Example source code for histogram equalization
and compare with origin histogram and stretching histogram.
result is like that:
origin image & histogram
stretching image and histogram
Equalization image and histogram
<gist>
</gist>
tags:
equalizeHist, cvtColor, normalize, calcHist
1/14/2018
Histogram Equalization, Stretching, origin histo compare and example source code
Labels:
calcHist,
cvtColor,
equalizeHist,
Histogram,
histogram equalization,
histogram stretch,
normalize,
OpenCV,
Total
1/12/2018
python list, numpy slicing
Oh.. I seem to be old.. I need a memo everything..
This is memo for me about list slicing.
result
[0, 1, 2, 3, 4]
[2, 3]
[2, 3, 4]
[0, 1]
[0, 1, 2, 3, 4]
[0, 1, 2, 3]
[0, 1, 8, 9, 4]
numpy slicing
This is memo for me about list slicing.
nums = list(range(5)) print(nums) #[0, 1, 2, 3, 4] print(nums[2:4]) #[2, 3] print(nums[2:]) #[2, 3, 4] print(nums[:2]) #[0, 1] print(nums[:]) #[0, 1, 2, 3, 4] print(nums[:-1]) #[0, 1, 2, 3] nums[2:4] = [8,9] print(nums) #[0, 1, 8, 9, 4]
result
[0, 1, 2, 3, 4]
[2, 3]
[2, 3, 4]
[0, 1]
[0, 1, 2, 3, 4]
[0, 1, 2, 3]
[0, 1, 8, 9, 4]
numpy slicing
πimport numpy as np a = np.array([1, 2, 3, 4, 5]) print(a[1:3]) #array [2 3]print(a[-1]) #5a[0:2] = 9print(a) #array [9 9 3 4 5] b = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) print(b) #array#[[ 1 2 3 4]
# [ 5 6 7 8]
# [ 9 10 11 12]]
print(b[:,1]) #array [2 6 10] print(b[-1]) #array [9 10 11 12]print(b[-1,:]) #array [9 10 11 12]print(b[-1, ...]) #array [9 10 11 12]print(b[0:2, :]) #array#[[1 2 3 4]# [5 6 7 8]]
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