run_multi_cam_clustering.py

from utilities.python_path_utility import append_to_pythonpath

append_to_pythonpath(['feature_extractors/reid_strong_baseline'
                      ,'feature_extractors/ABD_Net'
                        ,'detectors/mmdetection'
                       ,'evaluation/py_motmetrics'], __file__)

import os
os.environ["OMP_NUM_THREADS"] = "3" # export OMP_NUM_THREADS=4
os.environ["OPENBLAS_NUM_THREADS"] = "3" # export OPENBLAS_NUM_THREADS=4
os.environ["MKL_NUM_THREADS"] = "3" # export MKL_NUM_THREADS=6
os.environ["VECLIB_MAXIMUM_THREADS"] = "3" # export VECLIB_MAXIMUM_THREADS=4
os.environ["NUMEXPR_NUM_THREADS"] = "3" # export NUMEXPR_NUM_THREADS=6

import argparse
import mmcv
from feature_extractors.reid_strong_baseline.utils.logger import setup_logger
import json

from clustering.multi_cam_clustering import splitted_clustering_from_weights, find_clustering_weights


class Run_multi_cam_clustering:
    def __init__(self,args):

        self.cfg = mmcv.Config.fromfile(args.config).root

        self.cfg.config_basename = os.path.basename(args.config).replace(".py","")

        self.cfg.repository_root = os.path.abspath(os.path.dirname(__file__))


        self.cfg.config_run_path = os.path.join(self.cfg.repository_root
                                                , "work_dirs"
                                                , "clustering"
                                                , "config_runs"
                                                , self.cfg.config_basename)


        os.makedirs(self.cfg.config_run_path,exist_ok=True)

        logger = setup_logger("clustering_logger", self.cfg.config_run_path, 0)

        logger.info(json.dumps(self.cfg, sort_keys=True, indent=4))





    def run(self):


        if self.cfg.find_weights.run:
            find_clustering_weights(test_track_results_folder=self.cfg.test_track_results_folder
                                             , train_track_results_folder=self.cfg.train_track_results_folder
                                             , work_dirs=self.cfg.work_dirs
                                             , test_dataset_folder=self.cfg.test_dataset_folder
                                             , train_dataset_folder=self.cfg.train_dataset_folder
                                             , mc_cfg=self.cfg
                                             , cam_count=self.cfg.cam_count
                                             , take_frames_per_cam=self.cfg.find_weights.take_frames_per_cam
                                             , weight_search_configs=self.cfg.find_weights.weight_search_configs
                                             , dist_name_to_distance_weights=self.cfg.find_weights.dist_name_to_distance_weights
                                             , config_basename=self.cfg.config_basename
                                             , person_identifier=self.cfg.person_identifier
                                             )


        if self.cfg.cluster_from_weights.run:


            splitted_clustering_from_weights(test_track_results_folder=self.cfg.test_track_results_folder
                                             , train_track_results_folder=self.cfg.train_track_results_folder
                                             , work_dirs=self.cfg.work_dirs
                                             , test_dataset_folder=self.cfg.test_dataset_folder
                                             , train_dataset_folder=self.cfg.train_dataset_folder
                                             , mc_cfg=self.cfg
                                             , cam_count=self.cfg.cam_count
                                             , best_weights_path=self.cfg.cluster_from_weights.best_weights_path
                                             , default_weights=self.cfg.cluster_from_weights.default_weights
                                             , config_basename=self.cfg.config_basename
                                             , person_identifier="person_id"
                                             , n_split_parts=self.cfg.cluster_from_weights.split_count
                                             )






def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--config", type=str)

    return parser.parse_args()



if __name__=="__main__":


    args = parse_args()

    run_clustering = Run_multi_cam_clustering(args)


    run_clustering.run()