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