>
> a) Work with the 3 components in parallel (that is, use 3 separate
> matrices, one for each component, and regenerate the image at the
> end).
that wd be ok for image generation ..but to calculate covariance
matrix from the set of images i don't know if it wd work
eric
--
http://mail.pyth
> > def rgbTopixelvalue((r,g,b)):
> >alpha=255
> >return unpack("l", pack("", b, g, r, alpha))[0]
>
> That's much worse than averaging the R,G,B components.
oops!
the intention was to pack r,g,b components into a single value sothat
calculations like finding covariant matrix of a set
On Feb 19, 1:38 am, Robert Kern <[EMAIL PROTECTED]> wrote:
>Averaging color
> images is tricky; you really shouldn't do it in the RGB colorspace.
hi,
thanx for the guidance and detailed replies..I tried to pack the
r,g,b into a single value like below(something a member posted in the
past)
def
On Feb 19, 1:38 am, Robert Kern <[EMAIL PROTECTED]> wrote:
>Averaging color
> images is tricky; you really shouldn't do it in the RGB colorspace.
hi,
thanx for the guidance and detailed replies..I tried to pack the
r,g,b into a single value like below(something a member posted in the
past)
def r
hi
i have a set of RGB images of diff faces (of people )as a 2 dim
numpyarray
..something like
threefaces=array([[xa1,xa2,xa3],
[xb1,xb2,xb3],
[xc1,xc2,xc3]])
where xa1,xa2,xa3 are tuples each representing rgb values of a pixel
of first image ..
i need to create the average face ima
