''' gabor_threads.py ========= Sample demonstrates: - use of multiple Gabor filter convolutions to get Fractalius-like image effect (http://www.redfieldplugins.com/filterFractalius.htm) - use of python threading to accelerate the computation Usage ----- gabor_threads.py [image filename] ''' import numpy as np import cv2 from multiprocessing.pool import ThreadPool def build_filters(): filters = [] ksize = 31 for theta in np.arange(0, np.pi, np.pi / 16): kern = cv2.getGaborKernel((ksize, ksize), 4.0, theta, 10.0, 0.5, 0, ktype=cv2.CV_32F) kern /= 1.5*kern.sum() filters.append(kern) return filters def process(img, filters): accum = np.zeros_like(img) for kern in filters: fimg = cv2.filter2D(img, cv2.CV_8UC3, kern) np.maximum(accum, fimg, accum) return accum def process_threaded(img, filters, threadn = 8): accum = np.zeros_like(img) def f(kern): return cv2.filter2D(img, cv2.CV_8UC3, kern) pool = ThreadPool(processes=threadn) for fimg in pool.imap_unordered(f, filters): np.maximum(accum, fimg, accum) return accum if __name__ == '__main__': import sys from common import Timer print __doc__ try: img_fn = sys.argv[1] except: img_fn = '../cpp/baboon.jpg' img = cv2.imread(img_fn) filters = build_filters() with Timer('running single-threaded'): res1 = process(img, filters) with Timer('running multi-threaded'): res2 = process_threaded(img, filters) print 'res1 == res2: ', (res1 == res2).all() cv2.imshow('img', img) cv2.imshow('result', res2) cv2.waitKey() cv2.destroyAllWindows()