def run_whole_image(self, img, minu_thr=0.2):
# feed_dict = {self.images_placeholder: img}
# minutiae_cylinder = self.sess.run(self.minutiae_cylinder_placeholder, feed_dict=feed_dict)
img = img / 128.0 - 1
img = np.expand_dims(img, axis=2)
img = np.expand_dims(img, axis=0)
feed_dict = {self.images_placeholder: img}
minutiae_cylinder = self.sess.run(self.minutiae_cylinder_placeholder, feed_dict=feed_dict)
minutiae_cylinder = np.squeeze(minutiae_cylinder, axis=0)
#start = timeit.default_timer()
minutiae = prepare_data.get_minutiae_from_cylinder2(minutiae_cylinder, thr=0.25)
# stop = timeit.default_timer()
# minu_time = stop - start
# print minu_time
# cv2.imwrite('test_0.jpeg', (minutiae_cylinder[:, :, 0:3]) * 255)
# cv2.imwrite('test_1.jpeg', (minutiae_cylinder[:, :, 3:6]) * 255)
# cv2.imwrite('test_2.jpeg', (minutiae_cylinder[:, :, 6:9]) * 255)
# cv2.imwrite('test_3.jpeg', (minutiae_cylinder[:, :, 9:12]) * 255)
# prepare_data.show_features(img, minutiae, fname=os.path.basename(file)[:-4] +'.jpeg')
minutiae = prepare_data.refine_minutiae(minutiae, dist_thr=10, ori_dist=np.pi / 4)
minutiae = self.remove_crowded_minutiae(minutiae)
return minutiae
def run_whole_image(self, img, minu_thr=0.2):
img = img / 128.0 - 1
img = np.expand_dims(img, axis=2)
img = np.expand_dims(img, axis=0)
feed_dict = {self.images_placeholder: img}
minutiae_cylinder = self.sess.run(self.minutiae_cylinder_placeholder, feed_dict=feed_dict)
minutiae_cylinder = np.squeeze(minutiae_cylinder, axis=0)
minutiae = prepare_data.get_minutiae_from_cylinder2(minutiae_cylinder, thr=minu_thr)
minutiae = prepare_data.refine_minutiae(minutiae, dist_thr=20, ori_dist=np.pi / 4)
minutiae = self.remove_crowded_minutiae(minutiae)
return minutiae