update
This commit is contained in:
lee
275
ytracking/tracking/dotrack/track_front.py
Normal file
275
ytracking/tracking/dotrack/track_front.py
Normal file
@ -0,0 +1,275 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Created on Mon Mar 4 18:33:01 2024
|
||||
|
||||
@author: ym
|
||||
"""
|
||||
import numpy as np
|
||||
from sklearn.cluster import KMeans
|
||||
from .dotracks import MoveState, Track
|
||||
|
||||
|
||||
class frontTrack(Track):
|
||||
# boxes: [x1, y1, x2, y2, track_id, score, cls, frame_index, box_index]
|
||||
# 0, 1, 2, 3, 4, 5, 6, 7, 8
|
||||
def __init__(self, boxes, imgshape=(1024, 1280)):
|
||||
|
||||
super().__init__(boxes, imgshape)
|
||||
self.hands = []
|
||||
|
||||
self.mwh = np.mean((self.boxes[:, 2] - self.boxes[:, 0]) *
|
||||
(self.boxes[:, 3] - self.boxes[:, 1]))
|
||||
|
||||
|
||||
'''5个关键点（中心点、左上点、右上点、左下点、右下点 ）轨迹特征'''
|
||||
self.compute_cornpts_feats()
|
||||
|
||||
|
||||
self.CART_HIGH_THRESH1 = imgshape[1]/2.98
|
||||
|
||||
|
||||
|
||||
|
||||
# if self.tid==10:
|
||||
# print(f"ID: {self.tid}")
|
||||
|
||||
'''y1、y2静止状态区间，值是 boxes 中对 axis=0 的索引，不是帧索引'''
|
||||
self.static_y1, self.dynamic_y1 = self.compute_static_fids(boxes[:, 1])
|
||||
self.static_y2, self.dynamic_y2 = self.compute_static_fids(boxes[:, 3])
|
||||
|
||||
self.isCornpoint = self.is_left_right_cornpoint()
|
||||
self.isBotmpoint = self.is_bottom_cornpoint()
|
||||
|
||||
self.trajfeature()
|
||||
|
||||
'''手部状态分析'''
|
||||
self.HAND_STATIC_THRESH = 100
|
||||
self.CART_POSIT_0 = 430
|
||||
self.CART_POSIT_1 = 620
|
||||
|
||||
|
||||
|
||||
|
||||
def is_left_right_cornpoint(self):
|
||||
''' 基于 all(boxes)，
|
||||
boxes左下角点和图像左下角点重叠 或
|
||||
boxes右下角点和图像左下角点重叠
|
||||
'''
|
||||
x1, y1 = self.boxes[:, 0], self.boxes[:, 1]
|
||||
x2, y2 = self.boxes[:, 2], self.boxes[:, 3]
|
||||
|
||||
# Left-Bottom cornpoint
|
||||
condt1 = all(x1 < 5) and all(y2 > self.imgshape[1]-5)
|
||||
|
||||
# Right-Bottom cornpoint
|
||||
condt2 = all(x2 > self.imgshape[0]-5) and all(y2 > self.imgshape[1]-5)
|
||||
|
||||
condt = condt1 or condt2
|
||||
|
||||
return condt
|
||||
|
||||
def is_edge_cornpoint(self):
|
||||
'''基于 all(boxes)，boxes是否和图像左右边缘重叠'''
|
||||
x1, x2 = self.boxes[:, 0], self.boxes[:, 2]
|
||||
condt = all(x1 < 3) or all(x2 > self.imgshape[0]-3)
|
||||
|
||||
return condt
|
||||
|
||||
def is_bottom_cornpoint(self):
|
||||
'''基于 all(boxes)，boxes是否和图像下边缘重叠'''
|
||||
condt = all(self.boxes[:, 3] > self.imgshape[1]-20)
|
||||
|
||||
return condt
|
||||
|
||||
def compute_static_fids(self, y, STATIC_THRESH = 8):
|
||||
'''
|
||||
前摄时，y一般选择为 box 的 y1 坐标，且需限定商品在购物车内。
|
||||
inputs：
|
||||
y：1D array，
|
||||
parameters：
|
||||
STATIC_THRESH：轨迹处于静止状态的阈值。
|
||||
outputs：
|
||||
输出为差分值小于 STATIC_THRESH 的y中元素的（start, end）索引
|
||||
ranges = [(x1, y1),
|
||||
(x1, y1),
|
||||
...]
