On Mon, May 18, 2009 at 10:15 AM, Jesper Larsen <jesper.webm...@gmail.com> wrote:
> I am producing some png images for a web application. Some of the > images are cached and reused for other requests. I am using matplotlib > to produce the images. Unfortunately the images are quite large (up to > ~300 kb). I therefore tried using the Linux utilities pngcrush and > pngnq for compressing the images. pngnq gave by far the best results > (~300 kb -> ~90 kb in 0.4-0.5 seconds on my laptop; combining the two > tools did not yield further improvements). It reduces the color depth > to 8 bits (from 24) without any apparent image quality problems using > color quantization (http://en.wikipedia.org/wiki/Color_quantization). > > Is it possible to do this in PIL directly or will I have to code it > myself? At present I am considering just calling pngnq from my Python > code but I would rather not do that. > > Another thing is that for performance reasons I might want later to > reuse the colormap (since the image colors are pretty much the same). > Neither pngnq nor pngquant (which pngnq is based on) supports this > yet. If you convert the image to mode "P" before you save it, you get a fixed 8-bit palette by default (based on "web safe colors"). To have PIL pick an "optimal" palette instead, use convert("P", palette=Image.ADAPTIVE). See http://effbot.org/tag/PIL.Image.Image.convert for more options. The algorithm used by pngnq seems to be a bit better (though a lot slower) than PIL's median cut algorithm, so you might not get quite as good results as you get with pngnq. </F> _______________________________________________ Image-SIG maillist - Image-SIG@python.org http://mail.python.org/mailman/listinfo/image-sig
