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王庆刚
2024-11-25 18:05:08 +08:00
parent c47894ddc0
commit 8bbee310ba
109 changed files with 1003 additions and 305 deletions
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event_time_specify.py
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@ -11,13 +11,10 @@ import numpy as np
import matplotlib.pyplot as plt
from move_detect import MoveDetect
import sys
sys.path.append(r"D:\DetectTracking")
# from tracking.utils.read_data import extract_data, read_deletedBarcode_file, read_tracking_output, read_weight_timeConsuming
from tracking.utils.read_data import read_weight_timeConsuming
def str_to_float_arr(s):
@ -118,7 +115,14 @@ def extract_data_1(datapath):
def devide_motion_state(tboxes, width):
'''frameTstamp: 用于标记当前相机视野内用购物车运动状态变化'''
'''frameTstamp: 用于标记当前相机视野内用购物车运动状态变化
Hand状态：
0: 不存在
1: 手部存在
2: 手部存在且处于某种状态（静止）
'''
periods = []
if len(tboxes) < width:
@ -131,28 +135,22 @@ def devide_motion_state(tboxes, width):
state = np.zeros((fnum, 2), dtype=np.int64)
frameState = np.concatenate((frameTstamp, state), axis = 1).astype(np.int64)
handState = np.concatenate((frameTstamp, state), axis = 1).astype(np.int64)
mtrackFid = {}
handFid = {}
'''frameState 标记由图像判断的购物车状态：0: 静止，1: 运动'''
for idx in range(width, fnum+1):
lboxes = np.concatenate(fboxes[idx-width:idx], axis = 0)
idx0 = idx-width
lboxes = np.concatenate(fboxes[idx0:idx], axis = 0)
md = MoveDetect(lboxes)
md.classify()
# if idx==60:
# print('a')
## track.during 二元素组, 表征在该时间片段内，轨迹 track 的起止时间，数值用 boxes[:, 7]
for track in md.track_motion:
if track.cls == 0: continue
f1, f2 = track.during
# if track.cls == 0: continue
idx1 = set(np.where(frameState[:,0] >= f1)[0])
idx2 = set(np.where(frameState[:,0] <= f2)[0])
idx3 = list(idx1.intersection(idx2))
@ -164,7 +162,25 @@ def devide_motion_state(tboxes, width):
frameState[idx-1, 3] = 1
frameState[idx3, 2] = 1
for track in md.hand_tracks:
f11, f22 = track.during
idx11 = set(np.where(handState[:,0] >= f11)[0])
idx22 = set(np.where(handState[:,0] <= f22)[0])
idx33 = list(idx11.intersection(idx22))
'''手部存在标记'''
handState[idx33, 2] = 1
'''未来改进方向：is_static 可以用手部状态判断的函数代替'''
if track.is_static(70) and len(idx33)>1:
idx11 = set(np.where(handState[:,0] >= f11)[0])
idx22 = set(np.where(handState[:,0] <= f22)[0])
idx33 = list(idx11.intersection(idx22))
'''手部静止标记'''
handState[idx33, 2] = 2
'''状态变化输出'''
for tid, fid in mtrackFid.items():
@ -172,16 +188,11 @@ def devide_motion_state(tboxes, width):
fstate[list(fid), 0] = tid
frameState = np.concatenate((frameState, fstate), axis = 1).astype(np.int64)
return frameState
return frameState, handState
def state_measure(periods, weights, spath=None):
def state_measure(periods, weights, hands, spath=None):
'''两种状态：static、motion,
(t0, t1)
t0: static ----> motion
@ -269,15 +280,16 @@ def main():
'''====================图像运动分析===================='''
win_width = 12
periods = []
periods, hands = [], []
for ctype, tboxes, _ in tracker_boxes:
period = devide_motion_state(tboxes, win_width)
period, handState = devide_motion_state(tboxes, win_width)
periods.append((ctype, period))
hands.append((ctype, handState))
print('done!')
'''===============重力、图像信息融合==================='''
state_measure(periods, weights)
state_measure(periods, weights, hands)
if __name__ == "__main__":