将wierface标注转换为VOC格式

widerface是包含了3万多张总计近40万张人脸的人脸检测库，里面包含了大大小小各式各样的人脸，是不可多得的素材。

请将下面的代码保存至widerface.py，并至于下图所示的eval_tools文件夹下，其他的文件结构一并如图所示。

Update:

由于widerface里包含很多小脸，用SSD训练不一定能收敛，此外SSD要求输入为方形，不然会挤压图片造成变形，因此需要对此做些处理.

[cpp] view plain copy

print ?

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[python] view plain copy

print?

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[python] view plain copy

print ?

1. import os,h5py,cv2,sys,shutil  
2. import numpy as np  
3. from xml.dom.minidom import Document  
4. rootdir=”../”  
5. convet2yoloformat=True  
6. convert2vocformat=True  
7. resized_dim=(48, 48)  
8.   
9. #最小取20大小的脸，并且补齐  
10. minsize2select=20  
11. usepadding=True  
12.   
13. datasetprefix=”/home/yanhe/data/widerface”#  
14. def gen_hdf5():  
15.     imgdir=rootdir+”/WIDER_train/images”  
16.     gtfilepath=rootdir+”/wider_face_split/wider_face_train_bbx_gt.txt”  
17.     index =0  
18.     with open(gtfilepath,’r’) as gtfile:  
19.         faces=[]  
20.         labels=[]  
21.         while(True ):#and len(faces)<10  
22.             imgpath=gtfile.readline()[:-1]  
23.             if(imgpath==”“):  
24.                 break;  
25.             print index,imgpath  
26.             img=cv2.imread(imgdir+”/”+imgpath)  
27.             numbbox=int(gtfile.readline())  
28.             bbox=[]  
29.             for i in range(numbbox):  
30.                 line=gtfile.readline()  
31.                 line=line.split()  
32.                 line=line[0:4]                 
33.                 if(int(line[3])<=0 or int(line[2])<=0):  
34.                     continue  
35.                 bbox=(int(line[0]),int(line[1]),int(line[2]),int(line[3]))  
36.                 face=img[int(line[1]):int(line[1])+int(line[3]),int(line[0]):int(line[0])+int(line[2])]  
37.                 face=cv2.resize(face, resized_dim)  
38.                 faces.append(face)  
39.                 labels.append(1)  
40.                 cv2.rectangle(img,(int(line[0]),int(line[1])),(int(line[0])+int(line[2]),int(line[1])+int(line[3])),(255,0,0))  
41.             #cv2.imshow(“img”,img)  
42.             #cv2.waitKey(1)  
43.             index=index+1  
44.         faces=np.asarray(faces)  
45.         labels=np.asarray(labels)  
46.         f=h5py.File(’train.h5’,‘w’)  
47.         f[’data’]=faces.astype(np.float32)  
48.         f[’label’]=labels.astype(np.float32)  
49.         f.close()  
50. def viewginhdf5():  
51.     f = h5py.File(’train.h5’,‘r’)   
52.     f.keys()  
53.     faces=f[’data’][:]  
54.     for face in faces:  
55.         face=face.astype(np.uint8)  
56.         cv2.imshow(”img”,face)  
57.         cv2.waitKey(1)  
58.     f.close()  
59.   
60. def convertimgset(img_set=“train”):  
61.     imgdir=rootdir+”/WIDER_”+img_set+“/images”  
62.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
63.     imagesdir=rootdir+”/images”  
64.     vocannotationdir=rootdir+”/Annotations”  
65.     labelsdir=rootdir+”/labels”  
66.     if not os.path.exists(imagesdir):  
67.         os.mkdir(imagesdir)  
68.     if convet2yoloformat:  
69.         if not os.path.exists(labelsdir):  
70.             os.mkdir(labelsdir)  
71.     if convert2vocformat:  
72.         if not os.path.exists(vocannotationdir):  
73.             os.mkdir(vocannotationdir)  
74.     index=0  
75.     with open(gtfilepath,’r’) as gtfile:  
76.         while(True ):#and len(faces)<10  
77.             filename=gtfile.readline()[:-1]  
78.             if(filename==”“):  
79.                 break;  
80.             sys.stdout.write(”\r”+str(index)+“:”+filename+“\t\t\t”)  
81.             sys.stdout.flush()  
82.             imgpath=imgdir+”/”+filename  
83.             img=cv2.imread(imgpath)  
84.             if not img.data:  
85.                 break;  
86.             imgheight=img.shape[0]  
87.             imgwidth=img.shape[1]  
88.             maxl=max(imgheight,imgwidth)  
89.             paddingleft=(maxl-imgwidth)>>1  
90.             paddingright=(maxl-imgwidth)>>1  
91.             paddingbottom=(maxl-imgheight)>>1  
92.             paddingtop=(maxl-imgheight)>>1  
93.             saveimg=cv2.copyMakeBorder(img,paddingtop,paddingbottom,paddingleft,paddingright,cv2.BORDER_CONSTANT,value=0)  
94.             showimg=saveimg.copy()  
95.             numbbox=int(gtfile.readline())  
96.             bboxes=[]  
97.             for i in range(numbbox):  
98.                 line=gtfile.readline()  
99.                 line=line.split()  
100.                 line=line[0:4]                 
101.                 if(int(line[3])<=0 or int(line[2])<=0):  
102.                     continue  
103.                 x=int(line[0])+paddingleft  
