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更新 detacttracking

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lee
2025-01-22 13:16:44 +08:00
parent 2320468c40
commit c9d79f8059
355 changed files with 61097 additions and 1 deletions
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detecttracking/tracking/utils/read_pipeline_data.py Normal file
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# -*- coding: utf-8 -*-
"""
Created on Tue May 21 15:25:23 2024
读取 Pipeline 各模块的数据，主代码由 马晓慧 完成
@author: ieemoo-zl003
"""
import os
import numpy as np
# 替换为你的目录路径
files_path = 'D:/contrast/dataset/1_to_n/709/20240709-112658_6903148351833/'
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 = np.array([float(x) for x in s.split(",")])
return float_array
def extract_tracker_input_boxes_feats(file_name):
boxes = []
feats = []
with open(file_name, '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
# 跳过空行
if not line:
continue
# 检查是否以'box:'或'feat:'开始
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)) # 去掉'box:'并去除可能的空白字符
if line.find("feat:") >= 0:
feat = line[line.find("feat:") + 5:].strip()
feats.append(str_to_float_arr(feat)) # 去掉'box:'并去除可能的空白字符
return np.array(boxes), np.array(feats)
def find_string_in_array(arr, target):
"""
在字符串数组中找到目标字符串对应的行（索引）。
参数:
arr -- 字符串数组
target -- 要查找的目标字符串
返回:
目标字符串在数组中的索引。如果未找到，则返回-1。
"""
tg = [float(t) for k, t in enumerate(target.split(',')) if k<4][:4]
for i, st in enumerate(arr):
st = [float(s) for k, s in enumerate(target.split(',')) if k<4][:4]
if st == tg:
return i
# if st[:20] == target[:20]:
# return i
return -1
def find_samebox_in_array(arr, target):
for i, st in enumerate(arr):
if all(st[:4] == target[:4]):
return i
return -1
def extract_tracker_output_boxes_feats(read_file_name):
input_boxes, input_feats = extract_tracker_input_boxes_feats(read_file_name)
boxes = []
feats = []
with open(read_file_name, '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
# 跳过空行
if not line:
continue
# 检查是否以'output_box:'开始
if line.find("output_box:") >= 0:
box = str_to_float_arr(line[line.find("output_box:") + 11:].strip())
boxes.append(box) # 去掉'output_box:'并去除可能的空白字符
index = find_samebox_in_array(input_boxes, box)
if index >= 0:
# feat_f = str_to_float_arr(input_feats[index])
feat_f = input_feats[index]
norm_f = np.linalg.norm(feat_f)
feat_f = feat_f / norm_f
feats.append(feat_f)
return input_boxes, input_feats, np.array(boxes), np.array(feats)
def extract_tracking_output_boxes_feats(read_file_name):
tracker_boxes, tracker_feats, input_boxes, input_feats = extract_tracker_output_boxes_feats(read_file_name)
boxes = []
feats = []
tracking_flag = False
with open(read_file_name, '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
# 跳过空行
if not line:
continue
if tracking_flag:
if line.find("tracking_") >= 0:
tracking_flag = False
else:
box = str_to_float_arr(line)
boxes.append(box)
index = find_samebox_in_array(input_boxes, box)
if index >= 0:
feats.append(input_feats[index])
# 检查是否以tracking_'开始
if line.find("tracking_") >= 0:
tracking_flag = True
assert(len(tracker_boxes)==len(tracker_feats)), "Error at Yolo output"
assert(len(input_boxes)==len(input_feats)), "Error at tracker output"
assert(len(boxes)==len(feats)), "Error at tracking output"
return tracker_boxes, tracker_feats, input_boxes, input_feats, np.array(boxes), np.array(feats)
def read_tracking_input(datapath):
with open(datapath, 'r') as file:
lines = file.readlines()
data = []
for line in lines:
data.append([s for s in line.split(',') if len(s)>=3])
# data.append([float(s) for s in line.split(',') if len(s)>=3])
# data = np.array(data, dtype = np.float32)
try:
data = np.array(data, dtype = np.float32)
except Exception as e:
data = np.array([], dtype = np.float32)
print('DataError for func: read_tracking_input()')
return data
def read_tracker_input(datapath):
with open(datapath, 'r') as file:
lines = file.readlines()
Videos = []
FrameBoxes, FrameFeats = [], []
boxes, feats = [], []
timestamp = []
t1 = None
for line in lines:
if line.find('CameraId') >= 0:
t = int(line.split(',')[1].split(':')[1])
timestamp.append(t)
if len(boxes) and len(feats):
FrameBoxes.append(np.array(boxes, dtype = np.float32))
FrameFeats.append(np.array(feats, dtype = np.float32))
boxes, feats = [], []
if t1 and t - t1 > 1e3:
Videos.append((FrameBoxes, FrameFeats))
FrameBoxes, FrameFeats = [], []
t1 = int(line.split(',')[1].split(':')[1])
if line.find('box') >= 0:
box = line.split(':', )[1].split(',')[:-1]
boxes.append(box)
if line.find('feat') >= 0:
feat = line.split(':', )[1].split(',')[:-1]
feats.append(feat)
FrameBoxes.append(np.array(boxes, dtype = np.float32))
FrameFeats.append(np.array(feats, dtype = np.float32))
Videos.append((FrameBoxes, FrameFeats))
# TimeStamp = np.array(timestamp, dtype = np.int64)
# DimesDiff = np.diff((TimeStamp))
# sorted_indices = np.argsort(TimeStamp)
# TimeStamp_sorted = TimeStamp[sorted_indices]
# DimesDiff_sorted = np.diff((TimeStamp_sorted))
return Videos
def 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):
# 构造完整的文件路径
file_path = os.path.join(files_path, filename)
if os.path.isfile(file_path) and filename.find("track.data")>0:
tracker_boxes, tracker_feats, tracking_boxes, tracking_feats, output_boxes, output_feats = extract_tracking_output_boxes_feats(file_path)
print("Done")
if __name__ == "__main__":
main()