def AipImageCensoR(filePath):
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
result = client.imageCensorUserDefined(
get_file_content(filePath))
# result = client.imageCensorUserDefined('http://www.example.com/image.jpg')
#print(result)
return result['conclusionType']
def openpic(request):
from qiniu import Auth, put_file, etag
import qiniu.config
from PIL import Image
from aip import AipImageCensor
a = request.FILES.get("imageData") #得到图片
b = random.randint(111111, 999999)
key = 's2' + str(b) + '.jpg'
Image = Image.open(a)
Image.save('s1.jpg') #保存本地
APP_ID = '10027473'
API_KEY = 'vuVlmlKsXULFfo438jiWfxb0'
SECRET_KEY = '33Iew8K4zT3hBBI1YqGPaK9vcHD5dAxG'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
img = get_file_content('s1.jpg')
result = client.imageCensorUserDefined(img)
if result['conclusion'] == '合规':
# path = default_storage.save('s1.jpg', ContentFile(Image.read()))
access_key = 'EjIqvG2iluFxOx-PzeIyCNUKqUL2je9Q5bfunOyg'
secret_key = 'pqt97zqOt7cw07a9AWwEXPp0zofB_9swvTVJGOOr'
q = Auth(access_key, secret_key)
bucket_name = 'xunyingpicture'
localfile = r"s1.jpg"
token = q.upload_token(bucket_name, key)
ret, info = put_file(token, key, localfile)
#返回图片地址
return HttpResponse('http://files.g8.xmgc360.com/' + key)
else:
return HttpResponse("1")
def bad_words_filter(img_name):
base_name = img_name.split('\\')[-1]
text = ' '
with open('data/results/' + 'res_{}.txt'.format(base_name.split('.')[0]),
'r') as f:
# text = f.read().split('\n')
text = ' '
# for i in text:
# temp += i
lines = f.readlines()
for line in lines:
str_arr = line.strip().split(',')
if len(str_arr) > 4:
for word in str_arr[4:]:
text += (word + ',')
with open('data/results/' + 'res_{}.txt'.format(base_name.split('.')[0]),
'a') as f:
client = AipImageCensor(appId='18097522',
apiKey='bgeRXmpblbOMocErTxvMCiOF',
secretKey='SyRmwoFGsKXqC3LvAAYwlDlf1BckBOwG')
if client.antiSpam(text)['result']['spam'] == 0:
f.write('无敏感信息')
else:
f.write('待检测的文本里面含有侮辱、色情、暴力和政治敏感词汇。\n')
for i in client.antiSpam(text)['result']['reject']:
if (len(i['hit']) != 0):
f.write(str(i['hit']))
def __init__(self):
# 测试数据
test_case = [np.zeros(10)]
print('**** Load dict ****')
f = open(config._URL['URL_DICT_PATH'], encoding='utf8')
char = f.read()
url_dict = eval(char)
f = open(config._DGA['DGA_DICT_PATH'], encoding='utf8')
char = f.read()
dga_dict = eval(char)
f.close()
self.DGA_dict = dga_dict
self.Url_dict = url_dict
# 文本检测返回值
self.URL_labels = ['暴恐违禁', '文本色情', '政治敏感', '恶意推广', '低俗辱骂', '低质灌水']
print('**** Load model ****')
''' 创建加载模型的所需变量'''
self.graph1 = tf.Graph()
self.sess1 = tf.Session(graph=self.graph1)
self.graph2 = tf.Graph()
self.sess2 = tf.Session(graph=self.graph2)
'''保证模型加载在一个图中，以便再使用模型时不为空'''
with self.sess1.as_default():
with self.graph1.as_default():
self.DGAModel = tf.keras.models.load_model(
config._DGA['DGA_MODEL_PATH'])
# 初始化的时候要进行一次模拟测试，防止layer找不到
test_case = tf.keras.preprocessing.sequence.pad_sequences(
test_case,
maxlen=self.DGA_dict['maxlen'],
)
self.DGAModel.predict(test_case, verbose=0)
print('DGA模型初始化成功')
keras.backend.clear_session()
with self.sess2.as_default():
with self.graph2.as_default():
self.UrlModel = keras.models.load_model(
config._URL['URL_MODEL_PATH'])
test_case = keras.preprocessing.sequence.pad_sequences(
test_case,
maxlen=self.Url_dict['maxlen'],
)
self.UrlModel.predict(test_case, verbose=0)
print('URL模型初始化成功')
self.iface = config.IFACE
self.DGA_Flag = 1
self.URL_Flag = 1
self.mydb = connect(host='localhost',
user='******',
passwd='123456',
