def __init__(self):

self.IMAGE_HASH = ""

# 获取图片哈希值

def get_image_hash(self,file):

img = Image.open(file)

h = str(imagehash.dhash(img))

return h

# 人脸识别

def face(self,file):

matlab = matlab_wrapper.MatlabSession()

matlab.put('filename', file)

matlab.put('IMAGE_DIR', IMAGE_DIR)

matlab.eval('face')

count = matlab.get('count')

has_crop = matlab.get('has_crop')

return int(count),int(has_crop)==1

#黑白处理

def blackWhite(self,filename):

image_file = Image.open(IMAGE_DIR+filename) # open colour image

#exception : Premature end of JPEG file . IOError: image file is truncated (1 bytes not processed)

try:

image_file = image_file.convert('L') # convert image to black and white

except Exception as e:

raise

return IMAGE_DIR+filename

dst_path = IMAGE_DIR+"wb"+filename

image_file.save(dst_path)

return dst_path

#数字识别

def ocr(self,file):

ocr = BceOCRAPI("02fbe03acf3042a1b40e067bba1971f7", "bb1d4aafe7924fc0829fc33fa26b3347");

#黑白处理

# newImg = IMAGE_DIR +file

newImg = self.blackWhite(file)

#图像压缩处理

disImg = IMAGE_DIR +"ocrdis"+file

newImg = self.resizeImg(ori_img=newImg,dst_img=disImg,dst_w=1600,dst_h=1600,save_q=100)

with open(newImg, 'rb') as f:

content = f.read()

content = base64.b64encode(content)

try:

# ocr

# result = ocr.get_ocr_text(content, language='CHN_ENG')

result = ocr.get_ocr_text(content, language='ENG')

# print("file:"+file+"----------result:"+result)

return result

except Exception as e:

raise

# 图片如果宽或高大于300则等比例压缩

def resizeImg(self,**args):

args_key = {'ori_img': '', 'dst_img': '', 'dst_w': '', 'dst_h': '', 'save_q': 75}

arg = {}

for key in args_key:

if key in args:

arg[key] = args[key]

im = Image.open(arg['ori_img'])

ori_w, ori_h = im.size

widthRatio = heightRatio = None

ratio = 1

if (ori_w and ori_w > arg['dst_w']) or (ori_h and ori_h > arg['dst_h']):

if arg['dst_w'] and ori_w > arg['dst_w']:

widthRatio = float(arg['dst_w']) / ori_w # 正确获取小数的方式

if arg['dst_h'] and ori_h > arg['dst_h']:

heightRatio = float(arg['dst_h']) / ori_h

if widthRatio and heightRatio:

if widthRatio < heightRatio:

ratio = widthRatio

else:

ratio = heightRatio

if widthRatio and not heightRatio:

ratio = widthRatio

if heightRatio and not widthRatio:

ratio = heightRatio

newWidth = int(ori_w * ratio)

newHeight = int(ori_h * ratio)

else:

newWidth = ori_w

newHeight = ori_h

im.resize((newWidth, newHeight), Image.ANTIALIAS).save(arg['dst_img'], quality=arg['save_q'])

return arg['dst_img']

#鉴别黄色图片

def isnude(self,file):

#图像压缩处理

imagePath = IMAGE_DIR + file

nudeImg = IMAGE_DIR +"nude_"+file

# self.resizeImg(ori_img=imagePath,dst_img=nudeImg,dst_w=300,dst_h=300,save_q=100)

# faces = self.face("nude_"+file)

# self.cropImg("nude_"+file,faces)

n = Nude(nudeImg)

# n.setFaces(faces)

# n.resize(1000,1000)

n.parse()

# print n.result

return 1 if n.result else 0

# 统计数字个数

def countdigits(self,s):

digitpatt = re.compile('\d')

return len(digitpatt.findall(s))

# 删除图片

def delImg(self,file):

#黑白的

wbImg = IMAGE_DIR+"wb"+file

ocrImg300 = IMAGE_DIR +"dis"+file

#大于1600的

ocrImg1600 = IMAGE_DIR +"ocrdis"+file

nudeImg = IMAGE_DIR +"nude_"+file

if os.path.isfile(wbImg):

os.remove(wbImg)

if os.path.isfile(ocrImg300):

os.remove(ocrImg300)

if os.path.isfile(ocrImg1600):

os.remove(ocrImg1600)

# 鉴黄裁剪图

if os.path.isfile(nudeImg):

os.remove(nudeImg)

#删除原文件

# os.remove(IMAGE_DIR+file)

def one(self,file):

filepath = IMAGE_DIR+file

self.resizeImg(ori_img=filepath,dst_img=filepath,dst_w=480,dst_h=640,save_q=100)

if(os.path.isfile(filepath)):

# self.IMAGE_HASH = self.get_image_hash(filepath)

# redis_result = self.get_result_from_redis(self.IMAGE_HASH)

# if(redis_result):

# #删除图像

# self.delImg(file)

# print redis_result

# sys.exit(0)

is_pass = 1

#人脸检测

count,has_crop = self.face(file)

print("count:")

print(count)

print("has_crop:")

print(has_crop)

# 如果人脸不是1则 ocr和鉴黄不用检测

if(count!=1):

l = -1

is_nude = -1

is_pass = 0

else:

#ocr

text = ""

text = self.ocr(file)

text = text.encode("utf-8")

l = self.countdigits(text)

if (l > 6):

is_nude = -1

is_pass = 0

else:

#鉴黄 没有截图通过

if not has_crop:

is_nude = 0

is_pass = 1

else:

is_nude = self.isnude(file)

if(is_nude==1):

is_pass = 0

else:

is_pass = 1

#删除图像

self.delImg(file)

# print {"face_count":len(fc),"digital_count":l,"is_nude":is_nude,"pass":is_pass}

result = str(count)+","+str(l)+","+str(is_nude)+","+str(is_pass)

# 结果保存redis数据库

self.save_redis(self.IMAGE_HASH,result)

print result

return {"is_face":count,"is_qq":l,"is_nude":is_nude,"is_pass":is_pass}

else:

print("error:",file, "is not a img file")

return {"is_face":-1,"is_qq":-1,"is_nude":-1,"is_pass":-1}

# 保存redis

def save_redis(self,hash,result):

rr = RedisResults()

rr.save(hash,result)

# redis数据是否存在，并返回检测结果

def get_result_from_redis(self,hash):

rr = RedisResults()

return rr.get(hash)

# 多进程

def main(self):

count = multiprocessing.cpu_count()-1

pool = multiprocessing.Pool(processes=count)

# images = Images().findByNude(1)

youyuan = YouyuanLog().findByFace(0)

print("file count:"+str(len(youyuan)))

# sys.exit(0)

for f in youyuan:

# print f['name']

if(not os.path.isfile(IMAGE_DIR + f['name'])):

print(IMAGE_DIR + f['name'], " not exist")

else:

# self.detect(f['name'])

# pool.map(self.detect,f['name'] )

pool.apply_async(detect, (f['name'],)) # 维持执行的进程总数为processes，当一个进程执行完毕后会添加新的进程进去

# detect(f['name'])

print "Mark~ Mark~ Mark~~~~~~~~~~~~~~~~~~~~~~"

pool.close()

pool.join() # 调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束

print file

api = Api()

result = api.one(file)

# 更新数据库