This simple tracker, simply assigns track IDs which maximise the 'bounding box IoU' between previous tracks and current
detections. It is also able to match detections to tracks at more than one timestep previously.
"""
import os
import sys
import numpy as np
from multiprocessing.pool import Pool
from multiprocessing import freeze_support
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..')))
from trackeval.baselines import baseline_utils as butils
from trackeval.utils import get_code_path
code_path = get_code_path()
config = {
'INPUT_FOL': os.path.join(code_path, 'data/detections/rob_mots/{split}/non_overlap_supplied/data/'),
'OUTPUT_FOL': os.path.join(code_path, 'data/trackers/rob_mots/{split}/STP/data/'),
'SPLIT': 'train', # valid: 'train', 'val', 'test'.
'Benchmarks': None, # If None, all benchmarks in SPLIT.
'Num_Parallel_Cores': None, # If None, run without parallel.
'DETECTION_THRESHOLD': 0.5,
'ASSOCIATION_THRESHOLD': 1e-10,
'MAX_FRAMES_SKIP': 7
}
def track_sequence(seq_file):
# python3 scripts/run_rob_mots.py --ROBMOTS_SPLIT train --TRACKERS_TO_EVAL STP --USE_PARALLEL True --NUM_PARALLEL_CORES 8
import sys
import os
import csv
import numpy as np
from multiprocessing import freeze_support
sys.path.insert(0,
os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import trackeval # noqa: E402
from trackeval import utils
code_path = utils.get_code_path()
if __name__ == '__main__':
freeze_support()
script_config = {
'ROBMOTS_SPLIT':
'train', # 'train', # valid: 'train', 'val', 'test', 'test_live', 'test_post', 'test_all'
'BENCHMARKS':
['kitti_mots', 'davis_unsupervised', 'youtube_vis', 'ovis',
'tao'], # 'bdd_mots' coming soon
'GT_FOLDER':
os.path.join(code_path, 'data/gt/rob_mots'),
'TRACKERS_FOLDER':
os.path.join(code_path, 'data/trackers/rob_mots'),
}
default_eval_config = trackeval.Evaluator.get_default_eval_config()
default_eval_config['PRINT_ONLY_COMBINED'] = True