python - Jython convert picture to grayscale and then negate it

Question

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

I am using JES.

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))

It's not working. The error: "local or global name could not be found."

I understand why I am getting this error.

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

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.

The problem is:

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

Answer 1

Just to add an "artistic" point of view:

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

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

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

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

(R + G + B) / 3

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

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

      original           |         average          |         luminosity 

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

---

Code :

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

And to negate / invert, simply do:

level = 255 - level

Which give :

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

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