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""" run_burst_ow.py
The example commands given below expect the following folder structure:
- data
- gt
- burst
- {val,test}
- all_classes
- all_classes.json (filename is irrelevant)
- common_classes
- common_classes.json (filename is irrelevant)
- uncommon_classes.json
- uncommon_classes.json (filename is irrelevant)
- trackers
- burst
- open-world
- {val,test}
- my_tracking_method
- data
- results.json (filename is irrelevant)
Run example:
You'll need to run the eval script separately to get the OWTA metric for the three class splits. In the command below,
replace <SPLIT_NAME> with "common", "uncommon" and "all" to get the corresponding results.
run_burst_ow.py --USE_PARALLEL True --GT_FOLDER data/gt/burst/{val,test}/<SPLIT_NAME>_classes --TRACKERS_FOLDER data/trackers/burst/open-world/{val,test}
Command Line Arguments: Defaults, # Comments
Eval arguments:
'USE_PARALLEL': False,
'NUM_PARALLEL_CORES': 8,
'BREAK_ON_ERROR': True,
'PRINT_RESULTS': True,
'PRINT_ONLY_COMBINED': False,
'PRINT_CONFIG': True,
'TIME_PROGRESS': True,
'OUTPUT_SUMMARY': True,
'OUTPUT_DETAILED': True,
'PLOT_CURVES': True,
Dataset arguments:
'GT_FOLDER': os.path.join(code_path, '../data/gt/burst/{val,test}/<SPLIT_NAME>_classes'), # Location of GT data
'TRACKERS_FOLDER': os.path.join(code_path, '../data/trackers/burst/open-world/{val,test}), # Trackers location
'OUTPUT_FOLDER': None, # Where to save eval results (if None, same as TRACKERS_FOLDER)
'TRACKERS_TO_EVAL': None, # Filenames of trackers to eval (if None, all in folder)
'CLASSES_TO_EVAL': None, # Classes to eval (if None, all classes)
'SPLIT_TO_EVAL': 'training', # Valid: 'training', 'val'
'PRINT_CONFIG': True, # Whether to print current config
'TRACKER_SUB_FOLDER': 'data', # Tracker files are in TRACKER_FOLDER/tracker_name/TRACKER_SUB_FOLDER
'OUTPUT_SUB_FOLDER': '', # Output files are saved in OUTPUT_FOLDER/tracker_name/OUTPUT_SUB_FOLDER
'TRACKER_DISPLAY_NAMES': None, # Names of trackers to display, if None: TRACKERS_TO_EVAL
'MAX_DETECTIONS': 300, # Number of maximal allowed detections per image (0 for unlimited)
'SUBSET': 'unknown', # Evaluate on the following subsets ['all', 'known', 'unknown', 'distractor']
Metric arguments:
'METRICS': ['HOTA', 'CLEAR', 'Identity', 'TrackMAP']
"""
import sys
import os
import argparse
from multiprocessing import freeze_support
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import trackeval # noqa: E402
if __name__ == '__main__':
freeze_support()
# Command line interface:
default_eval_config = trackeval.Evaluator.get_default_eval_config()
# print only combined since TrackMAP is undefined for per sequence breakdowns
default_eval_config['PRINT_ONLY_COMBINED'] = True
default_eval_config['DISPLAY_LESS_PROGRESS'] = True
default_dataset_config = trackeval.datasets.BURST_OW.get_default_dataset_config()
# default_metrics_config = {'METRICS': ['HOTA', 'CLEAR', 'Identity', 'TrackMAP']}
default_metrics_config = {'METRICS': ['HOTA']}
config = {**default_eval_config, **default_dataset_config, **default_metrics_config} # Merge default configs
parser = argparse.ArgumentParser()
for setting in config.keys():
if type(config[setting]) == list or type(config[setting]) == type(None):
parser.add_argument("--" + setting, nargs='+')
else:
parser.add_argument("--" + setting)
args = parser.parse_args().__dict__
for setting in args.keys():
if args[setting] is not None:
if type(config[setting]) == type(True):
if args[setting] == 'True':
x = True
elif args[setting] == 'False':
x = False
else:
raise Exception('Command line parameter ' + setting + 'must be True or False')
elif type(config[setting]) == type(1):
x = int(args[setting])
elif type(args[setting]) == type(None):
x = None
else:
x = args[setting]
config[setting] = x
eval_config = {k: v for k, v in config.items() if k in default_eval_config.keys()}
dataset_config = {k: v for k, v in config.items() if k in default_dataset_config.keys()}
metrics_config = {k: v for k, v in config.items() if k in default_metrics_config.keys()}
# Run code
evaluator = trackeval.Evaluator(eval_config)
dataset_list = [trackeval.datasets.BURST_OW(dataset_config)]
metrics_list = []
# for metric in [trackeval.metrics.TrackMAP, trackeval.metrics.CLEAR, trackeval.metrics.Identity,
# trackeval.metrics.HOTA]:
for metric in [trackeval.metrics.HOTA]:
if metric.get_name() in metrics_config['METRICS']:
metrics_list.append(metric())
if len(metrics_list) == 0:
raise Exception('No metrics selected for evaluation')
output_res, output_msg = evaluator.evaluate(dataset_list, metrics_list, show_progressbar=True)
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