database='dgamonitoring')
print('**** Connect mysql ****')
self.Mycursor = self.mydb.cursor()
self.mysqlPool = self.MysqlPool()
print('**** Connect success ****')
self.client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
pass
def contentany(content):
client = AipImageCensor('百度ai自己申请', '百度ai自己申请', '百度ai自己申请')
result = client.textCensorUserDefined(content)
result = json.loads(str(result).replace("'", '"'))
if "error_code" in result:
return result["error_msg"]
if result["conclusionType"] != 1 \
and result["conclusionType"] != 3:
return result["data"][0]["msg"]
return False
def test_article_filter():
try:
res = request.get_json()
article_id = res.get('article_id')
article_images = res.get('article_images')
Logging.logger.info('request_args:{0}'.format(res))
if not article_id:
return jsonify(errno=-1, errmsg='参数错误,请传入要查询的文章的article_id')
article = Article.query.get(article_id)
if not article:
return jsonify(errno=-1, errmsg='参数错误,该文章不存在')
docs = mongo_store.articles.find({'title': article.title})
doc = docs[0]
article_dict = dict()
content = doc.get('content')
title = article.title.encode("utf-8")
article_dict['title'] = title
article_dict['content'] = content
obj = SensitiveFilter()
str11 = ''.join(
[item.get('text') for item in content if item.get('text')])
text = {'content': str11}
txt_data = obj.content_check(text)
if txt_data.get('errcode') == 40001:
redis_store.delete('access_token')
txt_data = obj.content_check(text)
Logging.logger.info('res_data:{0}'.format(txt_data))
APP_ID = '15791531'
API_KEY = 'kajyVlP73XtSGBgoXDIHH5Za'
SECRET_KEY = 'u2TClEW6LaHIIpRNdFcL2HIexcgG1ovC'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
txt_resp = client.antiSpam(str11)
Logging.logger.info('txt_resp:{0}'.format(txt_resp))
for img in article_images:
img_resp = client.imageCensorUserDefined(img)
print(img_resp)
Logging.logger.info('img_resp:{0}'.format(img_resp))
# img_data = obj.img_check(img)
# print img_data
return jsonify(errno=0, errmsg="OK", data=txt_data)
except Exception as e:
Logging.logger.error('errmsg:{0}'.format(e))
return jsonify(errno=-1, errmsg='文章详情查询失败')
def __init__(self,
credential,
bounds=(0, 255),
channel_axis=3,
preprocessing=(0, 1)):
from aip import AipImageCensor
super(AipAntiPornModel, self).__init__(credential=credential,
bounds=bounds,
channel_axis=channel_axis,
preprocessing=preprocessing)
self._task = 'cls'
self.model = AipImageCensor(self._appId, self._apiKey, self._secretKey)
def picture_review(content):
pic = re.findall(r"<img src=(.*?)data", content)
h = 0
l = len(pic)
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
if l > 0:
for i in range(l):
url = pic[0][1:-2]
result = client.imageCensorUserDefined(url)
print(result)
if len(result['conclusion']) == 2:
h += 1
print("图片通过:%d") % h
print("图片违规:%d") % (l - h)
else:
print("没有图片")
def baiduimg(s):
""" 你的 APPID AK SK """
APP_ID = '14440883'
API_KEY = 'kT8o0IxopsPwp8dswWCV54ww'
SECRET_KEY = '8jPrgXlKj7c2mvDtkeqcTQe83RhdKLzV'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
result = client.imageCensorUserDefined(get_file_content(r's1.' + s))
print(result)
if str(result['conclusionType']) == '1':
return ('1')
else:
return (result['data'][0]['msg'])
def repic():
from aip import AipImageCensor
APP_ID = '10805647'
API_KEY = '4BORuFSWdXtODzh8gjFVUzKB'
SECRET_KEY = 'uZG60psAKFxRYZuqtQdTbree4ilaaPbB'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
with open(os.getcwd() + "/tmp.png", 'rb') as fp:
options = {
'detect_direction': 'true',
