Halostack Image module¶

Module for image I/O and conversions

class halostack.image.Image(img=None, fname=None, enhancements=None, nprocs=1)¶

Bases: object

Class for handling images.

Parameters:	img (ndarray or None) – array holding image data fname (str or None) – image filename enhancements (dictionary or None) – image processing applied to the image nprocs (int) – number or parallel processes

enhance(enhancements)¶

Enhance the image with the given function(s) and argument(s).

Parameters:	enhancements (dictionary) – image processing methods

Available image processing methods:

br: Blue - Red
- possible calls:
  - {'br': None}
  - {'br': float}
- optional arguments:
  - float: multiplier for blue channel [mean(red/green)]
gr: Green - Red
- possible calls:
  - {'gr': None}
  - {'gr': float}
- optional arguments:
  - float: multiplier for red channel [mean(green/red)]
bg: Blue - Green
- possible calls:
  - {'bg': None}
  - {'bg': float}
- optional arguments:
  - float: multiplier for blue channel [mean(blue/green)]
emboss: emboss image using ImageMagick
- possible calls:
  - {'emboss': None}
  - {'emboss': float}
  - {'emboss': [float, float]}
- optional arguments:
  - float: light source azimuth in degrees [90]
  - float: light source elevation in degrees [45]
gamma: gamma correction using ImageMagick
- possible calls:
  - {'gamma': float}
- required arguments:
  - float: gamma value
gradient: remove image gradient
- possible calls:
  - {'gradient': None}
  - {'gradient': float}
- optional arguments:
  - float (blur radius) [min(image dimensions)/20]
rgb_sub: Subtract luminance from each color channel
- possible calls:
  
  {'rgb_sub': None}
rgb_mix: Subtract luminance from each color channel and mix it back to the original image
- possible calls:
  
  {'rgb_mix': None} {'rgb_mix': float}
- optional arguments:
  - float: mixing ratio [0.7]
stretch: linear histogram stretch
- possible calls:
  - {'stretch': None}
  - {'stretch': float}
  - {'stretch': [float, float]}
- optional arguments:
  - float: low cut threshold [0.01]
  - float: high cut threshold [1 - <low cut threshold>]
usm: unsharp mask using ImageMagick
- possible calls:
  - {'usm': [float, float]}
  - {'usm': [float, float, float]}
  - {'usm': [float, float, float, float]}
- required arguments:
  - float: radius
  - float: amount
- optional arguments:
  - float: standard deviation of the gaussian [sqrt(radius)]
  - float: threshold [0]

luminance()¶

Return luminance (channel average) as Numpy ndarray.

Return type:	Numpy ndarray

max()¶

Return the maximum value in the image.

Return type:	float

min()¶

Return the minimum value in the image.

Return type:	float

save(fname, bits=16, enhancements=None)¶

Save the image data.

Parameters:	fname (str) – output filename bits (int) – output bit-depth enhancements (dictionary or None) – image processing applied to the image before saving

to_numpy()¶: Convert from PMImage to Numpy ndarray.

halostack.image.polyfit2d(x_loc, y_loc, z_val, order=2)¶

Fit a 2-D polynomial to the given data.

Implementation from: http://stackoverflow.com/a/7997925

Parameters:	x_loc (list or ndarray) – X coordinates y_loc (list or ndarray) – Y coordinates z_val (list or ndarray) – Z values at (X, Y) order (integer) – order of the polynomial
Return type:	list of polynomial coefficients as floats

halostack.image.polyval2d(x_loc, y_loc, poly)¶

Evaluate 2-D polynomial poly at the given locations

Implementation from: http://stackoverflow.com/a/7997925

Parameters:	x_loc (list or Numpy array) – X coordinates y_loc (list or Numpy array) – Y coordinates poly (list of floats) – polynomial coefficients

halostack.image.to_imagemagick(img, bits=16)¶

Convert numpy array to Imagemagick format.

Parameters:	img (Numpy ndarray) – image to convert
Return type:	PythonMagick.Image

halostack.image.to_numpy(img)¶

Convert ImageMagick data to numpy array.

Parameters:	img (PythonMagick.Image) – image to convert
Return type:	Numpy ndarray