modified for site test

tracking/utils/read_data.py

@@ -0,0 +1,236 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Jul  5 13:59:21 2024
+func: extract_data()
+  读取 Pipeline 各模块的数据，在 read_pipeline_data.py（马晓慧）的基础上完成接口改造
+
+@author: ym
+"""
+import numpy as np
+import re
+import os
+
+
+
+
+def str_to_float_arr(s):
+    # 移除字符串末尾的逗号（如果存在）  
+    if s.endswith(','):  
+        s = s[:-1]  
+      
+    # 使用split()方法分割字符串，然后将每个元素转化为float  
+    float_array = [float(x) for x in s.split(",")]
+    return float_array        
+
+
+def find_samebox_in_array(arr, target):
+
+    for i, st in enumerate(arr):
+        if st[:4] == target[:4]:
+            return i
+    return -1
+
+
+def extract_data(datapath):
+    bboxes, ffeats = [], []
+    
+    trackerboxes = np.empty((0, 9), dtype=np.float64)
+    trackerfeats = np.empty((0, 256), dtype=np.float64)
+    
+    boxes, feats, tboxes, tfeats = [], [], [], []
+    with open(datapath, 'r', encoding='utf-8') as lines:
+        for line in lines:  
+            line = line.strip()  # 去除行尾的换行符和可能的空白字符  
+            if not line:  # 跳过空行  
+                continue
+            
+            if line.find("CameraId")>=0:
+                if len(boxes): bboxes.append(np.array(boxes))
+                if len(feats): ffeats.append(np.array(feats))
+                if len(tboxes):  
+                    trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)))
+                if len(tfeats):
+                    trackerfeats = np.concatenate((trackerfeats, np.array(tfeats)))
+     
+                boxes, feats, tboxes, tfeats = [], [], [], []
+            
+            if line.find("box:") >= 0 and line.find("output_box:") < 0:
+                box = line[line.find("box:") + 4:].strip()
+                boxes.append(str_to_float_arr(box))
+                
+            if line.find("feat:") >= 0:
+                feat = line[line.find("feat:") + 5:].strip()
+                feats.append(str_to_float_arr(feat))
+                    
+            if line.find("output_box:") >= 0:
+                box = str_to_float_arr(line[line.find("output_box:") + 11:].strip())
+                tboxes.append(box)  # 去掉'output_box:'并去除可能的空白字符  
+                index = find_samebox_in_array(boxes, box)
+                if index >= 0:
+                    # feat_f = str_to_float_arr(input_feats[index])
+                    feat_f = feats[index]
+                    norm_f = np.linalg.norm(feat_f) 
+                    feat_f = feat_f / norm_f
+                    tfeats.append(feat_f)
+    
+    if len(boxes): bboxes.append(np.array(boxes))
+    if len(feats): ffeats.append(np.array(feats))
+    if len(tboxes): trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)))
+    if len(tfeats): trackerfeats = np.concatenate((trackerfeats, np.array(tfeats)))
+    
+    assert(len(bboxes)==len(ffeats)), "Error at Yolo output!"
+    assert(len(trackerboxes)==len(trackerfeats)), "Error at tracker output!"
+    
+    tracker_feat_dict = {}
+    for i in range(len(trackerboxes)):
+        tid, fid, bid = int(trackerboxes[i, 4]), int(trackerboxes[i, 7]), int(trackerboxes[i, 8])
+        if f"frame_{fid}" not in tracker_feat_dict:
+            tracker_feat_dict[f"frame_{fid}"]= {"feats": {}}
+        tracker_feat_dict[f"frame_{fid}"]["feats"].update({bid: trackerfeats[i, :]})
+    
+    
+    boxes, trackingboxes= [], []
+    tracking_flag = False    
+    with open(datapath, 'r', encoding='utf-8') as lines:
+        for line in lines:  
+            line = line.strip()  # 去除行尾的换行符和可能的空白字符  
+            if not line:  # 跳过空行  
+                continue       
+            if tracking_flag:
+                if line.find("tracking_") >= 0:
+                    tracking_flag = False
+                else:
+                    box = str_to_float_arr(line)
+                    boxes.append(box)
+            if line.find("tracking_") >= 0:
+                tracking_flag = True
+                if len(boxes):
+                    trackingboxes.append(np.array(boxes))
+                boxes = []
+    
+    if len(boxes): 
+        trackingboxes.append(np.array(boxes))
+    
+    tracking_feat_dict = {}
+    for i, boxes in enumerate(trackingboxes):
+        for box in boxes:
+            tid, fid, bid = int(box[4]), int(box[7]), int(box[8])
+            if f"track_{tid}" not in tracking_feat_dict:
+                tracking_feat_dict[f"track_{tid}"]= {"feats": {}}
+            tracking_feat_dict[f"track_{tid}"]["feats"].update({f"{fid}_{bid}": tracker_feat_dict[f"frame_{fid}"]["feats"][bid]})
+
+    return bboxes, ffeats, trackerboxes, tracker_feat_dict, trackingboxes, tracking_feat_dict
+
+def read_tracking_output(filepath):
+    boxes = []
+    feats = []
+    with open(filepath, 'r', encoding='utf-8') as file:
+        for line in file:  
+            line = line.strip()  # 去除行尾的换行符和可能的空白字符
+            
+            if not line:  
+                continue 
+            
+            if line.endswith(','):  
+                line = line[:-1]
+                
+            data = np.array([float(x) for x in line.split(",")])
+            if data.size == 9:
+                boxes.append(data)
+            if data.size == 256:
+                feats.append(data)
+    
+    return np.array(boxes), np.array(feats) 
+    
+
+def read_deletedBarcode_file(filePth):
+    with open(filePth, 'r', encoding='utf-8') as f:
+        lines = f.readlines()
+
+        split_flag, all_list = False, []
+        dict, barcode_list, similarity_list =  {}, [], []
+  
+        clean_lines = [line.strip().replace("'", '').replace('"', '') for line in lines]
+        for line in clean_lines:
+            stripped_line = line.strip()
+            if not stripped_line:
+                if len(barcode_list): dict['barcode'] = barcode_list
+                if len(similarity_list): dict['similarity'] = similarity_list
+                if len(dict): all_list.append(dict)
+                
+                split_flag = False
+                dict, barcode_list, similarity_list =  {}, [], []
+                continue
+            
+            # print(line)
+            label = line.split(':')[0]
+            value = line.split(':')[1]
+            if label == 'SeqDir':
+                dict['SeqDir'] = value
+            if label == 'Deleted':
+                dict['Deleted'] = value
+            if label == 'List':
+                split_flag = True
+                continue
+            if split_flag:
+                barcode_list.append(label)
+                similarity_list.append(value)
+        
+        if len(barcode_list): dict['barcode'] = barcode_list
+        if len(similarity_list): dict['similarity'] = similarity_list
+        if len(dict): all_list.append(dict)
+    return all_list
+
+
+
+
+if __name__ == "__main__":    
+    files_path = 'D:/contrast/dataset/1_to_n/709/20240709-112658_6903148351833/'  
+    
+    # 遍历目录下的所有文件和目录  
+    for filename in os.listdir(files_path):    
+        filename = '1_track.data'
+        file_path = os.path.join(files_path, filename)
+        if os.path.isfile(file_path) and filename.find("track.data")>0:
+            extract_data(file_path)
+ 
+            print("Done")
+
+    
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