Caltech Pedestrian Detection数据的预处理

参考博客链接：

https://blog.csdn.net/a2008301610258/article/details/45873867
https://github.com/hizhangp/caltech-pedestrian-converter
http://www.kanadas.com/program-e/2015/06/converting_caltech_pedestrian.html

需要实现的功能：

将seq格式的视频文件提取图片，保存为.jpg格式的图片。
将vbb格式的bounding box标注文件转换为txt文件，供darknet，caffe-ssd等模型进行训练。

目的：训练yolov3和yolo-v3-tiny，需要大规模的行人检测数据集，因此就选到了Caltech Pedestrian Detection这个数据集。

从seq格式文件提取图片并保存

#-*-coding:utf-8-*-
import os
import numpy as np
import cv2
import os.path
import fnmatch
import shutildef open_save(file,savepath):# read .seq file, and save the images into the savepathf = open(file,'rb')string = str(f.read())splitstring = "\xFF\xD8\xFF\xE0\x00\x10\x4A\x46\x49\x46"# split .seq file into segment with the image prefixstrlist=string.split(splitstring)f.close()count = 0# delete the image folder path if it existsif os.path.exists(savepath):shutil.rmtree(savepath)# create the image folder pathif not os.path.exists(savepath):os.mkdir(savepath)# deal with file segment, every segment is an image except the first onefor img in strlist:filename = str(count)+'.jpg'filenamewithpath=os.path.join(savepath, filename)# abandon the first one, which is filled with .seq headerif count > 0:i=open(filenamewithpath,'wb+')i.write(splitstring)i.write(img)i.close()count += 1if __name__=="__main__":for i in range(11):rootdir = "./set{:02}/".format(i)print rootdir# walk in the rootdir, take down the .seq filename and filepathfor parent, dirnames, filenames in os.walk(rootdir):for filename in filenames:# check .seq file with suffixif fnmatch.fnmatch(filename,'*.seq'):# take down the filename with path of .seq filethefilename = os.path.join(parent, filename)# create the image folder by combining .seq file path with .seq filenamethesavepath = os.path.join(parent, filename.split('.')[0])print("Filename=" + thefilename)print("Savepath=" + thesavepath)open_save(thefilename,thesavepath)

效果：提取出set00/V000/1.jpg这样命令的图片，这里的图片id和下面生成的bbx的id是一一对应的

从vbb格式文件提取出bounding box

clear
clc
root_dir = 'E:/唐圣钦/person/annotations/';
path1 = dir(root_dir);
for i=3:length(path1)dir1 = path1(i).name;path2 = dir([ root_dir , dir1])for j=3:length(path2)ful_path = [root_dir, dir1, '/', path2(j).name]temp = strsplit(ful_path, '.');save_path = strcat(temp(1), '.txt');save_path = save_path{1}A = vbb('vbbLoad', ful_path );c=fopen(save_path, 'w');for i = 1:A.nFrameiframe = A.objLists(1,i);iframe_data = iframe{1,1};n1length = length(iframe_data);for  j = 1:n1lengthiframe_dataj = iframe_data(j);if iframe_dataj.pos(1) ~= 0  %pos  posvfprintf(c,'%d %f %f %f %f\n', i, iframe_dataj.pos(1),iframe_dataj.pos(2),iframe_dataj.pos(3),iframe_dataj.pos(4));endendendfclose(c);end
end

效果：生成annotations/set00/V000.txt这样的txt文件，格式：id, x, y, w, h （x,y为左上角坐标）

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Caltech Pedestrian Detection数据的预处理

从seq格式文件提取图片并保存

从vbb格式文件提取出bounding box

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