'language_type': 'CHN_ENG',
}
result = client.imageCensorComb(fp.read(), [
'clarity',
'antiporn',
])
rrresult = json.dumps(result).decode("unicode-escape")
print rrresult
def identity_picture(self, file_name, flag):
"""
:param file_name: 一个网络图片的url， 或者一个本地图片的地址
:param flag: 传送指定的参数‘url’ 或者 ‘local’
:return:
"""
s_client = AipImageCensor(self.APP_ID, self.API_KEY, self.SECRET_KEY)
if flag == 'local':
with open(file_name, 'rb') as f:
try:
res = s_client.imageCensorUserDefined(f.read())
print(res)
except TypeError:
raise print("类型错误")
elif flag == 'url':
res = s_client.imageCensorUserDefined(file_name)
print(res)
def __init__(self):
self.client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def __init__(self, api):
"""
:param api: ['15052846', 'SiU9AAGaZn2Zja7d8iSVqce5', 'P6NZ07ROvKTXFnSlDMmH4hf1smOxbfAA']
"""
self.api = api
self.client = AipImageCensor(*self.api)
def get_check_json(cls, content):
client = AipImageCensor(cls.APP_ID, cls.API_KEY, cls.SECRET_KEY)
return client.antiSpam(content=content)
password=GlobalVar.get_value('g_redis_password')))
# https://www.vaptcha.com
GlobalVar.set_value('g_vaptcha_id', '0')
GlobalVar.set_value('g_vaptcha_secretkey', '0')
websocket_clients = {}
GlobalVar.set_value('g_websocket_clients', websocket_clients)
# https://console.bce.baidu.com/
GlobalVar.set_value('g_baidu_APP_ID', '0')
GlobalVar.set_value('g_baidu_API_KEY', '0')
GlobalVar.set_value('g_baidu_APP_SECKEY', '0')
GlobalVar.set_value(
'g_baidu_APP',
AipImageCensor(GlobalVar.get_value('g_baidu_APP_ID'),
GlobalVar.get_value('g_baidu_API_KEY'),
GlobalVar.get_value('g_baidu_APP_SECKEY')))
websocket_urlpatterns = [
path('websocket/room/', web_socket.websocket_main),
]
application = ProtocolTypeRouter({
'websocket':
AuthMiddlewareStack(URLRouter(websocket_urlpatterns)),
})
urlpatterns = [
path('favicon.ico', serve, {'path': 'images/favicon.ico'}),
path('ha4k1r_admin/', view.admin, name='admin_index'),
path('bind_steam/', view.bind_steam, name='bind_steam'),
re_path(r'^$', view.index, name='index'),
re_path(r'^bind_steamid_process/(?P<key>\w+)/$',
view.steam_login,
def jh(self, file_name):
client = AipImageCensor(self.W_APP_ID, self.API_KEY, self.SECRET_KEY)
res = client.imageCensorUserDefined(file_name)
print(res)
def initspam():
global client1
APP_ID = '14422159'
API_KEY = 'psxn324sUoqFaNMjyob3FaqN'
SECRET_KEY = 'jakFwZEk63dTPr52ibznaBXoI0To2GEs'
client1 = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def check_Image(self, filepath): Image_client = AipImageCensor(self.APP_ID, self.API_KEY, self.SECRET_KEY) result = Image_client.imageCensorUserDefined(self.get_file_content(filepath)) return result
def __init__(self):
self.client = AipImageCensor(
current_app.config['APP_ID'],
current_app.config['API_KEY'],
current_app.config['SECRET_KEY']
)
def Check_Baidu():
imgContent, imgType = downloadImg(imgurl)
if len(imgContent) < 5e3 or len(imgContent) > 4e6:
return
if imgType not in ['jpg', 'jpeg', 'png']:
return
from aip import AipImageCensor
censor_APP_ID = '15708523'
censor_API_KEY = '6USQY453ZVSjxYYej1F195IZ'
censor_SECRET_KEY = 'r0rtrpRj8eHRnkPCfEhjOPRh2eO997Uv'
#另一个百度账号
if random.random() < 0:
censor_APP_ID = '22908418'
censor_API_KEY = 'Fz2zsXkSFmdH4BgcSwvGLeNP'
censor_SECRET_KEY = 'VSbOwvqUNzG1cDW89O9iTnnweLvLyGGM'
#classify_APP_ID = '17981247'
#classify_API_KEY = '3HuleW8fwIPymQcRM1DNhigp'
#classify_SECRET_KEY = 'LcClAOmKwGSIXR2st8ishMXUPXkiLaaI'
censor_client = AipImageCensor(censor_APP_ID, censor_API_KEY,
censor_SECRET_KEY)
