样本标注

int main()
{
    std::ifstream fin("D:\Data\MyAnnoData\视频\0.txt");//打开原始样本图片文件列表   

    Mat colorImage, detectSquareImg;
    string videoReadPath;

    int videoCnt = 0;//视频计数

    FILE* f = fopen("F:\videoList.txt", "wt");
    if (f == NULL)
    {
        printf("文件打开失败!
");
    }
    else
    {
        printf("文件打开成功!
");
    }

    while (getline(fin, videoReadPath)) //一行一行读取文件列表  
    {
        videoCnt++;
        string videoPath = videoReadPath;
        cout << videoPath << endl;

        VideoCapture capture(videoPath);//读入视频


        if (!capture.isOpened())//判断是否打开视频文件  
        {
            cout << "video not open..." << endl;
            continue;
        }
        else
        {
            int imgCnt = 0;//图片计数            
            while (1)
            {
                imgCnt++;
                cout << imgCnt << endl;

                if (imgCnt % 4 != 0)
                {
                    continue;
                }

                capture >> colorImage;//读入图片
                if (colorImage.empty())
                {
                    break;
                }
                else
                {
                    if (colorImage.channels() != 3)
                    {
                        cvtColor(colorImage, colorImage, CV_GRAY2BGR);
                    }

                    //调用算法进行检测
                    DetectNcnn detectNcnn;
                    int imgheight = colorImage.rows;
                    int    imgwidth = colorImage.cols;
                    int  maxl = imgheight > imgwidth ? imgheight : imgwidth;
                    int    paddingleft = (maxl - imgwidth) >> 1;
                    int    paddingright = (maxl - imgwidth) >> 1;
                    int    paddingbottom = (maxl - imgheight) >> 1;
                    int    paddingtop = (maxl - imgheight) >> 1;

                    copyMakeBorder(colorImage, detectSquareImg, paddingtop, paddingbottom, paddingleft, paddingright, cv::BORDER_CONSTANT, 0);

                    objects.clear(); classes.clear(); confidences.clear();

                    detectNcnn.detectObjNcnn(detectSquareImg.clone(), objects, classes, confidences);

                    int cntObject = classes.size();//目标个数，需要写入txt

                    string saveImgName = "F:\dmsImg\20190605" + to_string(videoCnt) + "to"+to_string(imgCnt) + ".jpg";

                    if (cntObject > 0) //有目标，保存图片,把图片名和图片中目标个数写入txt
                    {
                        fprintf(f, "%s%d%s%d%s", "20190605", videoCnt, "to", imgCnt, ".jpg"); //图片名写入txt
                        fprintf(f, "%s", "
"); //写入换行
                        fprintf(f, "%d", cntObject);//目标个数写入txt
                        fprintf(f, "%s", "
"); //写入换行

                        imwrite(saveImgName, detectSquareImg);
                    }

                    //检测结果分析
                    for (int i = 0; i < classes.size(); i++)
                    {
                        if (classes[i] == ObjectType::EYE)
                        {
                            //把目标名称、xmin,ymin,xmax,ymax写入txt
                            int x = objects[i].x;
                            int y = objects[i].y;
                            int w = objects[i].width;
                            int h = objects[i].height;

                            fprintf(f, "%s %d %d %d %d", "eye", x, y, w, h);//写入目标名和目标位置
                            fprintf(f, "%s", "
"); //写入换行
                        }

                        if (classes[i] == ObjectType::CLOSED)
                        {
                            //把目标名称、xmin,ymin,xmax,ymax写入txt
                            int x = objects[i].x;
                            int y = objects[i].y;
                            int w = objects[i].width;
                            int h = objects[i].height;

                            fprintf(f, "%s %d %d %d %d", "closed", x, y, w, h);//写入目标名和目标位置
                            fprintf(f, "%s", "
"); //写入换行
                        }

                        if (classes[i] == ObjectType::HAND)
                        {
                            //把目标名称、xmin,ymin,xmax,ymax写入txt
                            int x = objects[i].x;
                            int y = objects[i].y;
                            int w = objects[i].width;
                            int h = objects[i].height;

                            fprintf(f, "%s %d %d %d %d", "hand", x, y, w, h);//写入目标名和目标位置
                            fprintf(f, "%s", "
"); //写入换行
                        }if (classes[i] == ObjectType::MOUTH)
                        {
                            //把目标名称、xmin,ymin,xmax,ymax写入txt
                            int x = objects[i].x;
                            int y = objects[i].y;
                            int w = objects[i].width;
                            int h = objects[i].height;

