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Extending c functionality of PIL

开发者 https://www.devze.com 2023-02-14 09:35 出处:网络
I want to create functionality similar to PIL\'s Image.blend, using a different blending algorithm.To do this would I need to: (1) directly modify the PIL modules and compile my own custom PIL or (2)

I want to create functionality similar to PIL's Image.blend, using a different blending algorithm. To do this would I need to: (1) directly modify the PIL modules and compile my own custom PIL or (2) write a python c module which imports and extends PIL?

I have unsuccessfully tried:

#include "_imaging.c"

I also was trying to just pull out the parts I need from the PIL source and put them in my own file. The farther I got in the more things I had to pull and it seems that is not the ideal solution.

UPDATE: edited to add the blending algorithm implemented in python (this emulates the overlay blending mode in Photoshop):

def overlay(upx, lpx):
    return (2 * upx * lpx / 255 ) if lpx < 128 else ((255-2 * (255 - upx) * (255 - lpx) / 255))

def blend_images(upper = None, lower = None):
    upixels = upper.load()
    lpixels = lower.load()
    width, height = upper.size
    pixeldata = [0] * len(upixels[0, 0])
    for x in range(width):
        for y in range(height):
            # the next for loop is to deal with images of any number of bands
            for i in range(len(upixels[x,y])):
                pixeldata[i] =  overlay(upixels[x, y][i], lpixels[x, y][i])
            upixels[x,y] = tuple(pixeldata)
    return upper

I have also unsuccessfully tried implementing this using scipy's weave.inline:

def blend_images(upper=None, lower=None):
    upixels = numpy.array(upper)
    lpixels = numpy.array(lower)
    width, height = upper.size
    nbands = len(upixels[0,0])
    code = """
        #line 120 "laplace.py" (This is only useful for debug开发者_开发技巧ging)
        int upx, lpx;
        for (int i = 0; i < width-1; ++i) {
            for (int j=0; j<height-1; ++j) {
                for (int k = 0; k < nbands-1; ++k){
                    upx = upixels[i,j][k];
                    lpx = lpixels[i,j][k];
                    upixels[i,j][k] = ((lpx < 128) ? (2 * upx * lpx / 255):(255 - 2 * (255 - upx) * (255 - lpx) / 255));
                }
            }
        }
        return_val = upixels;
        """
        # compiler keyword only needed on windows with MSVC installed
    upixels = weave.inline(code,
                           ['upixels', 'lpixels', 'width', 'height', 'nbands'],
                           type_converters=converters.blitz,
                           compiler = 'gcc')
    return Image.fromarray(upixels)

I'm doing something wrong with the upixel and lpixel arrays but I'm not sure how to fix them. I'm a bit confused about the type of upixels[i,j][k], and not sure what I could assign it to.


Here's my implementation in NumPy. I have no unit tests, so I do not know if it contains bugs. I assume I'll hear from you if it fails. Explanation of what is going on is in the comments. It processes a 200x400 RGBA image in 0.07 seconds

import Image, numpy

def blend_images(upper=None, lower=None):
    # convert to arrays
    upx = numpy.asarray(upper).astype('uint16')
    lpx = numpy.asarray(lower).astype('uint16')
    # do some error-checking
    assert upper.mode==lower.mode
    assert upx.shape==lpx.shape
    # calculate the results of the two conditions
    cond1 = 2 * upx * lpx / 255
    cond2 = 255 - 2 * (255 - upx) * (255 - lpx) / 255
    # make a new array that is defined by condition 2
    arr = cond2
    # this is a boolean array that defines where in the array lpx<128
    mask = lpx<128
    # populate the parts of the new arry that meet the critera for condition 1
    arr[mask] = cond1[mask]
    # prevent overflow (may not be necessary)
    arr.clip(0, 255, arr)
    # convert back to image
    return Image.fromarray(arr.astype('uint8'), upper.mode)
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