear() -> None

      Sets all bits in a Mask to 0.

    `invert`()
      Flips the bits in a Mask
      invert() -> None

      Flips all of the bits in a Mask, so that the set pixels turn to unset pixels and the unset pixels turn to set pixels.

    `scale`()
      Resizes a mask
      scale((x, y)) -> Mask

      Returns a new Mask of the Mask scaled to the requested size.

    `draw`()
      Draws a mask onto another
      draw(othermask, offset) -> None

      Performs a bitwise `OR`, drawing othermask onto Mask.

    `erase`()
      Erases a mask from another
      erase(othermask, offset) -> None

      Erases all pixels set in othermask from Mask.

    `count`()
      Returns the number of set pixels
      count() -> pixels

      Returns the number of set pixels in the Mask.

    `centroid`()
      Returns the centroid of the pixels in a Mask
      centroid() -> (x, y)

      Finds the centroid, the center of pixel mass, of a Mask. Returns a coordinate tuple for the centroid of the Mask. In the event the Mask is empty, it will return (0,0).

    `angle`()
      Returns the orientation of the pixels
      angle() -> theta

      Finds the approximate orientation of the pixels in the image from -90 to 90 degrees. This works best if performed on one connected component of pixels. It will return 0.0 on an empty Mask.

    `outline`()
      list of points outlining an object
      outline(every = 1) -> [(x,y), (x,y) ...]

      Returns a list of points of the outline of the first object it comes across in a Mask. For this to be useful, there should probably only be one connected component of pixels in the Mask. The every option allows you to skip pixels in the outline. For example, setting it to 10 would return a list of every 10th pixel in the outline.

    `convolve`()
      Return the convolution of self with another mask.
      convolve(othermask, outputmask = None, offset = (0,0)) -> Mask

      Returns a mask with the (i-offset[0],j-offset[1]) bit set if shifting othermask so that its lower right corner pixel is at (i,j) would cause it to overlap with self.

      If an outputmask is specified, the output is drawn onto outputmask and outputmask is returned. Otherwise a mask of size `self.get_size()` + `othermask.get_size()` - (1,1) is created.

    `connected_component`()
      Returns a mask of a connected region of pixels.
      connected_component((x,y) = None) -> Mask

      This uses the `SAUF` algorithm to find a connected component in the Mask. It checks 8 point connectivity. By default, it will return the largest connected component in the image. Optionally, a coordinate pair of a pixel can be specified, and the connected component containing it will be returned. In the event the pixel at that location is not set, the returned Mask will be empty. The Mask returned is the same size as the original Mask.

    `connected_components`()
      Returns a list of masks of connected regions of pixels.
      connected_components(min = 0) -> [Masks]

      Returns a list of masks of connected regions of pixels. An optional minimum number of pixels per connected region can be specified to filter out noise.

    `get_bounding_rects`()
      Returns a list of bounding rects of regions of set pixels.
      get_bounding_rects() -> Rects

      This gets a bounding rect of connected regions of set pixels. A bounding rect is one for which each of the connected pixels is inside the rect.