def run(self) -> None:
encoder = build_encoder(self.config)
while self.running:
if self.lock.acquire(timeout=1):
features = encoder(self.tracker.latest_detections,
self.tracker.frame)
for i, feature in enumerate(features):
self.tracker.latest_features[i][encoder.name] = feature
self.next_lock.release()
logging.getLogger('MOT').info('Encoder thread terminated.')
def __init__(self, detector: Config, matcher: Config,
encoders: List[Config], predictor: Config, **kwargs):
# Allow detector to be None
detector = build_detector(detector) if detector is not None else None
matcher = build_matcher(matcher)
encoders = [build_encoder(encoder_cfg) for encoder_cfg in encoders]
predictor = build_predictor(predictor)
if 'detection_filters' in kwargs.keys():
kwargs['detection_filters'] = [
build_detection_filter(filter_cfg)
for filter_cfg in kwargs['detection_filters']
]
super().__init__(detector, encoders, matcher, predictor, **kwargs)
def __init__(self, detector: Config, encoders: List[Config], matcher: Config, predictor: Config,
central_address: str, **kwargs):
self.detector = build_detector(detector)
self.encoders = [build_encoder(encoder) for encoder in encoders]
self.detection_filters = []
self.identifier = random.randint(0, 1000000)
self.zmq_context = zmq.Context()
self.subscribe_socket = self.zmq_context.socket(zmq.SUB)
self.subscribe_socket.connect('tcp://' + central_address)
self.subscribe_socket.setsockopt_string(zmq.SUBSCRIBE, np.unicode(''))
super(SingleThreadTracker, self).__init__(self.detector, self.encoders, matcher, predictor, **kwargs)
def __init__(self, detector: Config, matcher: Config, encoders: List[Config], predictor: Config,
sigma_active: float = 0.5, lambda_active: float = 0.6,
lambda_new: float = 0.3, secondary_matcher: Config = None, **kwargs):
detector = build_detector(detector)
matcher = build_matcher(matcher)
encoders = [build_encoder(encoder_cfg) for encoder_cfg in encoders]
predictor = build_predictor(predictor)
self.sigma_active = sigma_active
self.lambda_active = lambda_active
self.lambda_new = lambda_new
self.tracklets_inactive = []
if secondary_matcher is not None:
self.secondary_matcher = build_matcher(secondary_matcher)
super().__init__(detector, encoders, matcher, predictor, **kwargs)
from mot.structures import Detection
sys.path.append(
'/home/linkinpark213/Source/online-mot-by-detection/mot/encode/OpenReID/')
from reid.evaluators import pairwise_distance, evaluate_all
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('dataset_path', type=str, help='Path to dataset')
args = parser.parse_args()
encoder_cfg = cfg_from_file(
'/home/linkinpark213/Source/online-mot-by-detection/configs/encode/openreid_r50.py'
)
print('Building encoder...')
encoder = build_encoder(encoder_cfg)
subset_features = {}
for subset in ['query', 'gallery']:
ids = sorted(os.listdir(os.path.join(args.dataset_path, subset)))
all_infos = []
all_features = []
for target_id in ids:
image_filenames = os.listdir(
os.path.join(args.dataset_path, subset, target_id))
for image_filename in image_filenames:
print('Encoding {}'.format(
os.path.join(args.dataset_path, subset, target_id,
for camID in range(1, 9):
cam_feature_dir = os.path.join(args.feature_path,
'camera{:d}'.format(camID))
if not os.path.isdir(cam_feature_dir):
os.makedirs(cam_feature_dir)
# From DukeMTMCC format (cam, ID, frameID, left, top, width, height, conf, x, y, z)
# To MOTChallenge format (frameID, ID, left, top, width, height, conf, x, y, z)
camData = tracks[np.where(tracks[:, 0] == camID)][:, 1:]
camData[:, (0, 1)] = camData[:, (1, 0)]
ids = np.unique(camData[:, 1]).astype(np.int)
print('All target IDs in cam{}: '.format(camID), ids)
encoder = build_encoder(cfg_from_file(args.encoder_config))
global target_id
for target_id in ids:
feature_filepath = os.path.join(cam_feature_dir,
'{:06d}'.format(int(target_id)))
detections = sample_detections(camData, target_id,
args.sample_rate)
if len(detections) > 0:
features = []
for i, detection in enumerate(detections):
frame_id, _, l, t, w, h, score, _, _, _ = detection
img = cv2.imread(
os.path.join(
args.duke_path,
'images/camera{}/{:06d}.jpg'.format(
def test_get_component():
detector = build_detector(dict(type='MMDetector'))
encoder = build_encoder(dict(type='DGNetEncoder'))
metric = build_metric(dict(type='IoUMetric'))
matcher = build_matcher(dict(type='HungarianMatcher'))
tracker = build_tracker(dict(type='Tracktor'))