104.                 y=int(line[1])+paddingtop  
105.                 width=int(line[2])  
106.                 height=int(line[3])  
107.                 bbox=(x,y,width,height)  
108.                 x2=x+width  
109.                 y2=y+height  
110.                 #face=img[x:x2,y:y2]  
111.                 if width>=minsize2select and height>=minsize2select:  
112.                     bboxes.append(bbox)  
113.                     cv2.rectangle(showimg,(x,y),(x2,y2),(0,255,0))  
114.                     #maxl=max(width,height)  
115.                     #x3=(int)(x+(width-maxl)*0.5)  
116.                     #y3=(int)(y+(height-maxl)*0.5)  
117.                     #x4=(int)(x3+maxl)  
118.                     #y4=(int)(y3+maxl)  
119.                     #cv2.rectangle(img,(x3,y3),(x4,y4),(255,0,0))  
120.                 else:  
121.                     cv2.rectangle(showimg,(x,y),(x2,y2),(0,0,255))                
122.             filename=filename.replace(”/”,“_”)  
123.             if len(bboxes)==0:  
124.                 print “warrning: no face”  
125.                 continue   
126.             cv2.imwrite(imagesdir+”/”+filename,saveimg)  
127.             if convet2yoloformat:  
128.                 height=saveimg.shape[0]  
129.                 width=saveimg.shape[1]  
130.                 txtpath=labelsdir+”/”+filename  
131.                 txtpath=txtpath[:-3]+“txt”  
132.                 ftxt=open(txtpath,’w’)    
133.                 for i in range(len(bboxes)):  
134.                     bbox=bboxes[i]  
135.                     xcenter=(bbox[0]+bbox[2]*0.5)/width  
136.                     ycenter=(bbox[1]+bbox[3]*0.5)/height  
137.                     wr=bbox[2]*1.0/width  
138.                     hr=bbox[3]*1.0/height  
139.                     txtline=”0 ”+str(xcenter)+“ ”+str(ycenter)+“ ”+str(wr)+“ ”+str(hr)+“\n”  
140.                     ftxt.write(txtline)  
141.                 ftxt.close()  
142.             if convert2vocformat:  
143.                 xmlpath=vocannotationdir+”/”+filename  
144.                 xmlpath=xmlpath[:-3]+“xml”  
145.                 doc = Document()  
146.                 annotation = doc.createElement(’annotation’)  
147.                 doc.appendChild(annotation)  
148.                 folder = doc.createElement(’folder’)  
149.                 folder_name = doc.createTextNode(’widerface’)  
150.                 folder.appendChild(folder_name)  
151.                 annotation.appendChild(folder)  
152.                 filenamenode = doc.createElement(’filename’)  
153.                 filename_name = doc.createTextNode(filename)  
154.                 filenamenode.appendChild(filename_name)  
155.                 annotation.appendChild(filenamenode)  
156.                 source = doc.createElement(’source’)  
157.                 annotation.appendChild(source)  
158.                 database = doc.createElement(’database’)  
159.                 database.appendChild(doc.createTextNode(’wider face Database’))  
160.                 source.appendChild(database)  
161.                 annotation_s = doc.createElement(’annotation’)  
162.                 annotation_s.appendChild(doc.createTextNode(’PASCAL VOC2007’))  
163.                 source.appendChild(annotation_s)  
164.                 image = doc.createElement(’image’)  
165.                 image.appendChild(doc.createTextNode(’flickr’))  
166.                 source.appendChild(image)  
167.                 flickrid = doc.createElement(’flickrid’)  
168.                 flickrid.appendChild(doc.createTextNode(’-1’))  
169.                 source.appendChild(flickrid)  
170.                 owner = doc.createElement(’owner’)  
171.                 annotation.appendChild(owner)  
172.                 flickrid_o = doc.createElement(’flickrid’)  
173.                 flickrid_o.appendChild(doc.createTextNode(’yanyu’))  
174.                 owner.appendChild(flickrid_o)  
175.                 name_o = doc.createElement(’name’)  
176.                 name_o.appendChild(doc.createTextNode(’yanyu’))  
177.                 owner.appendChild(name_o)  
178.                 size = doc.createElement(’size’)  
179.                 annotation.appendChild(size)  
180.                 width = doc.createElement(’width’)  
181.                 width.appendChild(doc.createTextNode(str(saveimg.shape[1])))  
182.                 height = doc.createElement(’height’)  
183.                 height.appendChild(doc.createTextNode(str(saveimg.shape[0])))  
184.                 depth = doc.createElement(’depth’)  
185.                 depth.appendChild(doc.createTextNode(str(saveimg.shape[2])))  
186.                 size.appendChild(width)  
