def test(ImagePath,savePathAligned,savePathCroped,fileformat=['png','jpg'],tag_recover=False,savesize=[64,64]):
'''
必须提供的参数：
1，@ImagePath：待检测和对齐的图像路径
2，@savePathAligned：保存对齐后的人脸文件夹路径
3，@savePathCroped：保存对齐后专注五官的人脸文件夹路径
可选的参数（有默认值）：
4，@fileformat：图像的格式列表，默认为png和jpg格式
5，@tag_recover: 是否先裁剪处人脸图像之后再做归一化，默认为False
6, @savesize: 检测后保留的人脸图像的大小，当tag_recover=True 的时候，才会生效，默认大小为64*64
'''
if not os.path.exists(savePathAligned):
os.makedirs(savePathAligned)
if not os.path.exists(savePathCroped):
os.makedirs(savePathCroped)
AB5plist='./Output/CASIA_imglist_5p.txt'
RE5plist='./Output/CASIA_imglist_5p_Relative.txt'
textutil.replace_file(AB5plist,RE5plist,ImagePath)
#five point file's absolute path and relative path
count=textutil.count_text_line(AB5plist)
print 'There are '+str(count)+' pictures.'
print 'Begin Alignment Face.'
aligment.align_all(RE5plist,ImagePath,savePathAligned)
print 'Done Alignment Face.'
print 'Begin Face croped in.'
facecrop.face_crop_in(savePathAligned,savePathCroped,RE5plist,savesize[0],savesize[1])
print 'Done Face croped in.'
print 'All work is done!'
def test(ImagePath,
savePathDetect,
savePathAligned,
savePathCroped,
fileformat=['png', 'jpg'],
tag_recover=False,
savesize=[128, 128]):
'''
必须提供的参数：
1，@ImagePath：待检测和对齐的图像路径
2，@savePathDetect：保存检测到的人脸的文件夹路径
3，@savePathAligned：保存对其后的人脸文件夹路径
可选的参数（有默认值）：
4，@fileformat：图像的格式列表，默认为png和jpg格式
5，@tag_recover: 是否先裁剪处人脸图像之后再做归一化，默认为False
6, @savesize: 检测后保留的人脸图像的大小，当tag_recover=True 的时候，才会生效，默认大小为64*64
'''
if not os.path.exists(savePathDetect):
os.makedirs(savePathDetect)
if not os.path.exists(savePathAligned):
os.makedirs(savePathAligned)
if not os.path.exists(savePathCroped):
os.makedirs(savePathCroped)
print 'Begin making filelist. step (1/6) '
#创建imagelist.list 文件，用来保存文件图像文件列表
imagelist = './Output/imagelist.list'
fid = open(imagelist, 'w')
makeimagelist.makeImageFileList(ImagePath, fid, fileformat)
fid.close()
#统计有多少个图像文件
count = textutil.count_text_line(imagelist)
textutil.insertLine(imagelist, 1, str(count))
print 'Done make file list. step(1/6)'
#人脸检测，生成imageBbox.list 文件，
print 'Begin Face Detection task. step(2/6)'
bboxlist = './Output/imagebbox.list'
os.system('FaceDetect.exe data ' + imagelist + ' ' + bboxlist)
print 'Done Face Detection task.step(2/6)'
#清除检测不到的图像，或者检测到多个的文件，以便于后面的人脸关键点检测。
print 'Begin Box file Clean and Replace. step(3/6)'
detectlist = './Output/imagebbox_detect.list'
misslist = './Output/imagebbox_miss.list'
textutil.cleanbox(fileinput=bboxlist,
detectlistfile=detectlist,
misslistfile=misslist)
replacelist = './Output/imagebbox_detect_replace.list'
textutil.replace_file(detectlist, replacelist, ImagePath)
print 'Done Box file Clean and Replace. step(3/6)'
if tag_recover == True:
#人脸先裁剪
# 保留检测到的人脸图像，可选，
print 'Begin Save Detected Face Image. step(4/4) optional'
facecrop.face_cropout(ImagePath,
savePathDetect,
replacelist,
w=savesize[0],
h=savesize[1])
print 'Done Save Detected Face Image. step(4/4) optional'
ImagePath = savePathDetect
print 'Begin making filelist. step (1/6) '
#创建imagelist.list 文件，用来保存文件图像文件列表
imagelist = './Output/imagelist_recover.list'
fid = open(imagelist, 'w')
makeimagelist.makeImageFileList(ImagePath, fid, fileformat)
fid.close()
#统计有多少个图像文件
count = textutil.count_text_line(imagelist)
textutil.insertLine(imagelist, 1, str(count))
print 'Done make file list. step(1/6)'
#人脸检测，生成imageBbox.list 文件，
print 'Begin Face Detection task. step(2/6)'
bboxlist = './Output/imagebbox__recover.list'
os.system('FaceDetect.exe data ' + imagelist + ' ' + bboxlist)
print 'Done Face Detection task.step(2/6)'
#清除检测不到的图像，或者检测到多个的文件，以便于后面的人脸关键点检测。
print 'Begin Box file Clean and Replace. step(3/6)'
detectlist = './Output/imagebbox_recover_detect.list'
misslist = './Output/imagebbox_recover_miss.list'
textutil.cleanbox(fileinput=bboxlist,
detectlistfile=detectlist,
misslistfile=misslist)
replacelist = './Output/imagebbox_detect_recover_replace.list'
textutil.replace_file(detectlist, replacelist, ImagePath)
print 'Done Box file Clean and Replace. step(3/6)'
#人脸关键点检测
print 'Begin Face Point Detection. step(4/6)'
resultpath = './Output/result.bin'
command_ = 'FacePointDetect.exe ' + replacelist + ' ' + ImagePath + ' Input ' + resultpath
os.system(command_)
print 'Done Face Point Detection. step(4/6)'
print 'Begin write Points files. step(5/6)'
points = textutil.take_out_point(resultpath)
imagepointlist = './Output/imagelist_point.list'
textutil.writePoint2File(replacelist, imagepointlist, points)
print 'Done write Points files. step(5/6)'
print 'Begin Alignment Face. step(6/6)'
aligment.align_all(imagepointlist, ImagePath, savePathAligned)
print 'Done Alignment Face. step(6/6)'
print 'Begin Face croped in'
facecrop.face_crop_in(savePathAligned, savePathCroped, replacelist,
savesize[0], savesize[1])
print 'Done Face croped in '
print 'All work is done!'
