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modify at output data format

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王庆刚
2024-12-10 19:01:54 +08:00
parent 1e6c5deee4
commit afd033b965
15 changed files with 545 additions and 290 deletions
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tracking/dotrack/__pycache__/dotracks.cpython-39.pyc
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tracking/dotrack/__pycache__/dotracks_back.cpython-39.pyc
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tracking/dotrack/__pycache__/dotracks_front.cpython-39.pyc
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tracking/dotrack/dotracks.py
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@ -394,21 +394,24 @@ class Track:
class doTracks:
def __init__(self, bboxes, TracksDict):
'''fundamental property'''
def __init__(self, bboxes, trackefeats):
'''fundamental property
trackefeats: dict, key 格式 "fid_bid"
'''
self.bboxes = bboxes
# self.TracksDict = TracksDict
self.frameID = np.unique(bboxes[:, 7].astype(int))
self.trackID = np.unique(bboxes[:, 4].astype(int))
self.lboxes = self.array2list()
self.lfeats = self.getfeats(TracksDict)
self.lfeats = self.getfeats(trackefeats)
'''对 self.tracks 中的元素进行分类，将 track 归入相应列表中'''
self.Hands = []
self.Kids = []
self.Static = []
self.Residual = []
self.Residual = []
self.Confirmed = []
self.DownWard = [] # subset of self.Residual
self.UpWard = [] # subset of self.Residual
self.FreeMove = [] # subset of self.Residual
@ -435,15 +438,22 @@ class doTracks:
return lboxes
def getfeats(self, TracksDict):
def getfeats(self, trackefeats):
lboxes = self.lboxes
lfeats = []
for boxes in lboxes:
afeat = readDict(boxes, TracksDict)
lfeats.append(afeat)
feats = []
for i in range(boxes.shape[0]):
fid, bid = int(boxes[i, 7]), int(boxes[i, 8])
key = f"{int(fid)}_{int(bid)}"
if key in trackefeats:
feats.append(trackefeats[key])
feats = np.asarray(feats, dtype=np.float32)
lfeats.append(feats)
return lfeats
def similarity(self):
nt = len(self.tracks)

23
tracking/dotrack/dotracks_back.py
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@ -6,6 +6,7 @@ Created on Mon Mar 4 18:36:31 2024
"""
import numpy as np
import cv2
import copy
from tracking.utils.mergetrack import track_equal_track
from scipy.spatial.distance import cdist
from pathlib import Path
@ -19,9 +20,9 @@ from .track_back import backTrack
class doBackTracks(doTracks):
def __init__(self, bboxes, TracksDict):
def __init__(self, bboxes, trackefeats):
super().__init__(bboxes, TracksDict)
super().__init__(bboxes, trackefeats)
self.tracks = [backTrack(b, f) for b, f in zip(self.lboxes, self.lfeats)]
@ -113,6 +114,22 @@ class doBackTracks(doTracks):
# self.merge_based_hands(htrack)
self.Residual = tracks
self.Confirmed = self.confirm_track()
def confirm_track(self):
Confirmed = None
mindist = 0
for track in self.Residual:
md = min(track.trajrects_wh)
if md > mindist:
mindist = copy.deepcopy(md)
Confirmed = copy.deepcopy(track)
if Confirmed is not None:
return [Confirmed]
return []
# def merge_based_hands(self, htrack):
# gtracks = htrack.Goods
@ -122,6 +139,8 @@ class doBackTracks(doTracks):
# btrack, bfious = gtracks[1]
def associate_with_hand(self, htrack, gtrack):
'''
迁移至基类：

24
tracking/dotrack/dotracks_front.py
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@ -5,6 +5,7 @@ Created on Mon Mar 4 18:38:20 2024
@author: ym
"""
import cv2