|
||||
'''
|
||||
# print(f"The ID is: {self.tid}")
|
||||
|
||||
det_y = np.diff(y, axis=0)
|
||||
ranges, rangex = [], []
|
||||
|
||||
static_indices = np.where(np.abs(det_y) < STATIC_THRESH)[0]
|
||||
|
||||
if len(static_indices) == 0:
|
||||
rangex.append((0, len(y)-1))
|
||||
return ranges, rangex
|
||||
|
||||
start_index = static_indices[0]
|
||||
|
||||
for i in range(1, len(static_indices)):
|
||||
if static_indices[i] != static_indices[i-1] + 1:
|
||||
ranges.append((start_index, static_indices[i-1] + 1))
|
||||
start_index = static_indices[i]
|
||||
ranges.append((start_index, static_indices[-1] + 1))
|
||||
|
||||
if len(ranges) == 0:
|
||||
rangex.append((0, len(y)-1))
|
||||
return ranges, rangex
|
||||
|
||||
idx1, idx2 = ranges[0][0], ranges[-1][1]
|
||||
|
||||
if idx1 != 0:
|
||||
rangex.append((0, idx1))
|
||||
|
||||
# 轨迹的最后阶段是运动状态
|
||||
for k in range(1, len(ranges)):
|
||||
index1 = ranges[k-1][1]
|
||||
index2 = ranges[k][0]
|
||||
rangex.append((index1, index2))
|
||||
|
||||
if idx2 != len(y)-1:
|
||||
rangex.append((idx2, len(y)-1))
|
||||
|
||||
return ranges, rangex
|
||||
|
||||
def is_Static(self):
|
||||
assert self.frnum > 1, "boxes number must greater than 1"
|
||||
# print(f"The ID is: {self.tid}")
|
||||
|
||||
# 手部和小孩目标不考虑
|
||||
if self.cls == 0 or self.cls == 9:
|
||||
return False
|
||||
|
||||
# boxes 全部 y2=1280
|
||||
if self.isBotmpoint:
|
||||
return True
|
||||
|
||||
boxes = self.boxes
|
||||
y0 = (boxes[:, 1]+boxes[:, 3])/2
|
||||
|
||||
## 纵轴矢量和
|
||||
sum_y0 = y0[-1] - y0[0]
|
||||
sum_y1 = boxes[-1, 1]-boxes[0, 1]
|
||||
sum_y2 = boxes[-1, 3]-boxes[0, 3]
|
||||
|
||||
# 一些需要考虑的特殊情况
|
||||
isbottom = max(boxes[:, 3]) > 1280-3
|
||||
istop = min(boxes[:, 1]) < 3
|
||||
isincart = min(y0) > self.CART_HIGH_THRESH1
|
||||
uncert = abs(sum_y1)<100 and abs(sum_y2)<100
|
||||
|
||||
'''初始条件：商品中心点始终在购物车内、'''
|
||||
condt0 = max((boxes[:, 1]+boxes[:, 3])/2) > self.CART_HIGH_THRESH1
|
||||
|
||||
'''条件1：轨迹运动纵向和（y1 或 y2）描述商品轨迹长度，存在情况：
|
||||
(1). 检测框可能与图像上下边缘重合，
|
||||
(2). 上边或下边存在跳动
|
||||
'''
|
||||
if isbottom and istop:
|
||||
condt1 = abs(sum_y0) < 300
|
||||
elif isbottom: # y2在底部，用y1表征运动
|
||||
condt1 = sum_y1 > -120 and abs(sum_y0)<80 # 有底部点，方向向上阈值小于100
|
||||
elif istop: # y1在顶部，用y2表征运动
|
||||
condt1 = abs(sum_y2) < 100
|
||||
else:
|
||||
condt1 = (abs(sum_y1) < 30 or abs(sum_y2)<30)
|
||||
|
||||
'''条件2：轨迹的开始和结束阶段均处于静止状态, 利用静止状态区间判断，用 y1
|
||||
a. 商品在购物车内，
|
||||
b. 检测框的起始阶段和结束阶段均为静止状态
|
||||
c. 静止帧长度 > 3'''
|
||||
|
||||
