Wider Face 转VOC格式制作LMDB数据集
本帖最后由 Happy清子 于 2019-1-23 18:30 编辑格式太复杂直接转原贴import os,h5py,cv2,sys,shutilimport numpy as npfrom xml.dom.minidom import Documentrootdir="../"convet2yoloformat=Trueconvert2vocformat=Trueresized_dim=(48, 48)
#最小取20大小的脸，并且补齐minsize2select=20usepadding=True
datasetprefix="/home/yanhe/data/widerface"#def gen_hdf5(): imgdir=rootdir+"/WIDER_train/images" gtfilepath=rootdir+"/wider_face_split/wider_face_train_bbx_gt.txt" index =0 with open(gtfilepath,'r') as gtfile: faces=[] labels=[] while(True ):#and len(faces)<10 imgpath=gtfile.readline()[:-1] if(imgpath==""): break; print index,imgpath img=cv2.imread(imgdir+"/"+imgpath) numbbox=int(gtfile.readline()) bbox=[] for i in range(numbbox): line=gtfile.readline() line=line.split() line=line if(int(line)<=0 or int(line)<=0): continue bbox=(int(line),int(line),int(line),int(line)) face=img):int(line)+int(line),int(line):int(line)+int(line)] face=cv2.resize(face, resized_dim) faces.append(face) labels.append(1) cv2.rectangle(img,(int(line),int(line)),(int(line)+int(line),int(line)+int(line)),(255,0,0)) #cv2.imshow("img",img) #cv2.waitKey(1) index=index+1 faces=np.asarray(faces) labels=np.asarray(labels) f=h5py.File('train.h5','w') f['data']=faces.astype(np.float32) f['label']=labels.astype(np.float32) f.close()def viewginhdf5(): f = h5py.File('train.h5','r') f.keys() faces=f['data'][:] for face in faces: face=face.astype(np.uint8) cv2.imshow("img",face) cv2.waitKey(1) f.close()
def convertimgset(img_set="train"): imgdir=rootdir+"/WIDER_"+img_set+"/images" gtfilepath=rootdir+"/wider_face_split/wider_face_"+img_set+"_bbx_gt.txt" imagesdir=rootdir+"/images" vocannotationdir=rootdir+"/Annotations" 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("\r"+str(index)+":"+filename+"\t\t\t") sys.stdout.flush() imgpath=imgdir+"/"+filename img=cv2.imread(imgpath) if not img.data: break; imgheight=img.shape imgwidth=img.shape 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=[] for i in range(numbbox): line=gtfile.readline() line=line.split() line=line if(int(line)<=0 or int(line)<=0): continue x=int(line)+paddingleft y=int(line)+paddingtop width=int(line) height=int(line) bbox=(x,y,width,height) x2=x+width y2=y+height #face=img if width>=minsize2select and height>=minsize2select: bboxes.append(bbox) 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 width=saveimg.shape txtpath=labelsdir+"/"+filename txtpath=txtpath[:-3]+"txt" ftxt=open(txtpath,'w') for i in range(len(bboxes)): bbox=bboxes xcenter=(bbox+bbox*0.5)/width ycenter=(bbox+bbox*0.5)/height wr=bbox*1.0/width hr=bbox*1.0/height txtline="0 "+str(xcenter)+" "+str(ycenter)+" "+str(wr)+" "+str(hr)+"\n" 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('yanyu')) owner.appendChild(flickrid_o) name_o = doc.createElement('name') name_o.appendChild(doc.createTextNode('yanyu')) owner.appendChild(name_o) size = doc.createElement('size') annotation.appendChild(size) width = doc.createElement('width') width.appendChild(doc.createTextNode(str(saveimg.shape))) height = doc.createElement('height') height.appendChild(doc.createTextNode(str(saveimg.shape))) depth = doc.createElement('depth') depth.appendChild(doc.createTextNode(str(saveimg.shape))) 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 objects = doc.createElement('object') annotation.appendChild(objects) object_name = doc.createElement('name') object_name.appendChild(doc.createTextNode('face')) 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))) bndbox.appendChild(xmin) ymin = doc.createElement('ymin') ymin.appendChild(doc.createTextNode(str(bbox))) bndbox.appendChild(ymin) xmax = doc.createElement('xmax') xmax.appendChild(doc.createTextNode(str(bbox+bbox))) bndbox.appendChild(xmax) ymax = doc.createElement('ymax') ymax.appendChild(doc.createTextNode(str(bbox+bbox))) bndbox.appendChild(ymax) f=open(xmlpath,"w") f.write(doc.toprettyxml(indent = '')) f.close() #cv2.imshow("img",showimg) #cv2.waitKey() index=index+1
def generatetxt(img_set="train"): gtfilepath=rootdir+"/wider_face_split/wider_face_"+img_set+"_bbx_gt.txt" f=open(rootdir+"/"+img_set+".txt","w") with open(gtfilepath,'r') as gtfile: while(True ):#and len(faces)<10 filename=gtfile.readline()[:-1] if(filename==""): break; filename=filename.replace("/","_") imgfilepath=datasetprefix+"/images/"+filename f.write(imgfilepath+'\n') numbbox=int(gtfile.readline()) for i in range(numbbox): line=gtfile.readline() f.close()
def generatevocsets(img_set="train"): if not os.path.exists(rootdir+"/ImageSets"): os.mkdir(rootdir+"/ImageSets") if not os.path.exists(rootdir+"/ImageSets/Main"): os.mkdir(rootdir+"/ImageSets/Main") gtfilepath=rootdir+"/wider_face_split/wider_face_"+img_set+"_bbx_gt.txt" f=open(rootdir+"/ImageSets/Main/"+img_set+".txt",'w') with open(gtfilepath,'r') as gtfile: while(True ):#and len(faces)<10 filename=gtfile.readline()[:-1] if(filename==""): break; filename=filename.replace("/","_") imgfilepath=filename[:-4] f.write(imgfilepath+'\n') numbbox=int(gtfile.readline()) for i in range(numbbox): line=gtfile.readline() f.close()
def convertdataset(): img_sets=["train","val"] for img_set in img_sets: convertimgset(img_set) generatetxt(img_set) generatevocsets(img_set)
if __name__=="__main__": convertdataset() shutil.move(rootdir+"/"+"train.txt",rootdir+"/"+"trainval.txt") shutil.move(rootdir+"/"+"val.txt",rootdir+"/"+"test.txt") shutil.move(rootdir+"/ImageSets/Main/"+"train.txt",rootdir+"/ImageSets/Main/"+"trainval.txt") shutil.move(rootdir+"/ImageSets/Main/"+"val.txt",rootdir+"/ImageSets/Main/"+"test.txt")
https://www.cnblogs.com/houjun/p/9833431.html 这个数据集
用的很广泛
voc格式，大家都喜欢，但做数据集的却总想来点不一样的
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