187.                 size.appendChild(height)  
188.                 size.appendChild(depth)  
189.                 segmented = doc.createElement(’segmented’)  
190.                 segmented.appendChild(doc.createTextNode(’0’))  
191.                 annotation.appendChild(segmented)  
192.                 for i in range(len(bboxes)):  
193.                     bbox=bboxes[i]  
194.                     objects = doc.createElement(’object’)  
195.                     annotation.appendChild(objects)  
196.                     object_name = doc.createElement(’name’)  
197.                     object_name.appendChild(doc.createTextNode(’face’))  
198.                     objects.appendChild(object_name)  
199.                     pose = doc.createElement(’pose’)  
200.                     pose.appendChild(doc.createTextNode(’Unspecified’))  
201.                     objects.appendChild(pose)  
202.                     truncated = doc.createElement(’truncated’)  
203.                     truncated.appendChild(doc.createTextNode(’1’))  
204.                     objects.appendChild(truncated)  
205.                     difficult = doc.createElement(’difficult’)  
206.                     difficult.appendChild(doc.createTextNode(’0’))  
207.                     objects.appendChild(difficult)  
208.                     bndbox = doc.createElement(’bndbox’)  
209.                     objects.appendChild(bndbox)  
210.                     xmin = doc.createElement(’xmin’)  
211.                     xmin.appendChild(doc.createTextNode(str(bbox[0])))  
212.                     bndbox.appendChild(xmin)  
213.                     ymin = doc.createElement(’ymin’)  
214.                     ymin.appendChild(doc.createTextNode(str(bbox[1])))  
215.                     bndbox.appendChild(ymin)  
216.                     xmax = doc.createElement(’xmax’)  
217.                     xmax.appendChild(doc.createTextNode(str(bbox[0]+bbox[2])))  
218.                     bndbox.appendChild(xmax)  
219.                     ymax = doc.createElement(’ymax’)  
220.                     ymax.appendChild(doc.createTextNode(str(bbox[1]+bbox[3])))  
221.                     bndbox.appendChild(ymax)  
222.                 f=open(xmlpath,”w”)  
223.                 f.write(doc.toprettyxml(indent = ”))  
224.                 f.close()       
225.             #cv2.imshow(“img”,showimg)  
226.             #cv2.waitKey()  
227.             index=index+1  
228.   
229. def generatetxt(img_set=“train”):  
230.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
231.     f=open(rootdir+”/”+img_set+“.txt”,“w”)  
232.     with open(gtfilepath,’r’) as gtfile:  
233.         while(True ):#and len(faces)<10  
234.             filename=gtfile.readline()[:-1]  
235.             if(filename==”“):  
236.                 break;  
237.             filename=filename.replace(”/”,“_”)  
238.             imgfilepath=datasetprefix+”/images/”+filename  
239.             f.write(imgfilepath+’\n’)  
240.             numbbox=int(gtfile.readline())  
241.             for i in range(numbbox):  
242.                 line=gtfile.readline()  
243.     f.close()  
244.   
245. def generatevocsets(img_set=“train”):  
246.     if not os.path.exists(rootdir+“/ImageSets”):  
247.         os.mkdir(rootdir+”/ImageSets”)  
248.     if not os.path.exists(rootdir+“/ImageSets/Main”):  
249.         os.mkdir(rootdir+”/ImageSets/Main”)  
250.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
251.     f=open(rootdir+”/ImageSets/Main/”+img_set+“.txt”,‘w’)  
252.     with open(gtfilepath,’r’) as gtfile:  
253.         while(True ):#and len(faces)<10  
254.             filename=gtfile.readline()[:-1]  
255.             if(filename==”“):  
256.                 break;  
257.             filename=filename.replace(”/”,“_”)  
258.             imgfilepath=filename[:-4]  
259.             f.write(imgfilepath+’\n’)  
260.             numbbox=int(gtfile.readline())  
261.             for i in range(numbbox):  
262.                 line=gtfile.readline()  
263.     f.close()  
264.   
265. def convertdataset():  
266.     img_sets=[”train”,“val”]  
267.     for img_set in img_sets:  
268.         convertimgset(img_set)  
269.         generatetxt(img_set)  
270.         generatevocsets(img_set)  
271.   
272. if __name__==“__main__”:  
273.     convertdataset()  
274.     shutil.move(rootdir+”/”+“train.txt”,rootdir+“/”+“trainval.txt”)  
275.     shutil.move(rootdir+”/”+“val.txt”,rootdir+“/”+“test.txt”)  
276.     shutil.move(rootdir+”/ImageSets/Main/”+“train.txt”,rootdir+“/ImageSets/Main/”+“trainval.txt”)  
277.     shutil.move(rootdir+”/ImageSets/Main/”+“val.txt”,rootdir+“/ImageSets/Main/”+“test.txt”)  

