# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import copy from collections import Counter class Result(object): def __init__(self): self.res_dict = { 'det': dict(), 'mot': dict(), 'attr': dict(), 'kpt': dict(), 'video_action': dict(), 'skeleton_action': dict(), 'reid': dict(), 'det_action': dict(), 'cls_action': dict(), 'vehicleplate': dict(), 'vehicle_attr': dict(), 'lanes': dict(), 'vehicle_press': dict(), 'vehicle_retrograde': dict() } def update(self, res, name): self.res_dict[name].update(res) def get(self, name): if name in self.res_dict and len(self.res_dict[name]) > 0: return self.res_dict[name] return None def clear(self, name): self.res_dict[name].clear() class DataCollector(object): """ DataCollector of Pipeline, collect results in every frames and assign it to each track ids. mainly used in mtmct. data struct: collector: - [id1]: (all results of N frames) - frames(list of int): Nx[int] - rects(list of rect): Nx[rect(conf, xmin, ymin, xmax, ymax)] - features(list of array(256,)): Nx[array(256,)] - qualities(list of float): Nx[float] - attrs(list of attr): refer to attrs for details - kpts(list of kpts): refer to kpts for details - skeleton_action(list of skeleton_action): refer to skeleton_action for details ... - [idN] """ def __init__(self): #id, frame, rect, score, label, attrs, kpts, skeleton_action self.mots = { "frames": [], "rects": [], "attrs": [], "kpts": [], "features": [], "qualities": [], "skeleton_action": [], "vehicleplate": [] } self.collector = {} def append(self, frameid, Result): mot_res = Result.get('mot') attr_res = Result.get('attr') kpt_res = Result.get('kpt') skeleton_action_res = Result.get('skeleton_action') reid_res = Result.get('reid') vehicleplate_res = Result.get('vehicleplate') rects = [] if reid_res is not None: rects = reid_res['rects'] elif mot_res is not None: rects = mot_res['boxes'] for idx, mot_item in enumerate(rects): ids = int(mot_item[0]) if ids not in self.collector: self.collector[ids] = copy.deepcopy(self.mots) self.collector[ids]["frames"].append(frameid) self.collector[ids]["rects"].append([mot_item[2:]]) if attr_res: self.collector[ids]["attrs"].append(attr_res['output'][idx]) if kpt_res: self.collector[ids]["kpts"].append( [kpt_res['keypoint'][0][idx], kpt_res['keypoint'][1][idx]]) if skeleton_action_res and (idx + 1) in skeleton_action_res: self.collector[ids]["skeleton_action"].append( skeleton_action_res[idx + 1]) else: # action model generate result per X frames, Not available every frames self.collector[ids]["skeleton_action"].append(None) if reid_res: self.collector[ids]["features"].append(reid_res['features'][ idx]) self.collector[ids]["qualities"].append(reid_res['qualities'][ idx]) if vehicleplate_res and vehicleplate_res['plate'][idx] != "": self.collector[ids]["vehicleplate"].append(vehicleplate_res[ 'plate'][idx]) def get_res(self): return self.collector def get_carlp(self, trackid): lps = self.collector[trackid]["vehicleplate"] counter = Counter(lps) carlp = counter.most_common() if len(carlp) > 0: return carlp[0][0] else: return None