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MOT15数据集格式简介
gt可视化
本人修改的GT可视化代码#xff1a; MOT15数据集格式简介
以下内容转自#xff1a;【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#xff1a;https://pan.baidu.com/s/1foGrBXvsanW8BI4eybqfWg?…目录
MOT15数据集格式简介
gt可视化
本人修改的GT可视化代码 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?pwd8888
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idid目标idbb_leftbbox左上角坐标xbb_topbbox左上角坐标ybb_widthbbox的宽度bb_heightbbox的高度conf置信度x三维坐标系x值对于二维任务填充为-1y三维坐标系y值对于二维任务填充为-1z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
import osimport cv2
def match_obj(obj_list, obj_id):try:index obj_list.index(obj_id)except:index -1return indexif __name__ __main__:dir_arB:\data\track\MOT15\train\ADL-Rundle-6img_dirrB:\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_i1track_showTrueimg cv2.imread(img_dir/img1/ 0000{:02d}.jpg.format(img_i))img2 imgfor 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_i1img cv2.imread(img_dir /img1/ 0000{:02d}.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 import sys
import base64
import os
from collections import OrderedDictimport 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 jsonif __name__ __main__:dir_arB:\data\track\MOT15\trainimg_dirrB:\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 3.16.7flags {}lineColor [0, 255, 0, 128]fillColor [255, 0, 0, 128]track_showTruesave_jsonFalsefor xmlpathName in txt_paths:xmlpathNamexmlpathName.replace(\\,/)dancetrack_namexmlpathName.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 {:06d}.format(int(frame)) .jpgbox [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] versiondic[flags] flagsdic[shapes] []img_path dancetrack_name/img1/ image_nameimg_new_name dancetrack_name _ image_nameimg_new_path img_dir img_pathimg cv2.imread(img_new_path)imageHeight, imageWidth, _ img.shapefor box in img_info[image_name]:shape {}shape[label] personshape[line_color] Noneshape[fill_color] Nonex1 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,y120), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,0,255), 2)shape[points] [[x1, y1], [x2, y2]]shape[shape_type] rectangleshape[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] lineColordic[fillColor] fillColordic[imagePath] img_new_namedic[imageData] base64.b64encode(open({}.format(img_new_path), rb).read()).decode(utf-8)dic[imageHeight] imageHeightdic[imageWidth] imageWidthfw 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