import copy
import numpy as np
from pathlib import Path
@ -16,8 +17,8 @@ from .dotracks import doTracks
from .track_front import frontTrack
class doFrontTracks(doTracks):
def __init__(self, bboxes, TracksDict):
super().__init__(bboxes, TracksDict)
def __init__(self, bboxes, frameDictList):
super().__init__(bboxes, frameDictList)
# self.tracks = [frontTrack(b) for b in self.lboxes]
self.tracks = [frontTrack(b, f) for b, f in zip(self.lboxes, self.lfeats)]
@ -84,11 +85,24 @@ class doFrontTracks(doTracks):
tracks = self.sub_tracks(tracks, static_tracks)
freemoved_tracks = [t for t in tracks if t.is_free_move()]
tracks = self.sub_tracks(tracks, freemoved_tracks)
self.Residual = tracks
self.Confirmed = self.confirm_track()
def confirm_track(self):
Confirmed = None
mindist = 0
for track in self.Residual:
md = min(track.trajrects_wh)
if md > mindist:
mindist = copy.deepcopy(md)
Confirmed = copy.deepcopy(track)
if Confirmed is not None:
return [Confirmed]
return []
def associate_with_hand(self, htrack, gtrack):
'''

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tracking/utils/__pycache__/read_data.cpython-39.pyc
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tracking/utils/read_data.py
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@ -34,10 +34,12 @@ def find_samebox_in_array(arr, target):
return -1
def extract_data(datapath):
'''
0/1_track.data 数据读取
对于特征，需要构造两个对象：
(1) tracking输出 boxes，依据 (fid, bid) 找到对应的 feats, tracker_feat_dict 实现较为方便
(2) frameDictList 中元素为 frameDict，输出同一接口
'''
bboxes, ffeats = [], []
@ -45,9 +47,7 @@ def extract_data(datapath):
trackerfeats = np.empty((0, 256), dtype=np.float64)
boxes, feats, tboxes, tfeats = [], [], [], []
timestamps, frameIds = [], []
with open(datapath, 'r', encoding='utf-8') as lines:
for line in lines:
line = line.strip() # 去除行尾的换行符和可能的空白字符
@ -102,16 +102,17 @@ def extract_data(datapath):
assert(len(bboxes)==len(ffeats)), "Error at Yolo output!"
assert(len(trackerboxes)==len(trackerfeats)), "Error at tracker output!"
tracker_feat_dict = {}
tracker_feat_dict["timestamps"] = timestamps
tracker_feat_dict["frameIds"] = frameIds
for i in range(len(trackerboxes)):
tid, fid, bid = int(trackerboxes[i, 4]), int(trackerboxes[i, 7]), int(trackerboxes[i, 8])
if f"frame_{fid}" not in tracker_feat_dict:
tracker_feat_dict[f"frame_{fid}"]= {"feats": {}}
tracker_feat_dict[f"frame_{fid}"]["feats"].update({bid: trackerfeats[i, :]})
## 生成帧为单位的特征列表
tracker_feats = {}
frmIDs = np.sort(np.unique(trackerboxes[:, 7].astype(int)))
for fid in frmIDs:
idx = np.where(trackerboxes[:, 7] == fid)[0]
boxes = trackerboxes[idx, :]
feats = trackerfeats[idx, :]
for i in range(len(boxes)):
f, b = int(boxes[i, 7]), int(boxes[i, 8])
tracker_feats.update({f"{f}_{b}": feats[i, :]})
boxes, trackingboxes= [], []
tracking_flag = False
@ -137,18 +138,41 @@ def extract_data(datapath):
if len(boxes):
trackingboxes.append(np.array(boxes))
tracking_feat_dict = {}
# tracking_feat_dict = {}
# try:
# for i, boxes in enumerate(trackingboxes):
# for box in boxes:
# tid, fid, bid = int(box[4]), int(box[7]), int(box[8])
# if f"track_{tid}" not in tracking_feat_dict:
# tracking_feat_dict[f"track_{tid}"]= {"feats": {}}
# tracking_feat_dict[f"track_{tid}"]["feats"].update({f"{fid}_{bid}": tracker_feat_dict[f"frame_{fid}"]["feats"][bid]})
# except Exception as e:
# print(f'Path: {datapath}, tracking_feat_dict can not be structured correcttly, Error: {e}')
# tracker_feat_dict = {}
# tracker_feat_dict["timestamps"] = timestamps
# tracker_feat_dict["frameIds"] = frameIds
# for i in range(len(trackerboxes)):
# fid, bid = int(trackerboxes[i, 7]), int(trackerboxes[i, 8])
# if f"frame_{fid}" not in tracker_feat_dict:
# tracker_feat_dict[f"frame_{fid}"]= {"feats": {}}
# tracker_feat_dict[f"frame_{fid}"]["feats"].update({bid: trackerfeats[i, :]})
trackingfeats = []
