# FeatureTrackerConfigs: SHI_TOMASI_ORB, FAST_ORB, ORB, ORB2, ORB2_FREAK, ORB2_BEBLID, BRISK, AKAZE, FAST_FREAK, SIFT, ROOT_SIFT, SURF, SUPERPOINT, FAST_TFEAT, CONTEXTDESC
tracker_config = FeatureTrackerConfigs.TEST
tracker_config['num_features'] = num_features
tracker_config['tracker_type'] = tracker_type
print('tracker_config: ', tracker_config)
feature_tracker = feature_tracker_factory(**tracker_config)
# create SLAM object
slam = Slam(cam, feature_tracker, groundtruth)
time.sleep(1) # to show initial messages
viewer3D = Viewer3D()
if platform.system() == 'Linux':
display2d = Display2D(cam.width, cam.height) # pygame interface
else:
display2d = None # enable this if you want to use opencv window
matched_points_plt = Mplot2d(xlabel='img id',
ylabel='# matches',
title='# matches')
do_step = False
is_paused = False
img_id = 0 #180, 340, 400 # you can start from a desired frame id if needed
while dataset.isOk():
if not is_paused:
print('..................................')
detector_type=FeatureDetectorTypes.SHI_TOMASI,
descriptor_type=FeatureDescriptorTypes.ORB,
tracker_type=tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, num_levels = 4, detector_type = FeatureDetectorTypes.FAST, descriptor_type = FeatureDescriptorTypes.ORB, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, num_levels = 4, detector_type = FeatureDetectorTypes.BRISK, descriptor_type = FeatureDescriptorTypes.ORB, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, num_levels = 4, detector_type = FeatureDetectorTypes.BRISK, descriptor_type = FeatureDescriptorTypes.BRISK, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, num_levels = 4, detector_type = FeatureDetectorTypes.AKAZE, descriptor_type = FeatureDescriptorTypes.AKAZE, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, num_levels = 4, detector_type = FeatureDetectorTypes.ORB, descriptor_type = FeatureDescriptorTypes.ORB, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, detector_type = FeatureDetectorTypes.SIFT, descriptor_type = FeatureDescriptorTypes.SIFT, tracker_type = tracker_type)
#feature_tracker = feature_tracker_factory(min_num_features=num_features, detector_type = FeatureDetectorTypes.SURF, descriptor_type = FeatureDescriptorTypes.SURF, tracker_type = tracker_type)
# create SLAM object
slam = SLAM(cam, feature_tracker, grountruth)
viewer3D = Viewer3D()
display2d = Display2D(cam.width, cam.height)
is_draw_matched_points = True
matched_points_plt = Mplot2d(xlabel='img id',
ylabel='# matches',
title='# matches')
img_id = 0 #200 # you can start from a desired frame id if needed
while dataset.isOk():
print('..................................')
print('frame: ', img_id)
img = dataset.getImageColor(img_id)
if img is not None: