https://arxiv.org/abs/1909.12605 Towards Real-Time Multi-Object Tracking Modern multiple object tracking (MOT) systems usually follow the \emph{tracking-by-detection} paradigm. It has 1) a detection model for target localization and 2) an appearance embedding model for data association. Having the two models separately executed arxiv.org Introduction 현대의 MOT system은 주로 tracking-by-detection 방식을 ..
kradar 데이터에서 nuscenes data format 형식으로 json 파일 생성. sample.json 마지막 줄의 comma를 지워줘야 함. 1. sample.json #sample.json import os import json from collections import OrderedDict file_data = OrderedDict() with open('sample.json', 'a+', encoding="utf-8") as make_file: make_file.write('[') make_file.write('\n') for j in range(1, 59): seq = os.path.join('seq_' + str(j)) path_dir = os.path.join('./'+str(j))..
nuscenes data format으로 만들기 위해 kradar 기존 데이터 파일에 token정보를 추가하였음. import os for j in range(1, 59): seq = os.path.join('seq_' + str(j)) path_dir = os.path.join('./'+str(j)) file_list = os.listdir(path_dir) #create token list for prev, next tkn_list = [''] for i in file_list: tkn = os.path.join(seq + '_'+i[:-4]) tkn_list.append(tkn) tkn_list.append('') #read kradar format, append token information f..
# Initialize NuScenes object. # We do not store it in self to let garbage collection take care of it and save memory. nusc = NuScenes(version=nusc_version, verbose=verbose, dataroot=nusc_dataroot) nusc가 필요한 부분을 정리 1. load.gt() gt_boxes = load_gt(nusc, self.eval_set, TrackingBox, verbose=verbose) sample.json['token'] # Read out all sample_tokens in DB. sample_tokens_all = [s['token'] for s in nus..
