def main(img):
saliency_methods = [ ('dictionary_ica_saliency', salienpy.dictionary_frequency.dictionary_saliency),
('frequency_tuned', salienpy.frequency_tuned.frequency_tuned_saliency),
('signature', salienpy.signature.signature_saliency),
]
for name, method in saliency_methods:
print name
t = time()
sal_img = method(img.copy())
t = t - time()
sal_img = minmaxnormalization(sal_img)
cv2.imshow('%s took %ss'%(name, t),255 - (255 * sal_img).astype('uint8'))
cv2.imwrite(name+'.png',255 - (255 * sal_img).astype('uint8'))
cv2.waitKey()
def plot_dif(dif):
vmax=max([abs(i) for i in (dif.min(), dif.max())])
dif[0][0] = 3.7
dif[1][0]= -3.7
fig = plt.figure()
ax = fig.add_subplot(111)
cax = ax.imshow(dif, cmap=cm.bwr)
cbar= fig.colorbar(cax)
plt.savefig(sys.argv[5])
if __name__ == '__main__':
if len(sys.argv) > 5:
img_a = cv2.imread(sys.argv[1])
img_b = cv2.imread(sys.argv[2])
sal_a, sal_b = main(img_a, img_b)
cv2.imwrite(sys.argv[3],(255 * minmaxnormalization(sal_a)).astype('uint8'))
cv2.imwrite(sys.argv[4],(255 * minmaxnormalization(sal_b)).astype('uint8'))
dif = sal_a - sal_b
dif_abs = numpy.abs(dif)
#cv2.imwrite('dif_sal_absolut.png',
#(255 * minmaxnormalization(dif_abs)).astype('uint8'))
plot_dif(dif)
else:
import pprint
pprint.pprint(sys.argv)
# compare_imgs.py
