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 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 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")
class AipAntiPornModel(AipModel):
"""Create a :class:`Model` instance from an `AipAntiPorn` model.
Parameters
----------
credential : tuple
Tuple of (appId, apiKey, secretKey) for using AIP API.
bounds : tuple
Tuple of lower and upper bound for the pixel values, usually
(0, 1) or (0, 255).
channel_axis : int
The index of the axis that represents color channels.
preprocessing: 2-element tuple with floats or numpy arrays
Elementwises preprocessing of input; we first substract the first
element of preprocessing from the input and then divide the input
by the second element.
"""
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 predictions(self, image):
"""Get prediction for input image
Parameters
----------
image : `numpy.ndarray`
The input image in [h, n, c] ndarry format.
Returns
-------
list
List of anitporn prediction resutls.
Each element is a dictionary containing:
{'class_name', 'probability'}
"""
image_bytes = ndarray_to_bytes(image)
predictions = self.model.antiPorn(image_bytes)
if 'result' in predictions:
return predictions['result']
return predictions
def model_task(self):
"""Get the task that the model is used for."""
return self._task
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)
class TextReview():
def __init__(self):
self.client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def recognize(self, text):
ans = self.client.antiSpam(text)
if ('error_msg' in ans.keys()):
print(ans['error_msg'])
return 0
ans = ans['result']
if (ans['reject'] == [] and ans['review'] == []): #pass
return 0
return 1
'''
class BaiduAntiSpam(object):
def __init__(self, api):
"""
:param api: ['15052846', 'SiU9AAGaZn2Zja7d8iSVqce5', 'P6NZ07ROvKTXFnSlDMmH4hf1smOxbfAA']
"""
self.api = api
self.client = AipImageCensor(*self.api)
@retry(tries=3, delay=2)
def anti_spam(self, text):
_ = self.client.antiSpam(text)
_['log_id'] = text
return _
def get_result(self, file, corpus):
with open(file, 'a') as f:
for s in tqdm_notebook(corpus):
res = self.anti_spam(s)
f.writelines("%s\n" % res)
class Util:
class MysqlPool(object):
"""
Mysql连接池
"""
def __init__(self,
host="127.0.0.1",
port="3306",
user="******",
password="******",
database="dgamonitoring",
pool_name="mypool",
pool_size=10):
res = {}
self._host = host
self._port = port
self._user = user
self._password = password
self._database = database
res["host"] = self._host
res["port"] = self._port
res["user"] = self._user
res["password"] = self._password
res["database"] = self._database
self.dbconfig = res
self.pool = self.create_pool(pool_name=pool_name,
pool_size=pool_size)
def create_pool(self, pool_name="mypool", pool_size=10):
pool = pooling.MySQLConnectionPool(pool_name=pool_name,
pool_size=pool_size,
pool_reset_session=True,
**self.dbconfig)
return pool
def close(self, conn, cursor):
cursor.close()
conn.close()
def execute(self, sql, args=None, commit=False):
"""
执行函数
args支持（1,2,3，）形式
DQL语句不用设置commit参数
操作语句需要设置
"""
# get connection form connection pool instead of create one.
conn = self.pool.get_connection()
cursor = conn.cursor()
if args:
cursor.execute(sql, args)
else:
cursor.execute(sql)
if commit is True:
conn.commit()
self.close(conn, cursor)
return None
else:
res = cursor.fetchall()
self.close(conn, cursor)
return res
def executemany(self, sql, args, commit=False):
conn = self.pool.get_connection()
cursor = conn.cursor()
cursor.executemany(sql, args)
if commit is True:
conn.commit()
self.close(conn, cursor)
return None
else:
res = cursor.fetchall()
self.close(conn, cursor)
return res
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 Sniff_DGA(self):
# 清空数据
# sql = 'delete from dga_response;'
# self.Mycursor.execute(sql)
# self.mydb.commit()
# self.mysqlPool.execute(sql,commit=True)
print('**** Start Monitoring traffic ****')
# 进程循环监测
self.DGA_Flag = 1
while self.DGA_Flag:
sniff(prn=self.callback_DGA,
iface=self.iface,
filter='udp port 53',
count=2)
self.DGA_Flag = 1
# sniff(prn=capture,iface='Realtek PCIe GBE Family Controller',filter='udp port 53',count=20)
def callback_DGA(self, packet):
if packet:
# print("抓包：",packet)
i = 0
for p in packet:
# 有的没有IP 只有IPV9
# print(p[IP].src)
# 查询/响应标志，0为查询，1为响应
qr = str(p[i][DNS].qr)
src = p[i][IP].src
dst = p[i][IP].dst
# 表示返回码，0表示没有差错，3表示名字差错，2表示服务器错误（Server Failure）
rcode = str(p[i][DNS].rcode)
if '0' in qr:
qr = 'Query'
# 域名
qname = p[i][DNS].qd.qname
if type(qname) == bytes:
qname = (qname.decode('utf-8'))[:-1]
