Dominant color & PIL

[Sebastjan Trepca]

Hehe, interesting. I'll try it out.

Thanks, Sebastjan


On 1/23/06, Terry Hancock <hancock at anansispaceworks.com> wrote:
>
> On 23 Jan 2006 05:47:58 -0800
> "Rinzwind" <w.damen at gmail.com> wrote:
> > For example:
> >
> > getdata
> >
> > im.getdata() => sequence
> >
> > Returns the contents of an image as a sequence object
> > containing pixel values. The sequence object is flattened,
> > so that values for line one follow directly after the
> > values of line zero, and so on.
> >
> > Note that the sequence object returned by this method is
> > an internal PIL data type, which only supports certain
> > sequence operations. To convert it to an ordinary sequence
> > (e.g. for printing), use list(im.getdata()).
> >
> > So you could get them and count them in :)
> > Don't know if you should do that on a 1600x1200 wallpaper
> > tho :D
>
> I think he's thinking of how to get the values for the
> master image.
>
> > Terry Hancock wrote:
> > > On Sun, 22 Jan 2006 21:07:45 +0100
> > > Sebastjan Trepca <trepca at gmail.com> wrote:
> > > > I was wondering is it possible to find out which
> > > > colour is dominant in an image using PIL?
> > > > It would be very easy to create interesting mozaic
> > > > images with that :)
> > >
> > > Shrink it to one pixel, and get that pixel's value. ;-)
> > >
> > > Seriously, that ought to do it.  Bear in mind that you
> > > need to use the right sampling mode (IIRC, you want
> > > ANTIALIAS).
>
> This is answering the OP's question which is how to get
> the average color for a whole image:
>
> color = img.resize( (1,1), Image.ANTIALIAS).getpixel((0,0))
>
> You just shrink the image down. The ANTIALIAS filter
> averages every pixel in the image (this occurs in the PIL
> library, so it's probably pretty fast), and then you fish
> the single remaining pixel out into tuple format.
>
> --
> Terry Hancock (hancock at AnansiSpaceworks.com)
> Anansi Spaceworks http://www.AnansiSpaceworks.com
>
> --
> http://mail.python.org/mailman/listinfo/python-list
>
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