def test(ImagePath,savePathDetect,savePathAligned,savePathCroped,fileformat=['png','jpg'],tag_recover=False,savesize=[128,128]):
'''
必须提供的参数：
1，@ImagePath：待检测和对齐的图像路径
2，@savePathDetect：保存检测到的人脸的文件夹路径
3，@savePathAligned：保存对其后的人脸文件夹路径
可选的参数（有默认值）：
4，@fileformat：图像的格式列表，默认为png和jpg格式
5，@tag_recover: 是否先裁剪处人脸图像之后再做归一化，默认为False
6, @savesize: 检测后保留的人脸图像的大小，当tag_recover=True 的时候，才会生效，默认大小为64*64
'''
if not os.path.exists(savePathDetect):
os.makedirs(savePathDetect)
if not os.path.exists(savePathAligned):
os.makedirs(savePathAligned)
if not os.path.exists(savePathCroped):
os.makedirs(savePathCroped)
print 'Begin making filelist. step (1/6) '
#创建imagelist.list 文件，用来保存文件图像文件列表
imagelist = './Output/imagelist.list'
fid=open(imagelist,'w')
makeimagelist.makeImageFileList(ImagePath,fid,fileformat)
fid.close()
#统计有多少个图像文件
count=textutil.count_text_line(imagelist)
textutil.insertLine(imagelist,1,str(count))
print 'Done make file list. step(1/6)'
#人脸检测，生成imageBbox.list 文件，
print 'Begin Face Detection task. step(2/6)'
bboxlist='./Output/imagebbox.list'
os.system('FaceDetect.exe data '+imagelist+' '+bboxlist)
print 'Done Face Detection task.step(2/6)'
#清除检测不到的图像，或者检测到多个的文件，以便于后面的人脸关键点检测。
print 'Begin Box file Clean and Replace. step(3/6)'
detectlist='./Output/imagebbox_detect.list'
misslist='./Output/imagebbox_miss.list'
textutil.cleanbox(fileinput=bboxlist,detectlistfile=detectlist,misslistfile=misslist)
replacelist='./Output/imagebbox_detect_replace.list'
textutil.replace_file(detectlist,replacelist,ImagePath)
print 'Done Box file Clean and Replace. step(3/6)'
if tag_recover==True:
#人脸先裁剪
# 保留检测到的人脸图像，可选，
print 'Begin Save Detected Face Image. step(4/4) optional'
facecrop.face_cropout(ImagePath,savePathDetect,replacelist,w=savesize[0],h=savesize[1])
print 'Done Save Detected Face Image. step(4/4) optional'
ImagePath=savePathDetect
print 'Begin making filelist. step (1/6) '
#创建imagelist.list 文件，用来保存文件图像文件列表
imagelist = './Output/imagelist_recover.list'
fid=open(imagelist,'w')
makeimagelist.makeImageFileList(ImagePath,fid,fileformat)
fid.close()
#统计有多少个图像文件
count=textutil.count_text_line(imagelist)
textutil.insertLine(imagelist,1,str(count))
print 'Done make file list. step(1/6)'
#人脸检测，生成imageBbox.list 文件，
print 'Begin Face Detection task. step(2/6)'
bboxlist='./Output/imagebbox__recover.list'
os.system('FaceDetect.exe data '+imagelist+' '+bboxlist)
print 'Done Face Detection task.step(2/6)'
#清除检测不到的图像，或者检测到多个的文件，以便于后面的人脸关键点检测。
print 'Begin Box file Clean and Replace. step(3/6)'
detectlist='./Output/imagebbox_recover_detect.list'
misslist='./Output/imagebbox_recover_miss.list'
textutil.cleanbox(fileinput=bboxlist,detectlistfile=detectlist,misslistfile=misslist)
replacelist='./Output/imagebbox_detect_recover_replace.list'
textutil.replace_file(detectlist,replacelist,ImagePath)
print 'Done Box file Clean and Replace. step(3/6)'
#人脸关键点检测
print 'Begin Face Point Detection. step(4/6)'
resultpath='./Output/result.bin'
command_='FacePointDetect.exe '+replacelist+' '+ImagePath+' Input '+resultpath
os.system(command_)
print 'Done Face Point Detection. step(4/6)'
print 'Begin write Points files. step(5/6)'
points=textutil.take_out_point(resultpath)
imagepointlist='./Output/imagelist_point.list'
textutil.writePoint2File(replacelist,imagepointlist,points)
print 'Done write Points files. step(5/6)'
print 'Begin Alignment Face. step(6/6)'
aligment.align_all(imagepointlist,ImagePath,savePathAligned)
print 'Done Alignment Face. step(6/6)'
print 'Begin Face croped in'
facecrop.face_crop_in(savePathAligned,savePathCroped,replacelist,savesize[0],savesize[1])
print 'Done Face croped in '
print 'All work is done!'