                            fprintf(f, "%s %d %d %d %d", "mouth", x, y, w, h);//写入目标名和目标位置
                            fprintf(f, "%s", "
"); //写入换行
                        }
                    }
                }
            }
        }
    }

    fclose(f);
    return 0;
}

#!/usr/bin/python
# -*- coding: UTF-8 -*-

import os, h5py, cv2, sys, shutil
import numpy as np
from xml.dom.minidom import Document

rootdir = "F:/zidongbiaozhuSample"
convet2yoloformat = True
convert2vocformat = True
#resized_dim = (48, 48)

# 最小取20大小的脸，并且补齐
minsize2select = 1
usepadding = True



def convertimgset(img_set="train"):
    imgdir = rootdir + "/dmsImg"
    gtfilepath = rootdir + "/dms20190605.txt"

    #imagesdir = rootdir + "/images"
    vocannotationdir = rootdir + "/dmsXml"
    #labelsdir = rootdir + "/labels"

    #if not os.path.exists(imagesdir):
        #os.mkdir(imagesdir)
    #if convet2yoloformat:
        #if not os.path.exists(labelsdir):
            #os.mkdir(labelsdir)
    if convert2vocformat:
        if not os.path.exists(vocannotationdir):
            os.mkdir(vocannotationdir)

    index = 0
    with open(gtfilepath, 'r') as gtfile:
        while (True):  # and len(faces)<10
            filename = gtfile.readline()[:-1]
            if (filename == ""):
                break
            sys.stdout.write("
" + str(index) + ":" + filename + "			")
            sys.stdout.flush()
            imgpath = imgdir + "/" + filename
            img = cv2.imread(imgpath)

            if img is None:
                bboxCnt = int(gtfile.readline())
                for i in range(bboxCnt):
                    line_read = gtfile.readline()
                continue

            if not img.data:
                continue

            #imgheight = img.shape[0]
            #imgwidth = img.shape[1]
            #maxl = max(imgheight, imgwidth)

            #paddingleft = (maxl - imgwidth) >> 1
            #paddingright = (maxl - imgwidth) >> 1
            #paddingbottom = (maxl - imgheight) >> 1
            #paddingtop = (maxl - imgheight) >> 1
            #saveimg = cv2.copyMakeBorder(img, paddingtop, paddingbottom, paddingleft, paddingright, cv2.BORDER_CONSTANT,value=0)
            #showimg = saveimg.copy()

            numbbox = int(gtfile.readline())
            bboxes = []
            bnames=[]
            for i in range(numbbox):
                line_read = gtfile.readline()
                line_cor = line_read.strip().split(" ")
                obj_name = line_cor[0]
                #line = line_cor[1:5]
                line = list(map(int,line_cor[1:5]))

                if (int(line[3]) <= 0 or int(line[2]) <= 0):
                    continue
                #x = int(line[0]) + paddingleft #左上角顶点x
                x = int(line[0])
                #y = int(line[1]) + paddingtop #左上角顶点y
                y = int(line[1])
                #width = int(line[2]) - int(line[0]) + 1 #宽度
                width = int(line[2])
               #height = int(line[3]) - int(line[1])+ 1 #高度
                height = int(line[3])
                bbox = (x, y, width, height)
                #x2 = x + width
                #y2 = y + height
                # face=img[x:x2,y:y2]
                if width >= minsize2select and height >= minsize2select:
                    bboxes.append(bbox)
                    bnames.append(obj_name)
                    #cv2.rectangle(showimg, (x, y), (x2, y2), (0, 255, 0))
                    # maxl=max(width,height)
                    # x3=(int)(x+(width-maxl)*0.5)
                    # y3=(int)(y+(height-maxl)*0.5)
                    # x4=(int)(x3+maxl)
                    # y4=(int)(y3+maxl)
                    # cv2.rectangle(img,(x3,y3),(x4,y4),(255,0,0))
                #else:
                    #cv2.rectangle(showimg, (x, y), (x2, y2), (0, 0, 255))


            #filename = filename.replace("/", "_")
            if len(bboxes) == 0:
                print ("warrning: no face")
                continue

            #cv2.imwrite(imagesdir + "/" + filename, saveimg)

