A huge roadblock to pyth participating in many challenges was image i/o. In many cases it was impossible, and even when ppm was allowed, headers and formatting kills your score when both parsing and generating. So I added native image support to ' and .w with PIL.
' detects image file names and makes a nested array. It removes alpha when all 255 and condenses grayscale tuples into a single value.
.w detects arrays and does the reverse in regards to alpha and grayscale. I also changed the default filename behavior in .w. It now first creates a filename-prefix, defaulting to "o" which you can override by passing in like "foo"and then a suffix which defaults to .png and .txt. You cant override just suffix, but you both as expected like "foo.jpg".
A possible improvement that might be disruptive is on .w to take grayscale images with only 0 and 1 as values and assume B&W and make the 1's 255's, and the opposite on '.
A huge roadblock to pyth participating in many challenges was image i/o. In many cases it was impossible, and even when
ppmwas allowed, headers and formatting kills your score when both parsing and generating. So I added native image support to'and.wwith PIL.'detects image file names and makes a nested array. It removes alpha when all 255 and condenses grayscale tuples into a single value..wdetects arrays and does the reverse in regards to alpha and grayscale. I also changed the default filename behavior in.w. It now first creates a filename-prefix, defaulting to"o"which you can override by passing in like"foo"and then a suffix which defaults to.pngand.txt. You cant override just suffix, but you both as expected like"foo.jpg".A possible improvement that might be disruptive is on
.wto take grayscale images with only0and1as values and assume B&W and make the1's255's, and the opposite on'.