CODEWITHSUNDEEP
pythonnumpy
PolarBear10
PolarBear10

Reputation: 2305

Get the average value of the pixel across all the frames

I have 14400 values saved in a list which represent a 4 pixels vertical by 6 pixels horizontal and 600 frames.

Here are the values if anyone is interested

# len of blurry values 14400
data = np.array(blurry_values)

#shape of data (4, 6, 600)
shape = ( 4,6,600 )
data= data.reshape(shape)

#print(np.round(np.mean(data, axis=2),2))

[[0.89 0.37 0.45 0.44 0.51 0.52]
 [0.5  0.47 0.53 0.48 0.48 0.53]
 [0.49 0.5  0.5  0.53 0.48 0.54]
 [0.48 0.51 0.45 0.55 0.5  0.49]]

However, when I confirm the sanity of the first average by doing the following

list1 = blurry_values[::23]
np.round(np.mean(list1),2)

I get 0.51 instead of 0.89

I am trying to get the average value of the pixel across all the frames. Why are these values different?

Upvotes: 0

Views: 300

Answers (3)

fountainhead
fountainhead

Reputation: 3722

Since I haven't seen the code that produced blurry_values, I can't be 100% sure, but I'm guessing that you're re-shaping blurry_values wrongly.

In most programming scenarios, I would expect the pixel-height and pixel-width to be represented by the last two axes, and the frame to be represented by an axis preceding these two.

So, I'm guessing that your shape should have been shape = (600, 4, 6) instead of shape = (4, 6, 600).

In that case, you should be doing np.round(np.mean(data, axis=0),2) rather than np.round(np.mean(data, axis=2),2). BTW, that would also produce a shape of (4, 6).

Then, for your sanity check, you should be doing this:

list1 = blurry_values[::24] # Note that it's 24, not 23
np.round(np.mean(list1),2)

You should be checking whether the first value of np.round(np.mean(data, axis=0),2), with the first value of np.round(np.mean(list1),2). (I haven't tested it myself, though).

Upvotes: 1

David M.
David M.

Reputation: 4588

Let us tackle this with a smaller array:

import numpy as np
np.random.seed(42)

values = np.random.randint(low=0, high=100, size=48)
shape = (2,4,6)
data = values.reshape(shape)  # 2 frames of 4 pixels by 6 pixels each

print(data, '\n')

print(np.round(np.mean(data, axis=0),2), '\n')  # average values across frames

list1 = values[::24]
print(np.round(np.mean(list1),2))  # average of first pixel across frames

Output:

[[[51 92 14 71 60 20]
  [82 86 74 74 87 99]
  [23  2 21 52  1 87]
  [29 37  1 63 59 20]]

 [[32 75 57 21 88 48]
  [90 58 41 91 59 79]
  [14 61 61 46 61 50]
  [54 63  2 50  6 20]]] 

[[41.5 83.5 35.5 46.  74.  34. ]
 [86.  72.  57.5 82.5 73.  89. ]
 [18.5 31.5 41.  49.  31.  68.5]
 [41.5 50.   1.5 56.5 32.5 20. ]] 

41.5

Upvotes: 2

ce.teuf
ce.teuf

Reputation: 786

I don't know exactly why, but :

list1 = blurry_values[:600]

gives 0.89

list1 = blurry_values[600:1200]

gives 0.37

Python starts reshaping by first filling the last dimension, i believe..

Upvotes: 2

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