import os,h5py,cv2,sys,shutil
import numpy as np
from xml.dom.minidom import Document
rootdir="../"
convet2yoloformat=True
convert2vocformat=True
resized_dim=(48, 48)

最小取20大小的脸，并且补齐

minsize2select=20
usepadding=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[0:4]
if(int(line[3])<=0 or int(line[2])<=0):
continue
bbox=(int(line[0]),int(line[1]),int(line[2]),int(line[3]))
face=img[int(line[1]):int(line[1])+int(line[3]),int(line[0]):int(line[0])+int(line[2])]
face=cv2.resize(face, resized_dim)
faces.append(face)
labels.append(1)
cv2.rectangle(img,(int(line[0]),int(line[1])),(int(line[0])+int(line[2]),int(line[1])+int(line[3])),(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[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=[]
for i in range(numbbox):
line=gtfile.readline()
line=line.split()
line=line[0:4]
if(int(line[3])<=0 or int(line[2])<=0):
continue
x=int(line[0])+paddingleft
y=int(line[1])+paddingtop
width=int(line[2])
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)
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)+"\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[1])))
height = doc.createElement('height')
height.appendChild(doc.createTextNode(str(saveimg.shape[0])))
depth = doc.createElement('depth')
depth.appendChild(doc.createTextNode(str(saveimg.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')
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[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 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)

