Function isolines

Synopse

Isolines of a grayscale image.

g = isolines(f, nc=10, np=1)
- g: Image.
- f: Image. Input image.
- nc: Double. Number of colors.
- n: Double. Number of pixels by isoline.

Description

Shows lines where the pixels have same intensity with a unique color.



In [6]:

    
import numpy as np
def isolines(f, nc=10, n=1):
    from colormap import colormap
    from applylut import applylut
    
    maxi = int(np.ceil(f.max()))
    mini = int(np.floor(f.min()))
    d = int(np.ceil(1.*(maxi-mini)/nc))
    m = np.zeros((d,1))
    m[0:n,:] = 1
    m = np.resize(m, (maxi-mini, 1))
    m = np.concatenate((np.zeros((mini,1)), m))
    m = np.concatenate((m, np.zeros((256-maxi,1))))
    m = np.concatenate((m,m,m), 1)
    ct = m*colormap('hsv') + (1-m)*colormap('gray')
    g = applylut(f, ct)
    return g

Examples



In [1]:

    
testing = (__name__ == "__main__")
if testing:
    ! jupyter nbconvert --to python isolines.ipynb
    import numpy as np
    import sys,os
    ia898path = os.path.abspath('../../')
    if ia898path not in sys.path:
        sys.path.append(ia898path)
    import ia898.src as ia









    



[NbConvertApp] Converting notebook isolines.ipynb to python
[NbConvertApp] Writing 1470 bytes to isolines.py

Example 1



In [2]:

    
if testing:
    f = ia.normalize(ia.bwlp([150,150], 4, 1), [0,255])
    f = f.astype('uint8')
    g = ia.isolines(f, 10, 3)
    g = g.astype('uint8')

    ia.adshow(f)
    ia.adshow(g)



In [ ]: