Laziness plays a big role in real world image processing. Typically, in applications like Apple's Shake, you build a dataflow representation of the image processing operations you wish to perform, and the final result is computed lazily so as to reduce the amount of computation. For example, if you blur an image, and then zoom in on the top left corner, then only the top left corner will be loaded up from the original image (assuming your image file format supports tiled access). You still work on tiles or scan-lines, rather than individual pixels, so the laziness has a 'coarse' granularity. But I'm not sure if this is what the original poster was talking about. -- Dan On 10/29/07, jerzy.karczmarczuk@info.unicaen.fr <jerzy.karczmarczuk@info.unicaen.fr> wrote:
[iso-8859-1] Bj�rn Wikstr�m writes:
Hi! I have lots and lots of images (jpegs) that I would like to manipulate and shrink (in size). They are around 5 Mb big, so I thought this would be a good Haskell project since it's a lazy evaluating language. ...
I must say that I don't see much use of laziness here.