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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")

如果没有时间自己转换，也可以下载已经转换好的文件，百度网盘，密码：t46t

widerface是包含了3万多张总计近40万张人脸的人脸检测库，里面包含了大大小小各式各样的人脸，是不可多得的素材。

请将下面的代码保存至widerface.py，并至于下图所示的eval_tools文件夹下，其他的文件结构一并如图所示。

Update:

由于widerface里包含很多小脸，用SSD训练不一定能收敛，此外SSD要求输入为方形，不然会挤压图片造成变形，因此需要对此做些处理.

[cpp] view plain copy

print ?

1.   

[python] view plain copy

print?

1.   

[python] view plain copy

print ?

1. import os,h5py,cv2,sys,shutil  
2. import numpy as np  
3. from xml.dom.minidom import Document  
4. rootdir=”../”  
5. convet2yoloformat=True  
6. convert2vocformat=True  
7. resized_dim=(48, 48)  
8.   
9. #最小取20大小的脸，并且补齐  
10. minsize2select=20  
11. usepadding=True  
12.   
13. datasetprefix=”/home/yanhe/data/widerface”#  
14. def gen_hdf5():  
15.     imgdir=rootdir+”/WIDER_train/images”  
16.     gtfilepath=rootdir+”/wider_face_split/wider_face_train_bbx_gt.txt”  
17.     index =0  
18.     with open(gtfilepath,’r’) as gtfile:  
19.         faces=[]  
20.         labels=[]  
21.         while(True ):#and len(faces)<10  
22.             imgpath=gtfile.readline()[:-1]  
23.             if(imgpath==”“):  
24.                 break;  
25.             print index,imgpath  
26.             img=cv2.imread(imgdir+”/”+imgpath)  
27.             numbbox=int(gtfile.readline())  
28.             bbox=[]  
29.             for i in range(numbbox):  
30.                 line=gtfile.readline()  
31.                 line=line.split()  
32.                 line=line[0:4]                 
33.                 if(int(line[3])<=0 or int(line[2])<=0):  
34.                     continue  
35.                 bbox=(int(line[0]),int(line[1]),int(line[2]),int(line[3]))  
36.                 face=img[int(line[1]):int(line[1])+int(line[3]),int(line[0]):int(line[0])+int(line[2])]  
37.                 face=cv2.resize(face, resized_dim)  
38.                 faces.append(face)  
39.                 labels.append(1)  
40.                 cv2.rectangle(img,(int(line[0]),int(line[1])),(int(line[0])+int(line[2]),int(line[1])+int(line[3])),(255,0,0))  
41.             #cv2.imshow(“img”,img)  
42.             #cv2.waitKey(1)  
43.             index=index+1  
44.         faces=np.asarray(faces)  
45.         labels=np.asarray(labels)  
46.         f=h5py.File(’train.h5’,‘w’)  
47.         f[’data’]=faces.astype(np.float32)  
48.         f[’label’]=labels.astype(np.float32)  
49.         f.close()  
50. def viewginhdf5():  
51.     f = h5py.File(’train.h5’,‘r’)   
52.     f.keys()  
53.     faces=f[’data’][:]  
54.     for face in faces:  
55.         face=face.astype(np.uint8)  
56.         cv2.imshow(”img”,face)  
57.         cv2.waitKey(1)  
58.     f.close()  
59.   
60. def convertimgset(img_set=“train”):  
61.     imgdir=rootdir+”/WIDER_”+img_set+“/images”  
62.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
63.     imagesdir=rootdir+”/images”  
64.     vocannotationdir=rootdir+”/Annotations”  
65.     labelsdir=rootdir+”/labels”  
66.     if not os.path.exists(imagesdir):  
67.         os.mkdir(imagesdir)  
68.     if convet2yoloformat:  
69.         if not os.path.exists(labelsdir):  
70.             os.mkdir(labelsdir)  
71.     if convert2vocformat:  
72.         if not os.path.exists(vocannotationdir):  
73.             os.mkdir(vocannotationdir)  
74.     index=0  
75.     with open(gtfilepath,’r’) as gtfile:  
76.         while(True ):#and len(faces)<10  
77.             filename=gtfile.readline()[:-1]  
78.             if(filename==”“):  
79.                 break;  
