find_board.docstring

Runs the full mrgingham chessboard detector on an image

SYNOPSIS

    points = mrgingham.find_board(image)

    [ points is an array of shape (N*N,2), the ordered list of ]
    [ pixel coordinates in the grid ]

This function runs the full mrgingham sequence:

- pre-process image
- find chessboard corners (or blobs)
- find an NxN grid in the set of corners
- refine

No broadcasting is supported by this function

ARGUMENTS

- image: numpy array of shape (H,W) and dtype np.uint8. This is the image we're
  processing. Must be densely-stored, grayscale image

- blobs: optional boolean, defaulting to False. If True, we look for
  black-on-white blobs, instead of chessboard corners. If blobs: we MUST have
  image_pyramid_level==0

- image_pyramid_level: optional integer defaulting to -1. This can be given to
  operate on a downsampled version of the image. 0 means "original image", 1
  means "downsample by a factor of 2 in each dimension", 2 means "downsample by
  a factor of 4 in each dimension" and so on. image_pyramid_level < 0 (the
  default) means "start with a downsampled image, and then refine the results by
  repeatedly reducing the downsampling. If blobs: image_pyramid_level==0 is the
  only allowed option

- gridn: optional integer defaulting to 10. We detect an NxN grid of corners,
  where N is given by this argument

- debug: optional boolean, defaulting to False. If True, this will dump various
  intermediate results into /tmp and it will report more stuff on standard out.
  Most of the intermediate results are self-plotting data files. Run them. This
  does the same thing as "mrgingham --debug"; the Python output is unaffected.

- debug_sequence: optional string "X,Y" where X and Y are integers. In addition
  to "debug", this produces diagnostics when searching for sequence candidates.
  X,Y are the approximate image coordinates of the start of a given sequence
  (corner on the edge of a chessboard. This doesn't need to be exact; mrgingham
  will report on the nearest corner. This does the same thing as "mrgingham
  --debug-sequence"; the Python output is unaffected.

RETURNED VALUE

A numpy array of shape (N*N,2) containing ordered pixel coordinates of the grid
found in the image. If no grid was found, None is returned.