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datacollector.py
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# 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()
}
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