80.             sys.stdout.write(”\r”+str(index)+“:”+filename+“\t\t\t”)  
81.             sys.stdout.flush()  
82.             imgpath=imgdir+”/”+filename  
83.             img=cv2.imread(imgpath)  
84.             if not img.data:  
85.                 break;  
86.             imgheight=img.shape[0]  
87.             imgwidth=img.shape[1]  
88.             maxl=max(imgheight,imgwidth)  
89.             paddingleft=(maxl-imgwidth)>>1  
90.             paddingright=(maxl-imgwidth)>>1  
91.             paddingbottom=(maxl-imgheight)>>1  
92.             paddingtop=(maxl-imgheight)>>1  
93.             saveimg=cv2.copyMakeBorder(img,paddingtop,paddingbottom,paddingleft,paddingright,cv2.BORDER_CONSTANT,value=0)  
94.             showimg=saveimg.copy()  
95.             numbbox=int(gtfile.readline())  
96.             bboxes=[]  
97.             for i in range(numbbox):  
98.                 line=gtfile.readline()  
99.                 line=line.split()  
100.                 line=line[0:4]                 
101.                 if(int(line[3])<=0 or int(line[2])<=0):  
102.                     continue  
103.                 x=int(line[0])+paddingleft  
104.                 y=int(line[1])+paddingtop  
105.                 width=int(line[2])  
106.                 height=int(line[3])  
107.                 bbox=(x,y,width,height)  
108.                 x2=x+width  
109.                 y2=y+height  
110.                 #face=img[x:x2,y:y2]  
111.                 if width>=minsize2select and height>=minsize2select:  
112.                     bboxes.append(bbox)  
113.                     cv2.rectangle(showimg,(x,y),(x2,y2),(0,255,0))  
114.                     #maxl=max(width,height)  
115.                     #x3=(int)(x+(width-maxl)*0.5)  
116.                     #y3=(int)(y+(height-maxl)*0.5)  
117.                     #x4=(int)(x3+maxl)  
118.                     #y4=(int)(y3+maxl)  
119.                     #cv2.rectangle(img,(x3,y3),(x4,y4),(255,0,0))  
120.                 else:  
121.                     cv2.rectangle(showimg,(x,y),(x2,y2),(0,0,255))                
122.             filename=filename.replace(”/”,“_”)  
123.             if len(bboxes)==0:  
124.                 print “warrning: no face”  
125.                 continue   
126.             cv2.imwrite(imagesdir+”/”+filename,saveimg)  
127.             if convet2yoloformat:  
128.                 height=saveimg.shape[0]  
129.                 width=saveimg.shape[1]  
130.                 txtpath=labelsdir+”/”+filename  
131.                 txtpath=txtpath[:-3]+“txt”  
132.                 ftxt=open(txtpath,’w’)    
133.                 for i in range(len(bboxes)):  
134.                     bbox=bboxes[i]  
135.                     xcenter=(bbox[0]+bbox[2]*0.5)/width  
136.                     ycenter=(bbox[1]+bbox[3]*0.5)/height  
137.                     wr=bbox[2]*1.0/width  
138.                     hr=bbox[3]*1.0/height  
139.                     txtline=”0 ”+str(xcenter)+“ ”+str(ycenter)+“ ”+str(wr)+“ ”+str(hr)+“\n”  
140.                     ftxt.write(txtline)  
141.                 ftxt.close()  
142.             if convert2vocformat:  
143.                 xmlpath=vocannotationdir+”/”+filename  
144.                 xmlpath=xmlpath[:-3]+“xml”  
145.                 doc = Document()  
146.                 annotation = doc.createElement(’annotation’)  
147.                 doc.appendChild(annotation)  
148.                 folder = doc.createElement(’folder’)  
149.                 folder_name = doc.createTextNode(’widerface’)  
150.                 folder.appendChild(folder_name)  