            #if convet2yoloformat:
                #height = saveimg.shape[0]
                #width = saveimg.shape[1]
                #txtpath = labelsdir + "/" + filename
                #txtpath = txtpath[:-3] + "txt"
                #ftxt = open(txtpath, 'w')
                #for i in range(len(bboxes)):
                    #bbox = bboxes[i]
                    #xcenter = (bbox[0] + bbox[2] * 0.5) / width
                    #ycenter = (bbox[1] + bbox[3] * 0.5) / height
                    #wr = bbox[2] * 1.0 / width
                    #hr = bbox[3] * 1.0 / height
                    #txtline = "0 " + str(xcenter) + " " + str(ycenter) + " " + str(wr) + " " + str(hr) + "
"
                    #ftxt.write(txtline)
                #ftxt.close()



            if convert2vocformat:
                xmlpath = vocannotationdir + "/" + filename
                xmlpath = xmlpath[:-3] + "xml"
                doc = Document()
                annotation = doc.createElement('annotation')
                doc.appendChild(annotation)
                folder = doc.createElement('folder')
                folder_name = doc.createTextNode('widerface')
                folder.appendChild(folder_name)
                annotation.appendChild(folder)
                filenamenode = doc.createElement('filename')
                filename_name = doc.createTextNode(filename)
                filenamenode.appendChild(filename_name)
                annotation.appendChild(filenamenode)
                source = doc.createElement('source')
                annotation.appendChild(source)
                database = doc.createElement('database')
                database.appendChild(doc.createTextNode('wider face Database'))
                source.appendChild(database)
                annotation_s = doc.createElement('annotation')
                annotation_s.appendChild(doc.createTextNode('PASCAL VOC2007'))
                source.appendChild(annotation_s)
                image = doc.createElement('image')
                image.appendChild(doc.createTextNode('flickr'))
                source.appendChild(image)
                flickrid = doc.createElement('flickrid')
                flickrid.appendChild(doc.createTextNode('-1'))
                source.appendChild(flickrid)
                owner = doc.createElement('owner')
                annotation.appendChild(owner)
                flickrid_o = doc.createElement('flickrid')
                flickrid_o.appendChild(doc.createTextNode('widerFace'))
                owner.appendChild(flickrid_o)
                name_o = doc.createElement('name')
                name_o.appendChild(doc.createTextNode('widerFace'))
                owner.appendChild(name_o)
                size = doc.createElement('size')
                annotation.appendChild(size)
                width = doc.createElement('width')
                #width.appendChild(doc.createTextNode(str(saveimg.shape[1])))
                width.appendChild(doc.createTextNode(str(img.shape[1])))
                height = doc.createElement('height')
                #height.appendChild(doc.createTextNode(str(saveimg.shape[0])))
                height.appendChild(doc.createTextNode(str(img.shape[0])))
                depth = doc.createElement('depth')
                #depth.appendChild(doc.createTextNode(str(saveimg.shape[2])))
                depth.appendChild(doc.createTextNode(str(img.shape[2])))
                size.appendChild(width)
                size.appendChild(height)
                size.appendChild(depth)
                segmented = doc.createElement('segmented')
                segmented.appendChild(doc.createTextNode('0'))
                annotation.appendChild(segmented)

                for i in range(len(bboxes)):
                    bbox = bboxes[i]
                    objects = doc.createElement('object')
                    annotation.appendChild(objects)
                    object_name = doc.createElement('name')
                    bnames_var = str(bnames[i])

                    object_name.appendChild(doc.createTextNode(bnames_var))
                    objects.appendChild(object_name)
                    pose = doc.createElement('pose')
                    pose.appendChild(doc.createTextNode('Unspecified'))
                    objects.appendChild(pose)
                    truncated = doc.createElement('truncated')
                    truncated.appendChild(doc.createTextNode('1'))
                    objects.appendChild(truncated)
                    difficult = doc.createElement('difficult')
                    difficult.appendChild(doc.createTextNode('0'))
                    objects.appendChild(difficult)
                    bndbox = doc.createElement('bndbox')
                    objects.appendChild(bndbox)
                    xmin = doc.createElement('xmin')
                    xmin.appendChild(doc.createTextNode(str(bbox[0])))
                    bndbox.appendChild(xmin)
                    ymin = doc.createElement('ymin')
                    ymin.appendChild(doc.createTextNode(str(bbox[1])))
                    bndbox.appendChild(ymin)
                    xmax = doc.createElement('xmax')
                    xmax.appendChild(doc.createTextNode(str(bbox[0] + bbox[2])))
                    bndbox.appendChild(xmax)
                    ymax = doc.createElement('ymax')
                    ymax.appendChild(doc.createTextNode(str(bbox[1] + bbox[3])))
                    bndbox.appendChild(ymax)
                f = open(xmlpath, "w")
                f.write(doc.toprettyxml(indent=''))
                f.close()
                # cv2.imshow("img",showimg)
            # cv2.waitKey()
            index = index + 1


def convertdataset():
    img_sets = ["train"]
    for img_set in img_sets:
        convertimgset(img_set)


if __name__ == "__main__":
    convertdataset()