GitLab

characters to take advantage of the fact that you can just write
the contents of memory out in this case.

even when compiling with unicode strings enabled.

over an image space and finding the locations where the sum of pixels in
the rectangles exceeds a threshold.

way it is obvious what file to #include to get them.

MAP inference.

alpha channel into something without an alpha channel there were
uninitialized values being alpha blended into the image.

which contain simple 8bit POD pixel types.  This makes the serialize
routines much faster in these cases.

 - Added width_step() to array2d to help define the memory layout.  Also added
   it to cv_image to keep the interfaces compatible.
 - Fixed a typo in the deserialize for array2d objects.  The template wasn't
   declared properly.

in BGR order rather than RGB.

they report the entire set of LOO prediction values rather than a
summary statistic like mean squared error.

mean_sign_agreement(), correlation(), covariance(), r_squared(),
and mean_squared_error()

when using the multiple selection feature.

available image data.  Previously, more pixels on the right and bottom
of the image were cropped than was necessary.

rectangular areas instead of just square areas.

code to not compile when used with the mingw-cross-env project.