151.                 annotation.appendChild(folder)  
152.                 filenamenode = doc.createElement(’filename’)  
153.                 filename_name = doc.createTextNode(filename)  
154.                 filenamenode.appendChild(filename_name)  
155.                 annotation.appendChild(filenamenode)  
156.                 source = doc.createElement(’source’)  
157.                 annotation.appendChild(source)  
158.                 database = doc.createElement(’database’)  
159.                 database.appendChild(doc.createTextNode(’wider face Database’))  
160.                 source.appendChild(database)  
161.                 annotation_s = doc.createElement(’annotation’)  
162.                 annotation_s.appendChild(doc.createTextNode(’PASCAL VOC2007’))  
163.                 source.appendChild(annotation_s)  
164.                 image = doc.createElement(’image’)  
165.                 image.appendChild(doc.createTextNode(’flickr’))  
166.                 source.appendChild(image)  
167.                 flickrid = doc.createElement(’flickrid’)  
168.                 flickrid.appendChild(doc.createTextNode(’-1’))  
169.                 source.appendChild(flickrid)  
170.                 owner = doc.createElement(’owner’)  
171.                 annotation.appendChild(owner)  
172.                 flickrid_o = doc.createElement(’flickrid’)  
173.                 flickrid_o.appendChild(doc.createTextNode(’yanyu’))  
174.                 owner.appendChild(flickrid_o)  
175.                 name_o = doc.createElement(’name’)  
176.                 name_o.appendChild(doc.createTextNode(’yanyu’))  
177.                 owner.appendChild(name_o)  
178.                 size = doc.createElement(’size’)  
179.                 annotation.appendChild(size)  
180.                 width = doc.createElement(’width’)  
181.                 width.appendChild(doc.createTextNode(str(saveimg.shape[1])))  
182.                 height = doc.createElement(’height’)  
183.                 height.appendChild(doc.createTextNode(str(saveimg.shape[0])))  
184.                 depth = doc.createElement(’depth’)  
185.                 depth.appendChild(doc.createTextNode(str(saveimg.shape[2])))  
186.                 size.appendChild(width)  
187.                 size.appendChild(height)  
188.                 size.appendChild(depth)  
189.                 segmented = doc.createElement(’segmented’)  
190.                 segmented.appendChild(doc.createTextNode(’0’))  
191.                 annotation.appendChild(segmented)  
192.                 for i in range(len(bboxes)):  
193.                     bbox=bboxes[i]  
194.                     objects = doc.createElement(’object’)  
195.                     annotation.appendChild(objects)  
196.                     object_name = doc.createElement(’name’)  
197.                     object_name.appendChild(doc.createTextNode(’face’))  
198.                     objects.appendChild(object_name)  
199.                     pose = doc.createElement(’pose’)  
200.                     pose.appendChild(doc.createTextNode(’Unspecified’))  
201.                     objects.appendChild(pose)  
202.                     truncated = doc.createElement(’truncated’)  
203.                     truncated.appendChild(doc.createTextNode(’1’))  
204.                     objects.appendChild(truncated)  
205.                     difficult = doc.createElement(’difficult’)  
206.                     difficult.appendChild(doc.createTextNode(’0’))  
207.                     objects.appendChild(difficult)  
