# -*- coding: utf-8 -*- """ Created on Mon Mar 4 18:28:47 2024 @author: ym """ import cv2 import numpy as np from scipy.spatial.distance import cdist from sklearn.decomposition import PCA from .dotracks import MoveState, Track from pathlib import Path curpath = Path(__file__).resolve().parents[0] curpath = Path(curpath) parpath = curpath.parent class backTrack(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) '''该函数依赖项: self.cornpoints MarginState: list, seven elements, 表示轨迹中boxes出现在图像的 [左上，右上，左中，右中，左下，右下底部] ''' self.isCornpoint, self.MarginState = self.isimgborder() '''该函数依赖项: self.isCornpoint，不能在父类中初始化''' self.trajfeature() '''静止点帧索引''' # self.static_index = self.compute_static_fids() '''运动点帧索引(运动帧两端的静止帧索引)''' # self.moving_index = self.compute_dynamic_fids() self.static_index, self.moving_index = self.compute_static_dynamic_fids() '''该函数依赖项: self.cornpoints，定义 4 个商品位置变量： self.Cent_isIncart, self.LB_isIncart, self.RB_isIncart self.posState = self.Cent_isIncart+self.LB_isIncart+self.RB_isIncart''' self.PositionState(camerType="back") '''self.feature_ious = (incart_iou, outcart_iou, cartboarder_iou, maxbox_iou, minbox_iou) self.incartrates = incartrates''' self.compute_ious_feat() # self.PCA() def isimgborder(self, BoundPixel=10, BoundThresh=0.3): x1, y1 = self.cornpoints[:,2], self.cornpoints[:,3], x2, y2 = self.cornpoints[:,8], self.cornpoints[:,9] condt1 = sum(abs(x1) BoundThresh condt2 = sum(abs(y1) BoundThresh condt3 = sum(abs(x2-self.imgshape[0]) BoundThresh condt4 = sum(abs(y2-self.imgshape[1]) BoundThresh condt = condt1 or condt2 or condt3 or condt4 isCornpoint = False if condt: isCornpoint = True condtA = condt1 and condt2 condtB = condt3 and condt2 condtC = condt1 and not condt2 and not condt4 condtD = condt3 and not condt2 and not condt4 condtE = condt1 and condt4 condtF = condt3 and condt4 condtG = condt4 and not condt1 and not condt3 MarginState = [condtA, condtB, condtC, condtD, condtE, condtF, condtG] return isCornpoint, MarginState def PCA(self): self.pca = PCA() X = self.cornpoints[:, 0:2] self.pca.fit(X) def compute_ious_feat(self): '''输出： self.feature_ious = (incart_iou, outcart_iou, cartboarder_iou, maxbox_iou, minbox_iou) self.incartrates = incartrates， 其中： boxes流：track中所有boxes形成的轨迹图，可分为三部分：incart, outcart, cartboarder incart_iou, outcart_iou, cartboarder_iou：各部分和 boxes流的 iou。 incart_iou = 0，track在购物车外， outcart_iou = 0，track在购物车内，也可能是通过左下角、右下角置入购物车， maxbox_iou, minbox_iou：track中最大、最小 box 和boxes流的iou，二者差值越小，越接近 1，表明track的运动型越小。 incartrates: 各box和incart的iou时序，由小变大，反应的是置入过程，由大变小，反应的是取出过程 ''' incart = cv2.imread(str(parpath/"shopcart/cart_tempt/incart.png"), cv2.IMREAD_GRAYSCALE) outcart = cv2.imread(str(parpath/"shopcart/cart_tempt/outcart.png"), cv2.IMREAD_GRAYSCALE) cartboarder = cv2.imread(str(parpath/"shopcart/cart_tempt/cartboarder.png"), cv2.IMREAD_GRAYSCALE) incartrates = [] temp = np.zeros(incart.shape, np.uint8) maxarea, minarea = 0, self.imgshape[0]*self.imgshape[1] for i in range(self.frnum): # x, y, w, h = self.boxes[i, 0:4] x = (self.boxes[i, 2] + self.boxes[i, 0]) / 2 w = (self.boxes[i, 2] - self.boxes[i, 0]) / 