|
|
| """ run_mot_challenge.py |
| |
| Run example: |
| run_mot_challenge.py --USE_PARALLEL False --METRICS Hota --TRACKERS_TO_EVAL Lif_T |
| |
| 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/mot_challenge/'), # Location of GT data |
| 'TRACKERS_FOLDER': os.path.join(code_path, 'data/trackers/mot_challenge/'), # 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': ['pedestrian'], # Valid: ['pedestrian'] |
| 'BENCHMARK': 'MOT17', # Valid: 'MOT17', 'MOT16', 'MOT20', 'MOT15' |
| 'SPLIT_TO_EVAL': 'train', # Valid: 'train', 'test', 'all' |
| 'INPUT_AS_ZIP': False, # Whether tracker input files are zipped |
| 'PRINT_CONFIG': True, # Whether to print current config |
| 'DO_PREPROC': True, # Whether to perform preprocessing (never done for 2D_MOT_2015) |
| '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 |
| Metric arguments: |
| 'METRICS': ['HOTA', 'CLEAR', 'Identity', 'IDEucl'] |
| """ |
|
|
| 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 |
|
|
| if __name__ == '__main__': |
| freeze_support() |
|
|
| |
| default_eval_config = trackeval.Evaluator.get_default_eval_config() |
| default_eval_config['DISPLAY_LESS_PROGRESS'] = False |
| default_dataset_config = trackeval.datasets.HeadTrackingChallenge.get_default_dataset_config() |
| default_metrics_config = {'METRICS': ['HOTA', 'CLEAR', 'Identity', 'IDEucl'], 'THRESHOLD': 0.4} |
| config = {**default_eval_config, **default_dataset_config, **default_metrics_config} |
| 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 |
| elif setting == 'SEQ_INFO': |
| x = dict(zip(args[setting], [None]*len(args[setting]))) |
| 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()} |
|
|
| |
| evaluator = trackeval.Evaluator(eval_config) |
| dataset_list = [trackeval.datasets.HeadTrackingChallenge(dataset_config)] |
| metrics_list = [] |
| for metric in [trackeval.metrics.HOTA, trackeval.metrics.CLEAR, trackeval.metrics.Identity, trackeval.metrics.IDEucl]: |
| if metric.get_name() in metrics_config['METRICS']: |
| metrics_list.append(metric(metrics_config)) |
| if len(metrics_list) == 0: |
| raise Exception('No metrics selected for evaluation') |
| evaluator.evaluate(dataset_list, metrics_list) |
|
|