208.                     bndbox = doc.createElement(’bndbox’)  
209.                     objects.appendChild(bndbox)  
210.                     xmin = doc.createElement(’xmin’)  
211.                     xmin.appendChild(doc.createTextNode(str(bbox[0])))  
212.                     bndbox.appendChild(xmin)  
213.                     ymin = doc.createElement(’ymin’)  
214.                     ymin.appendChild(doc.createTextNode(str(bbox[1])))  
215.                     bndbox.appendChild(ymin)  
216.                     xmax = doc.createElement(’xmax’)  
217.                     xmax.appendChild(doc.createTextNode(str(bbox[0]+bbox[2])))  
218.                     bndbox.appendChild(xmax)  
219.                     ymax = doc.createElement(’ymax’)  
220.                     ymax.appendChild(doc.createTextNode(str(bbox[1]+bbox[3])))  
221.                     bndbox.appendChild(ymax)  
222.                 f=open(xmlpath,”w”)  
223.                 f.write(doc.toprettyxml(indent = ”))  
224.                 f.close()       
225.             #cv2.imshow(“img”,showimg)  
226.             #cv2.waitKey()  
227.             index=index+1  
228.   
229. def generatetxt(img_set=“train”):  
230.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
231.     f=open(rootdir+”/”+img_set+“.txt”,“w”)  
232.     with open(gtfilepath,’r’) as gtfile:  
233.         while(True ):#and len(faces)<10  
234.             filename=gtfile.readline()[:-1]  
235.             if(filename==”“):  
236.                 break;  
237.             filename=filename.replace(”/”,“_”)  
238.             imgfilepath=datasetprefix+”/images/”+filename  
239.             f.write(imgfilepath+’\n’)  
240.             numbbox=int(gtfile.readline())  
241.             for i in range(numbbox):  
242.                 line=gtfile.readline()  
243.     f.close()  
244.   
245. def generatevocsets(img_set=“train”):  
246.     if not os.path.exists(rootdir+“/ImageSets”):  
247.         os.mkdir(rootdir+”/ImageSets”)  
248.     if not os.path.exists(rootdir+“/ImageSets/Main”):  
249.         os.mkdir(rootdir+”/ImageSets/Main”)  
250.     gtfilepath=rootdir+”/wider_face_split/wider_face_”+img_set+“_bbx_gt.txt”  
251.     f=open(rootdir+”/ImageSets/Main/”+img_set+“.txt”,‘w’)  
252.     with open(gtfilepath,’r’) as gtfile:  
253.         while(True ):#and len(faces)<10  
254.             filename=gtfile.readline()[:-1]  
255.             if(filename==”“):  
256.                 break;  
257.             filename=filename.replace(”/”,“_”)  
258.             imgfilepath=filename[:-4]  
259.             f.write(imgfilepath+’\n’)  
260.             numbbox=int(gtfile.readline())  
261.             for i in range(numbbox):  
262.                 line=gtfile.readline()  
263.     f.close()  
264.   
265. def convertdataset():  
266.     img_sets=[”train”,“val”]  
267.     for img_set in img_sets:  
268.         convertimgset(img_set)  
269.         generatetxt(img_set)  
270.         generatevocsets(img_set)  
271.   
272. if __name__==“__main__”:  
273.     convertdataset()  
274.     shutil.move(rootdir+”/”+“train.txt”,rootdir+“/”+“trainval.txt”)  
275.     shutil.move(rootdir+”/”+“val.txt”,rootdir+“/”+“test.txt”)  
276.     shutil.move(rootdir+”/ImageSets/Main/”+“train.txt”,rootdir+“/ImageSets/Main/”+“trainval.txt”)  
277.     shutil.move(rootdir+”/ImageSets/Main/”+“val.txt”,rootdir+“/ImageSets/Main/”+“test.txt”)  

import os,h5py,cv2,sys,shutil
import numpy as np
from xml.dom.minidom import Document
rootdir="../"
convet2yoloformat=True
convert2vocformat=True
resized_dim=(48, 48)