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""" run_youtube_vis.py | |
Run example: | |
run_youtube_vis.py --USE_PARALLEL False --METRICS HOTA --TRACKERS_TO_EVAL STEm_Seg | |
Command Line Arguments: Defaults, # Comments | |
Eval arguments: | |
'USE_PARALLEL': False, | |
'NUM_PARALLEL_CORES': 8, | |
'BREAK_ON_ERROR': True, # Raises exception and exits with error | |
'RETURN_ON_ERROR': False, # if not BREAK_ON_ERROR, then returns from function on error | |
'LOG_ON_ERROR': os.path.join(code_path, 'error_log.txt'), # if not None, save any errors into a log file. | |
'PRINT_RESULTS': True, | |
'PRINT_ONLY_COMBINED': False, | |
'PRINT_CONFIG': True, | |
'TIME_PROGRESS': True, | |
'DISPLAY_LESS_PROGRESS': True, | |
'OUTPUT_SUMMARY': True, | |
'OUTPUT_EMPTY_CLASSES': True, # If False, summary files are not output for classes with no detections | |
'OUTPUT_DETAILED': True, | |
'PLOT_CURVES': True, | |
Dataset arguments: | |
'GT_FOLDER': os.path.join(code_path, 'data/gt/youtube_vis/youtube_vis_training'), # Location of GT data | |
'TRACKERS_FOLDER': os.path.join(code_path, 'data/trackers/youtube_vis/youtube_vis_training'), | |
# 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 | |
'OUTPUT_SUB_FOLDER': '', # Output files are saved in OUTPUT_FOLDER/tracker_name/OUTPUT_SUB_FOLDER | |
'TRACKER_SUB_FOLDER': 'data', # Tracker files are in TRACKER_FOLDER/tracker_name/TRACKER_SUB_FOLDER | |
'TRACKER_DISPLAY_NAMES': None, # Names of trackers to display, if None: TRACKERS_TO_EVAL | |
Metric arguments: | |
'METRICS': ['TrackMAP', 'HOTA', 'CLEAR', 'Identity'] | |
""" | |
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_dataset_config = trackeval.datasets.YouTubeVIS.get_default_dataset_config() | |
default_metrics_config = {'METRICS': ['TrackMAP', 'HOTA', 'CLEAR', 'Identity']} | |
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.YouTubeVIS(dataset_config)] | |
metrics_list = [] | |
for metric in [trackeval.metrics.TrackMAP, trackeval.metrics.HOTA, trackeval.metrics.CLEAR, | |
trackeval.metrics.Identity]: | |
if metric.get_name() in metrics_config['METRICS']: | |
# specify TrackMAP config for YouTubeVIS | |
if metric == trackeval.metrics.TrackMAP: | |
default_track_map_config = metric.get_default_metric_config() | |
default_track_map_config['USE_TIME_RANGES'] = False | |
default_track_map_config['AREA_RANGES'] = [[0 ** 2, 128 ** 2], | |
[ 128 ** 2, 256 ** 2], | |
[256 ** 2, 1e5 ** 2]] | |
metrics_list.append(metric(default_track_map_config)) | |
else: | |
metrics_list.append(metric()) | |
if len(metrics_list) == 0: | |
raise Exception('No metrics selected for evaluation') | |
evaluator.evaluate(dataset_list, metrics_list) |