目录
MOT15数据集格式简介
以下内容转自：【目标跟踪】MOT数据集GroundTruth可视化-腾讯云开发者社区-腾讯云
MOT15数据集下载：https://pan.baidu.com/s/1foGrBXvsanW8BI4eybqfWg?pwd=8888
以下为一行gt示例：
1,1,1367,393,73,225,1,-1,-1,-1
各列数据对应含义如下
<frame>,<id>,<bb_left>,<bb_top>,<bb_width>,<bb_height>,<conf>,<x>,<y>,<z>复制
- frame:图片帧id
- id：目标id
- bb_left：bbox左上角坐标x
- bb_top：bbox左上角坐标y
- bb_width：bbox的宽度
- bb_height：bbox的高度
- conf：置信度
- x：三维坐标系x值，对于二维任务填充为-1
- y：三维坐标系y值，对于二维任务填充为-1
- z：三维坐标系z值，对于二维任务填充为-1
gt可视化
由于是跟踪任务，因此在可视化检测框的同时进一步添加箭头，用来标识目标的运动轨迹。
处理思路是读取一张图片后，同时读取两张图片的gt，若两张图片同时包含同一个目标，则用箭头连接前一帧bbox的中心点和后一帧bbox的中心点。
只能跟踪一个人：
python
import os
import cv2
def match_obj(obj_list, obj_id):
try:
index = obj_list.index(obj_id)
except:
index = -1
return index
if __name__ == '__main__':
dir_a=r'B:\data\track\MOT15\train\ADL-Rundle-6'
img_dir=r'B:\data\track\MOT15\train\ADL-Rundle-6/'
txt_paths = files = ['%s/%s' % (i[0].replace("\\", "/"), j) for i in os.walk(dir_a) for j in i[-1] if j.endswith(('gt.txt', '.xpng'))]
img_i=1
track_show=True
img = cv2.imread(img_dir+"/img1/" + "0000{:0>2d}.jpg".format(img_i))
img2 = img
for txt_path in txt_paths:
with open(txt_path, 'r') as f:
lines = f.readlines()
object_list = []
center_list = []
for line in lines:
img_id = line.split(',')[0]
if img_id == str(img_i):
object_id = line.split(',')[1]
object_list.append(object_id)
x, y, w, h = int(line.split(',')[2]), int(line.split(',')[3]), int(line.split(',')[4]), int(line.split(',')[5])
center1 = (int(int(x) + int(w) / 2), int(int(y) + int(h) / 2))
center_list.append(center1)
if img_id == str(int(img_i) + 1):
img_i+=1
img = cv2.imread(img_dir + "/img1/" + "0000{:0>2d}.jpg".format(img_i))
object_id = line.split(',')[1]
index = match_obj(object_list, object_id)
x, y, w, h = int(line.split(',')[2]), int(line.split(',')[3]), int(line.split(',')[4]), int(line.split(',')[5])
center2 = (int(int(x) + int(w) / 2), int(int(y) + int(h) / 2))
if index != -1:
img2 = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255))
img2 = cv2.arrowedLine(img2, center_list[index], center2, (0, 255, 255), 1, 8, 0, 0.5)
if track_show:
cv2.imshow("sdf",img)
cv2.waitKey(0)本人修改的GT可视化代码：
python
import sys
import base64
import os
from collections import OrderedDict
import cv2
import shutil
import glob
module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path:
sys.path.append(module_path)
import json
if __name__ == '__main__':
dir_a=r'B:\data\track\MOT15\train'
img_dir=r'B:\data\track\MOT15\train/'
txt_paths = ['%s/%s' % (i[0].replace("\\", "/"), j) for i in os.walk(dir_a) for j in i[-1] if j.endswith(('gt.txt', '.xpng'))]
version = '3.16.7'
flags = {}
lineColor = [0, 255, 0, 128]
fillColor = [255, 0, 0, 128]
track_show=True
save_json=False
for xmlpathName in txt_paths:
xmlpathName=xmlpathName.replace("\\","/")
dancetrack_name=xmlpathName.split("/")[-3]
img_info = OrderedDict()
with open(xmlpathName) as fs:
lines = fs.readlines()
# lines = sorted(lines)
for line in lines:
line = line.replace("\n", '')
line_info = line.split(',')
frame = line_info[0]
frame_image_name = '{:0>6d}'.format(int(frame)) + ".jpg"
box = [int(line_info[2]), int(line_info[3]), int(line_info[2]) + int(line_info[4]),
int(line_info[3]) + int(line_info[5]),int(line_info[1])]
if frame_image_name in img_info:
img_info[frame_image_name].append(box)
else:
img_info[frame_image_name] = [box]
for image_name in img_info.keys():
print(image_name)
dic = {}
dic['version'] = version
dic['flags'] = flags
dic['shapes'] = []
img_path = dancetrack_name+"/img1/" + image_name
img_new_name = dancetrack_name + "_" + image_name
img_new_path = img_dir + img_path
img = cv2.imread(img_new_path)
imageHeight, imageWidth, _ = img.shape
for box in img_info[image_name]:
shape = {}
shape['label'] = 'person'
shape['line_color'] = None
shape['fill_color'] = None
x1 = int(box[0])
y1 = int(box[1])
x2 = int(box[2])
y2 = int(box[3])
if track_show:
cv2.rectangle(img, (x1, y1), (x2, y2), (0,0,255), 1)
cv2.putText(img, "t:" + str(box[4]), (x1,y1+20), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,0,255), 2)
shape['points'] = [[x1, y1], [x2, y2]]
shape['shape_type'] = 'rectangle'
shape['flags'] = {}
dic['shapes'].append(shape)
if track_show:
cv2.putText(img, image_name, (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 1)
cv2.imshow("sdf",img)
cv2.waitKey(0)
if save_json:
dic['lineColor'] = lineColor
dic['fillColor'] = fillColor
dic['imagePath'] = img_new_name
dic['imageData'] = base64.b64encode(open('{}'.format(img_new_path), "rb").read()).decode('utf-8')
dic['imageHeight'] = imageHeight
dic['imageWidth'] = imageWidth
fw = open('{}json'.format(img_new_path.replace(img_new_path.split('.')[-1], "")), 'w')
json.dump(dic, fw)
fw.close()可视化效果如图所示：
在这里插入图片描述