try:
for i, boxes in enumerate(trackingboxes):
feats = []
for box in boxes:
tid, fid, bid = int(box[4]), int(box[7]), int(box[8])
if f"track_{tid}" not in tracking_feat_dict:
tracking_feat_dict[f"track_{tid}"]= {"feats": {}}
tracking_feat_dict[f"track_{tid}"]["feats"].update({f"{fid}_{bid}": tracker_feat_dict[f"frame_{fid}"]["feats"][bid]})
fid, bid = int(box[7]), int(box[8])
feat = tracker_feats[f"{fid}_{bid}"]
feats.append(feat)
trackingfeats.append(np.array(feats))
except Exception as e:
print(f'Path: {datapath}, tracking_feat_dict can not be structured correcttly, Error: {e}')
print(f'Path: {datapath}, trackingfeats can not be structured correcttly, Error: {e}')
return bboxes, ffeats, trackerboxes, tracker_feat_dict, trackingboxes, tracking_feat_dict
# return bboxes, ffeats, trackerboxes, tracker_feat_dict, trackingboxes, trackingfeats
return bboxes, ffeats, trackerboxes, tracker_feats, trackingboxes, trackingfeats
def read_tracking_output(filepath):
'''
@ -236,8 +260,6 @@ def read_returnGoods_file(filePath):
lines = f.readlines()
clean_lines = [line.strip().replace("'", '').replace('"', '') for line in lines]
all_list = []
split_flag, dict = False, {}
barcode_list, similarity_list = [], []
@ -318,14 +340,15 @@ def read_seneor(filepath):
def read_similar(filePath):
SimiDict = {}
SimiDict['one2one'] = []
SimiDict['one2SN'] = []
SimiDict['one2n'] = []
with open(filePath, 'r', encoding='utf-8') as f:
lines = f.readlines()
clean_lines = [line.strip().replace("'", '').replace('"', '') for line in lines]
one2one_list, one2n_list = [], []
one2one_list, one2SN_list, one2n_list = [], [], []
Flag_1to1, Flag_1ton = False, False
Flag_1to1, Flag_1toSN, Flag_1ton = False, False, False
for i, line in enumerate(clean_lines):
line = line.strip()
if line.endswith(','):
@ -334,18 +357,26 @@ def read_similar(filePath):
if not line:
if len(one2one_list): SimiDict['one2one'] = one2one_list
if len(one2SN_list): SimiDict['one2SN'] = one2SN_list
if len(one2n_list): SimiDict['one2n'] = one2n_list
one2one_list, one2n_list = [], []
Flag_1to1, Flag_1ton = False, False
one2one_list, one2SN_list, one2n_list = [], [], []
Flag_1to1, Flag_1toSN, Flag_1ton = False, False, False
continue
if line.find('oneToOne')>=0:
Flag_1to1, Flag_1ton = True, False
Flag_1to1, Flag_1toSN, Flag_1ton = True, False,False
continue
if line.find('oneToSN')>=0:
Flag_1to1, Flag_1toSN, Flag_1ton = False, True, False
continue
if line.find('oneTon')>=0:
Flag_1to1, Flag_1ton = False, True
Flag_1to1, Flag_1toSN, Flag_1ton = False, False, True
continue
if Flag_1to1:
barcode = line.split(',')[0].strip()
value = line.split(',')[1].split(':')[1].strip()
@ -353,6 +384,14 @@ def read_similar(filePath):
Dict['similar'] = float(value)
one2one_list.append(Dict)
continue
if Flag_1toSN:
barcode = line.split(',')[0].strip()
value = line.split(',')[1].split(':')[1].strip()
Dict['barcode'] = barcode
Dict['similar'] = float(value)
one2SN_list.append(Dict)
continue
if Flag_1ton:
label = line.split(':')[0].strip()