更新 detacttracking

detecttracking/tracking/dotrack/track_front.py

@@ -0,0 +1,194 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar  4 18:33:01 2024
+
+@author: ym
+"""
+import numpy as np
+import cv2
+# from sklearn.cluster import KMeans
+from .dotracks import MoveState, Track
+
+from pathlib import Path
+curpath = Path(__file__).resolve().parents[0]
+curpath = Path(curpath)
+parpath = curpath.parent
+
+
+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, features, imgshape=(1024, 1280)):
+        
+        super().__init__(boxes, features, imgshape)
+        
+        self.CART_HIGH_THRESH1 = imgshape[1]/2.98
+        
+        '''y1、y2静止状态区间，值是 boxes 中对 axis=0 的索引，不是帧索引'''
+        det_y1 = np.diff(boxes[:, 1], axis=0)
+        det_y2 = np.diff(boxes[:, 3], axis=0)
+        self.static_y1, self.dynamic_y1 = self.pt_state_fids(det_y1)
+        self.static_y2, self.dynamic_y2 = self.pt_state_fids(det_y2)
+        
+        self.isCornpoint = self.is_left_or_right_cornpoint()
+        self.isBotmpoint = self.is_bottom_cornpoint()
+        
+        '''该函数依赖项: self.isCornpoint，不能在父类中初始化'''
+        self.trajfeature()
+        
+        self.PositionState(camerType="front")
+        
+        '''手部状态分析'''
+        self.HAND_STATIC_THRESH = 100
+        self.CART_POSIT_0 = 430
+        self.CART_POSIT_1 = 620
+
+    def is_left_or_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 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 is_upward(self):
+        '''判断商品是否取出，'''
+        print(f"The ID is: {self.tid}")
+        
+    def is_free_move(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()) and min(y0)>self.CART_HIGH_THRESH1
+
+
+        '''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
+    
+    
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