How to evaluate difference between RGB numpy arrays?

Question

I'm building a software for a LED Canvas with 24 x 30 pixels. And I want to save the current state in a numpy array, then get a new state as a numpy array and slowly fade from the first state to the second state.

To do so I was thinking i have to compare my two numpy arrays:

currentState = np.zeros((24,30,3), 'int_') # All LEDs off e.g.
newState = np.zeros((24,30,3), 'int_') + 255 # All LEDS full white

Now i need an array with the difference between each item on the matrix like

currentState[x][y] = [0, 0, 0]
newState[x][y] = [255, 255, 255]
# Some compare operation
difference[x][y] = [255, 255, 255]

# or e.g.

currentState[x][y] = [255, 70, 30]
newState[x][y] = [100, 255, 30]
# Some compare operation
difference[x][y] = [-155, 185, 0]

Since execution time is crutial i don't wanna iterate over the matrix arrays. Is there any other way?

Thanks a lot in advance.

The answer is not currentState - newState. Please look carefully on the second example.

Can you please unmark as duplicate. It's not the same issue. Look at the second example i gave... the simple subtract does not work for that. it would be difference[x][y] = [155, - 115, 0] -> Not what I need! — xioverflow, Jul 24 '19 at 17:51
How would you get that if you subtract `currentState` from `newState`? `100-255 = -155`, `255-70=185`, and `30-30=0`. You're subtracting in the wrong order — user3483203, Jul 24 '19 at 17:52

score 0 · Accepted Answer · answered Jul 24 '19 at 17:21

0

Literally just subtract them:

difference = newState - currentState

answered Jul 24 '19 at 17:21

Akaisteph7

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Look at the second example i gave. This would not work: ``` currentState[x][y] = [255, 70, 30] newState[x][y] = [100, 255, 30] # Some compare operation difference[x][y] = [-155, 185, 0] ``` – xioverflow Jul 24 '19 at 17:43
@stackcrossiflow Did you try it? I did and it works. – Akaisteph7 Jul 24 '19 at 17:56
You are totally right, sorry! – xioverflow Jul 24 '19 at 18:08

How to evaluate difference between RGB numpy arrays?

1 Answers1