censor_result = censor_client.antiPorn(imgContent)
#print(censor_result)
if 'result_fine' in censor_result:
for each in censor_result['result_fine']:
#print('type', each['type'], 'prob', each['probability'])
if each['class_name'] == '一般色情' and each['probability'] > 0.9:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '卡通色情' and each['probability'] > 0.51:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == 'SM' and each['probability'] > 0.65:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '艺术品色情' and each['probability'] > 0.9:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '儿童裸露' and each['probability'] > 0.9:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '低俗' and each['probability'] > 0.95:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '性玩具' and each['probability'] > 0.7:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '女性性感' and each['probability'] > 0.85:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '卡通女性性感' and each['probability'] > 0.51:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '男性性感' and each['probability'] > 0.95:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '自然男性裸露' and each['probability'] > 0.95:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '亲密行为' and each['probability'] > 0.90:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '卡通亲密行为' and each['probability'] > 0.65:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '特殊类' and each['probability'] > 0.95:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '一般正常' and each['probability'] > 1.0:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '卡通正常' and each['probability'] > 1.0:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '臀部特写' and each['probability'] > 0.85:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '裆部特写' and each['probability'] > 0.75:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '脚部特写' and each['probability'] > 0.85:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '孕肚裸露' and each['probability'] > 0.99:
print('色图！', end='')
saveImg(imgurl)
break
#
# # """ 调用人体检测与属性识别 """
# clients.bodyAttr(image)
#
# # """ 如果有可选参数 """
# options = {}
# options["age"] = "gender,age,upper_color"
#
# # """ 带参数调用人体检测与属性识别 """
# res = clients.bodyAttr(image, options)
# # print(res)
# c = res['person_info'][0]['attributes']
# # print(c)
# for k,v in c.items():
# print(k,v['name'])
# 图片鉴黄
s_client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
""" 读取图片 """
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
""" 调用色情识别接口 """
result = s_client.imageCensorUserDefined(
get_file_content('images/12345678.jpg'))
print(result)
def downloadImg(url):
r = requests.get(url)
return r.content
censor_APP_ID = '15708523'
censor_API_KEY = '6USQY453ZVSjxYYej1F195IZ'
censor_SECRET_KEY = 'r0rtrpRj8eHRnkPCfEhjOPRh2eO997Uv'
#classify_APP_ID = '17981247'
#classify_API_KEY = '3HuleW8fwIPymQcRM1DNhigp'
#classify_SECRET_KEY = 'LcClAOmKwGSIXR2st8ishMXUPXkiLaaI'
censor_client = AipImageCensor(censor_APP_ID, censor_API_KEY,
censor_SECRET_KEY)
censor_result = censor_client.antiPorn(downloadImg(imgurl))
print(censor_result)
if 'result_fine' in censor_result:
for each in censor_result['result_fine']:
#print('type', each['type'], 'prob', each['probability'])
if each['class_name'] == '一般色情' and each['probability'] > 0.9:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == '卡通色情' and each['probability'] > 0.55:
print('色图！', end='')
saveImg(imgurl)
break
elif each['class_name'] == 'SM' and each['probability'] > 0.65: