Jython将图片转换为灰度，然后取反 [英] Jython convert picture to grayscale and then negate it

问题描述

请多多包涵，几周前我才开始使用python.

Please bear with me, I've only started python a few weeks ago.

我正在使用JES.

我已经实现了将图片转换为灰度的功能.我为每种颜色r和r1，g和g1，b和b1创建了两个名称.其背后的想法是将原始值保留在内存中，以便图片可以恢复为原始颜色.

I have made a function to convert a picture to grayscale. I created two names for each color r and r1, g and g1, b and b1. The idea behind this, was to keep the original values in memory, so the picture could be restored to it's original color.

def grayScale(pic):
  for p in getPixels(pic):
    r = int(getRed(p))
    g = int(getGreen(p))
    b = int(getBlue(p))//I have tried this with and without the int()
    r1=r
    g1=g
    b1=b
    new = (r + g + b)/3
    color= makeColor(new,new,new)
    setColor(p, color)


def restoreColor(pic):
  for p in getPixels(pic):
    setColor (p, makeColor(r1,g1,b1))

它不起作用. The error: "local or global name could not be found."

我了解为什么会收到此错误.

I understand why I am getting this error.

但是，如果我尝试在restoreColor中定义它们，它将给出灰度值.

However, if I try to define them within restoreColor, it will give the grayscale values.

我了解为什么会收到此错误，但不知道如何格式化代码以保存名称值.我研究了有关局部和全局变量/名称的问题；但我无法在所学的基本语法范围内解决该问题.

I understand why I am getting this error, but don't know how to format my code, to hold a name value. I have looked at questions about local and global variables/names; but I cannot work out, within the rudimentary syntax I have learnt, how to do this.

问题是:

如何为原始名称(红色，绿色，蓝色)创建名称并获取其值，然后在以后的其他功能中使用它们?我尝试过的所有操作都返回了更改后的(灰度)值. thnx

How to I create names and get their values for the original (red, green, blue) that I can then use later in another function? Everything I have tried, has returned the altered (grayscale) values. thnx

推荐答案

只需添加一种艺术性"的观点:

Just to add an "artistic" point of view:

您在程序中使用的是(r + g + b)/3 ，但是还有其他算法:

You are using (r + g + b) / 3 in your program, but there is other algorithms:

1) lightness method平均最突出和最不突出的颜色:

1) The lightness method averages the most prominent and least prominent colors:

(max(R, G, B) + min(R, G, B)) / 2

2) average method(您的)只是对这些值求平均值:

2) The average method (yours) simply averages the values:

(R + G + B) / 3

3) luminosity method是平均值方法的更复杂的版本.它还对这些值取平均值，但形成一个加权平均值以说明人的感知.我们对绿色的敏感度高于其他颜色，因此绿色的权重最大.发光度的公式为:

3) The luminosity method is a more sophisticated version of the average method. It also averages the values, but it forms a weighted average to account for human perception. We’re more sensitive to green than other colors, so green is weighted most heavily. The formula for luminosity is:

0.21 R + 0.71 G + 0.07 B

这可以带来很大的不同(亮度之间的差异要大得多):

This can make a big difference (luminosity is way far more contrasted):

      original           |         average          |         luminosity 

....... .......... ........ ............ ....... ........

....................................................

代码:

Code :

px = getPixels(pic)
level = int(0.21 * getRed(px) + 0.71 * getGreen(px) + 0.07 * getBlue(px))
color = makeColor(level, level, level)

要求反/求反，只需执行以下操作:

And to negate / invert, simply do:

level = 255 - level

给予:

def greyScaleAndNegate(pic):  

   for px in getPixels(pic):
      level = 255 - int(0.21*getRed(px) + 0.71*getGreen(px) +0.07*getBlue(px))
      color = makeColor(level, level, level)
      setColor(px, color)


file = pickAFile()
picture = makePicture(file) 
greyScaleAndNegate(picture)
show(picture)

---

      original          |         luminosity        |           negative

......... ......... .............. ...... ................... . .....

...................................................................

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