condt2 = False
|
||||
if len(self.static_y1)>=2:
|
||||
condt_s0 = self.static_y1[0][0]==0 and self.static_y1[0][1] - self.static_y1[0][0] >= 3
|
||||
condt_s1 = self.static_y1[-1][1]==self.frnum-1 and self.static_y1[-1][1] - self.static_y1[-1][0] >= 3
|
||||
condt2 = condt_s0 and condt_s1 and isincart
|
||||
|
||||
|
||||
condt = condt0 and (condt1 or condt2)
|
||||
|
||||
return condt
|
||||
|
||||
|
||||
def extract_hand_features(self):
|
||||
self.isHandStatic = False
|
||||
|
||||
x0 = (self.boxes[:, 0] + self.boxes[:, 2]) / 2
|
||||
y0 = (self.boxes[:, 1] + self.boxes[:, 3]) / 2
|
||||
|
||||
handXy = np.stack((x0, y0), axis=-1)
|
||||
handMaxY0 = np.max(y0)
|
||||
|
||||
handCenter = np.array([(max(x0)+min(x0))/2, (max(y0)+min(y0))/2])
|
||||
|
||||
handMaxDist = np.max(np.linalg.norm(handXy - handCenter))
|
||||
|
||||
if handMaxDist < self.HAND_STATIC_THRESH:
|
||||
self.isHandStatic = True
|
||||
return
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
def is_Upward(self):
|
||||
'''判断商品是否取出，'''
|
||||
print(f"The ID is: {self.tid}")
|
||||
|
||||
def is_FreeMove(self):
|
||||
if self.frnum == 1:
|
||||
return True
|
||||
# print(f"The ID is: {self.tid}")
|
||||
|
||||
|
||||
y0 = (self.boxes[:, 1] + self.boxes[:, 3]) / 2
|
||||
det_y0 = np.diff(y0, axis=0)
|
||||
sum_y0 = y0[-1] - y0[0]
|
||||
|
||||
'''情况1：中心点向下 '''
|
||||
## 初始条件：商品第一次检测到在购物车内
|
||||
condt0 = y0[0] > self.CART_HIGH_THRESH1
|
||||
|
||||
condt_a = False
|
||||
## 条件1：商品初始为静止状态，静止条件应严格一些
|
||||
condt11, condt12 = False, False
|
||||
if len(self.static_y1)>0:
|
||||
condt11 = self.static_y1[0][0]==0 and self.static_y1[0][1] - self.static_y1[0][0] >= 5
|
||||
if len(self.static_y2)>0:
|
||||
condt12 = self.static_y2[0][0]==0 and self.static_y2[0][1] - self.static_y2[0][0] >= 5
|
||||
|
||||
# 条件2：商品中心发生向下移动
|
||||
condt2 = y0[-1] > y0[0]
|
||||
|
||||
# 综合判断a
|
||||
condt_a = condt0 and (condt11 or condt12) and condt2
|
||||
|
||||
'''情况2：中心点向上 '''
|
||||
## 商品中心点向上移动，但没有关联的Hand轨迹，也不是左右边界点
|
||||
condt_b = condt0 and len(self.hands)==0 and y0[-1] < y0[0] and (not self.is_edge_cornpoint())
|
||||
|
||||
|
||||
'''情况3: 商品在购物车内，但运动方向无序'''
|
||||
## 中心点在购物车内，纵向轨迹和小于轨迹差中绝对值最大的两个值的和，说明运动没有主方向
|
||||
condt_c = False
|
||||
if self.frnum > 3:
|
||||
condt_c = all(y0>self.CART_HIGH_THRESH1) and \
|
||||
(abs(sum_y0) < sum(np.sort(np.abs(det_y0))[::-1][:2])-1)
|
||||
|
||||
condt = (condt_a or condt_b or condt_c) and self.cls!=0
|
||||
|
||||
return condt
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user