k = cv2.waitKey(33) & 0xFF if k == 27: # Esc key to stop break elif k == -1: # normally -1 returned,so don't print it continue elif k == ord('c'): ezsift_matcher.add_reference_image(str(angles_to_capture[current]), grey_scale_image) print "Reference Added", angles_to_capture[current] current += 1 if current >= len(angles_to_capture): cap = False time.sleep(0.1) for row in ezsift_matcher.get_reference_image_confusion_matrix(): print row while True: gray = vidgrab.grab_frame_return_grey() grey_scale_image = cv2.cvtColor(gray, cv2.COLOR_BGR2GRAY) grey_scale_image = np.array(grey_scale_image) matching_result = ezsift_matcher.match(grey_scale_image) angle = [] angle_average = 0 lensall = 0 for logo_key in angles_to_capture: coords_1 = matching_result.get_match_coord_lst(str(logo_key))
color_cycle = itertools.cycle([[255, 0, 0], [0, 255, 0], [0, 255, 0]]) ezsift_matcher = EZSiftImageMatcher() num_images = 100 for i in range(0, num_images, 1): path = "./img/image-{}.png".format(i) print path img1 = cv2.imread(path) g1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) ezsift_matcher.add_reference_image(str(i), g1) conf_matrix = ezsift_matcher.get_reference_image_confusion_matrix() np_conf_mat = np.array(conf_matrix) for i in range(num_images): for j in range(num_images): if i != j and i > j: np_conf_mat[i][j] = np_conf_mat[j][i] plt.figure(0) c = plt.imshow(np_conf_mat, interpolation="none") plt.colorbar(c) np_conf_mat_inv = np.zeros(np_conf_mat.shape)