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      1 #!/usr/bin/env python
      2 
      3 '''
      4 gabor_threads.py
      5 =========
      6 
      7 Sample demonstrates:
      8 - use of multiple Gabor filter convolutions to get Fractalius-like image effect (http://www.redfieldplugins.com/filterFractalius.htm)
      9 - use of python threading to accelerate the computation
     10 
     11 Usage
     12 -----
     13 gabor_threads.py [image filename]
     14 
     15 '''
     16 
     17 import numpy as np
     18 import cv2
     19 from multiprocessing.pool import ThreadPool
     20 
     21 
     22 def build_filters():
     23     filters = []
     24     ksize = 31
     25     for theta in np.arange(0, np.pi, np.pi / 16):
     26         kern = cv2.getGaborKernel((ksize, ksize), 4.0, theta, 10.0, 0.5, 0, ktype=cv2.CV_32F)
     27         kern /= 1.5*kern.sum()
     28         filters.append(kern)
     29     return filters
     30 
     31 def process(img, filters):
     32     accum = np.zeros_like(img)
     33     for kern in filters:
     34         fimg = cv2.filter2D(img, cv2.CV_8UC3, kern)
     35         np.maximum(accum, fimg, accum)
     36     return accum
     37 
     38 def process_threaded(img, filters, threadn = 8):
     39     accum = np.zeros_like(img)
     40     def f(kern):
     41         return cv2.filter2D(img, cv2.CV_8UC3, kern)
     42     pool = ThreadPool(processes=threadn)
     43     for fimg in pool.imap_unordered(f, filters):
     44         np.maximum(accum, fimg, accum)
     45     return accum
     46 
     47 if __name__ == '__main__':
     48     import sys
     49     from common import Timer
     50 
     51     print __doc__
     52     try:
     53         img_fn = sys.argv[1]
     54     except:
     55         img_fn = '../data/baboon.jpg'
     56 
     57     img = cv2.imread(img_fn)
     58     if img is None:
     59         print 'Failed to load image file:', img_fn
     60         sys.exit(1)
     61 
     62     filters = build_filters()
     63 
     64     with Timer('running single-threaded'):
     65         res1 = process(img, filters)
     66     with Timer('running multi-threaded'):
     67         res2 = process_threaded(img, filters)
     68 
     69     print 'res1 == res2: ', (res1 == res2).all()
     70     cv2.imshow('img', img)
     71     cv2.imshow('result', res2)
     72     cv2.waitKey()
     73     cv2.destroyAllWindows()
     74