更新 detacttracking

detecttracking/tracking/dotrack/track_select.py

@@ -0,0 +1,91 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Jul 29 10:28:21 2024
+    未来需将这一部分和轨迹分析代码集成
+
+@author: ym
+"""
+import numpy as np
+import cv2
+from scipy.spatial.distance import cdist
+
+class TProp:
+    def __init__(self, boxes):
+        
+        self.boxes = boxes
+        
+    
+    
+
+
+class TProp:
+    '''抽象基类，不能实例化对象'''
+    def __init__(self, boxes):
+        '''
+        boxes: [x1, y1, x2, y2, track_id, score, cls, frame_index, box_index] 
+                0   1   2   3      4        5     6       7           8     
+        '''
+        # assert len(set(boxes[:, 4].astype(int))) == 1, "For a Track, track_id more than 1"
+        # assert len(set(boxes[:, 6].astype(int))) == 1, "For a Track, class number more than 1"
+        
+        self.boxes = boxes
+        
+        '''5个关键点（中心点、左上点、右上点、左下点、右下点 ）坐标'''
+        self.compute_cornpoints()
+        
+        '''5个关键点轨迹特征，可以在子类中实现，降低顺序处理时的计算量
+          （中心点、左上点、右上点、左下点、右下点 ）轨迹特征'''
+        self.compute_cornpts_feats()
+        
+        self.distmax = max(self.trajdist)
+        
+        
+    def compute_cornpoints(self):
+        '''
+        cornpoints 共10项，分别是个点的坐标值（x, y）
+            (center, top_left, top_right, bottom_left, bottom_right)
+        '''
+        boxes = self.boxes
+        cornpoints = np.zeros((self.frnum, 10))
+        cornpoints[:,0] = (boxes[:, 0] + boxes[:, 2]) / 2
+        cornpoints[:,1] = (boxes[:, 1] + boxes[:, 3]) / 2
+        cornpoints[:,2], cornpoints[:,3] = boxes[:, 0], boxes[:, 1]
+        cornpoints[:,4], cornpoints[:,5] = boxes[:, 2], boxes[:, 1]
+        cornpoints[:,6], cornpoints[:,7] = boxes[:, 0], boxes[:, 3]
+        cornpoints[:,8], cornpoints[:,9] = boxes[:, 2], boxes[:, 3]
+
+        self.cornpoints = cornpoints
+    def compute_cornpts_feats(self):
+        '''
+        '''
+        trajectory = []
+        trajlens = []
+        trajdist = []
+        trajrects = []
+        for k in range(5):
+            # diff_xy2 = np.power(np.diff(self.cornpoints[:, 2*k:2*(k+1)], axis = 0), 2)
+            # trajlen = np.sum(np.sqrt(np.sum(diff_xy2, axis = 1)))
+            
+            X = self.cornpoints[:, 2*k:2*(k+1)]
+            
+            traj = np.linalg.norm(np.diff(X, axis=0), axis=1)
+            trajectory.append(traj)
+            
+            trajlen = np.sum(traj)
+            trajlens.append(trajlen)
+            
+            ptdist = np.max(cdist(X, X))
+            trajdist.append(ptdist)
+            
+            '''最小外接矩形：
+                   rect[0]: 中心(x, y)
+                   rect[1]: (w, h)
+                   rect[0]: 旋转角度 (-90°, 0]  
+            '''  
+            rect = cv2.minAreaRect(X.astype(np.int64))
+            trajrects.append(rect)
+        
+        self.trajectory = trajectory
+        self.trajlens = trajlens
+        self.trajdist = trajdist
+        self.trajrects = trajrects