2 y = (self.boxes[i, 3] + self.boxes[i, 1]) / 2 h = (self.boxes[i, 3] - self.boxes[i, 1]) / 2 if w*h > maxarea: maxarea = w*h if w*h < minarea: minarea = w*h cv2.rectangle(temp, (int(x-w/2), int(y-h/2)), (int(x+w/2), int(y+h/2)), 255, cv2.FILLED) temp1 = np.zeros(incart.shape, np.uint8) cv2.rectangle(temp1, (int(x-w/2), int(y-h/2)), (int(x+w/2), int(y+h/2)), 255, cv2.FILLED) temp2 = cv2.bitwise_and(incart, temp1) inrate = cv2.countNonZero(temp1)/(w*h) incartrates.append(inrate) isincart = cv2.bitwise_and(incart, temp) isoutcart = cv2.bitwise_and(outcart, temp) iscartboarder = cv2.bitwise_and(cartboarder, temp) num_temp = cv2.countNonZero(temp) num_incart = cv2.countNonZero(isincart) num_outcart = cv2.countNonZero(isoutcart) num_cartboarder = cv2.countNonZero(iscartboarder) incart_iou = num_incart/num_temp outcart_iou = num_outcart/num_temp cartboarder_iou = num_cartboarder/num_temp maxbox_iou = maxarea/num_temp minbox_iou = minarea/num_temp self.feature_ious = (incart_iou, outcart_iou, cartboarder_iou, maxbox_iou, minbox_iou) self.incartrates = incartrates def compute_static_dynamic_fids(self): if self.MarginState[0] or self.MarginState[2]: idx1 = 4 elif self.MarginState[1] or self.MarginState[3]: idx1 = 3 elif self.MarginState[4]: idx1 = 2 elif self.MarginState[5]: idx1 = 1 elif self.MarginState[6]: if self.trajlens[1] < self.trajlens[2]: idx1 = 1 else: idx1 = 2 else: idx1 = self.trajlens.index(min(self.trajlens)) # idx1 = self.trajlens.index(min(self.trajlens)) trajmin = self.trajectory[idx1] static, dynamic = self.pt_state_fids(trajmin) static = np.array(static) dynamic = np.array(dynamic) if static.size: indx = np.argsort(static[:, 0]) static = static[indx] if dynamic.size: indx = np.argsort(dynamic[:, 0]) dynamic = dynamic[indx] return static, dynamic def is_static(self): '''静态情况 1: 目标关键点最小相对运动轨迹 < 0.2, 指标值偏大 TrajFeat = [trajlen_min, trajlen_max, trajdist_min, trajdist_max, trajlen_rate, trajdist_rate] ''' # print(f"TrackID: {self.tid}") boxes = self.boxes '''静态情况 1: ''' condt1 = self.TrajFeat[5] < 0.2 or self.TrajFeat[3] < 120 '''静态情况 2: 目标初始状态为静止，适当放宽关键点最小相对运动轨迹 < 0.5''' condt2 = self.static_index.size > 0 \ and self.static_index[0, 0] <= 2 \ and self.static_index[0, 1] >= 5 \ and self.TrajFeat[5] < 0.5 \ and self.TrajFeat[1] < 240 \ and self.isWholeInCart # and self.posState >= 2 # and self.TrajFeat[0] < 240 \ '''静态情况 3: 目标初始状态和最终状态均为静止''' condt3 = self.static_index.shape[0] >= 2 \ and self.static_index[0, 0] <= 2 \ and self.static_index[0, 1] >= 5 \ and self.static_index[-1, 1] >= self.frnum-3 \ and self.TrajFeat[1] < 240 \ and self.isWholeInCart # and self.posState >= 2 # and self.TrajFeat[0] < 240 \ condt4 = self.static_index.shape[0] >= 2 \ and self.static_index[0, 0] <= 2 \ and self.static_index[0, 1] >= 6 \ and self.static_index[-1, 0] <= self.frnum-5 \ and self.static_index[-1, 1] >= self.frnum-2 condt = condt1 or condt2 or condt3 or condt4 return condt def is_OutTrack(self): if self.posState <= 1: isout = True else: isout = False return isout def compute_distance(self): pass def move_start_fid(self): pass def move_end_fid(self): pass