domainArray = qname.split('.')[:-1]
domain = [[self.DGA_dict[x] for x in y]
for y in domainArray if len(y) > 1]
domain = tf.keras.preprocessing.sequence.pad_sequences(
domain, maxlen=self.DGA_dict['maxlen'])
with self.sess1.as_default():
with self.graph1.as_default():
pre = np.max(self.DGAModel.predict(domain))
# dga_request=Request(domain=domain,pre=float(pre))
# dga_request.save()
oldQname = ''
sql = "insert into dga_flow(src,dst,domain,type,prediction) values(%s,%s,%s,%s,%s)"
val = (src, dst, qname, 'request', float(pre))
self.mysqlPool.execute(sql, val, commit=True)
# self.Mycursor.execute(sql, val)
# self.mydb.commit()
print("Found DGA Request:-->", qname, "--- Pre :", pre)
if '1' in qr:
if '0' in rcode:
for j in range(10):
try:
rrname = p[j][DNS].an[j].rrname
rdata = p[j][DNS].an[j].rdata
if type(rrname) == bytes:
rrname = (rrname.decode('utf-8'))[:-1]
if type(rdata) == bytes:
rdata = (rdata.decode('utf-8'))[:-1]
# print("数据"+rdata)
domainArray = rrname.split('.')[:-1]
domain = [[self.DGA_dict[x] for x in y]
for y in domainArray if len(y) > 1]
domain = tf.keras.preprocessing.sequence.pad_sequences(
domain, maxlen=self.DGA_dict['maxlen'])
with self.sess1.as_default():
with self.graph1.as_default():
pre = np.max(
self.DGAModel.predict(domain))
oldRname = ''
sql = "insert into dga_flow(src,dst,domain,type,prediction) values(%s,%s,%s,%s,%s)"
val = (src, dst, rrname, 'response',
float(pre))
self.mysqlPool.execute(sql, val, commit=True)
print("Found DGA Response-->", rrname,
"---Pre :", pre)
except Exception as e:
pass
i = i + 1
'''
监测URL
'''
def Sniff_URL(self):
# sql = 'delete from URl_response'
# sql1 = 'delete from URl_request'
# self.Mycursor.execute(sql)
# self.Mycursor.execute(sql1)
# self.mydb.commit()
print('**** StartMonitoring traffic ****')
self.URL_Flag = 1
# 线程开启监测tcp 80端口
while self.URL_Flag:
sniff(prn=self.callBack_URL,
iface=self.iface,
filter='tcp',
count=5)
# sniff(prn=capture,iface='Realtek PCIe GBE Family Controller',filter='udp port 53',count=20)
self.URL_Flag = 1
print("****** 监测结束 *****")
pass
def callBack_URL(self, packet):
if packet:
i = 0
src = '0.0.0.0'
dst = '0.0.0.0'
if (packet.haslayer(IP)):
src = packet[IP].src
dst = packet[IP].dst
try:
if packet.haslayer('HTTP'):
p = packet["HTTP"]
try:
if p.haslayer('HTTPRequest'):
a = p["HTTPRequest"]
method = bytes.decode(a.Method)
if (a.Host != None):
Url = 'http://' + bytes.decode(
a.Host) + bytes.decode(a.Path)
url = [[self.Url_dict[x] for x in Url]]
url = keras.preprocessing.sequence.pad_sequences(
url, maxlen=self.Url_dict['maxlen'])
with self.sess2.as_default():
with self.graph2.as_default():
pre = np.max(
self.UrlModel.predict(url))
if (pre >= 0.7):
'''当url恶意率超过0.7，进行该网页爬取分析'''
t = threading.Thread(
target=self.AnalysisUrl(Url))
t.start()
print("Request url is :", Url, "pre :", pre)
sql = "insert into url_flow(src,dst,url,pre) values(%s,%s,%s,%s)"
val = (src, dst, Url, float(pre))
self.mysqlPool.execute(sql, val, commit=True)
except IndexError:
pass
try:
a = p["HTTPResponse"]
print('响应Url:', a.Location)
except IndexError:
pass
try:
a = p["Raw"]
try:
b = p["HTTPRequest"]
print("请求数据:", a.load)
except IndexError:
pass
try:
b = p["HTTPResponse"]
print('响应数据', a.load)
except IndexError:
pass
'''
对数据解析
也可将数据包保存下来
'''
except IndexError:
pass
except IndexError:
pass
def getBaiduTextDivideRes(self, text):
url = 'https://aip.baidubce.com/rest/2.0/antispam/v2/spam?access_token=24.d6402afd2e5dc564214b9a69a68d48fd.2592000.1571732535.282335-17305394'
data = urllib.parse.urlencode({
'content': text
}).encode(encoding='utf8')
request = urllib.request.Request(url, data=data)
# 设置请求头
request.add_header('Content-Type', 'application/x-www-form-urlencoded')
response = urllib.request.urlopen(request)
res = response.read()
j = json.loads(res.decode('utf8'))
review = j.get('result').get('review')
reject = j.get('result').get('reject')
print(review, reject)
return review, reject
def AnalysisUrl(self, url):
req = urllib.request.Request(url)
try:
res = urllib.request.urlopen(req, timeout=5)
result = res.read()
html = BeautifulSoup(result.decode('utf8'), 'lxml')
# 正则过滤
text = html.get_text(strip=True)
if len(text) > 5000:
limit = 0
while 1:
# 每次查5000字
if len(text[limit:limit + 5000]) == 0:
break
res = self.client.textCensorUserDefined(
(text[limit:limit + 5000]))
if res['conclusion'] != '合规':
result_list = list()
try:
datas = res['data']
for data in datas:
if (data['msg'] != '存在百度官方默认违禁词库不合规'):
result_list.append(
data['msg'].strip("存在").strip("不合规"))
except Exception as e:
print(e)
limit += 5000
else:
res = self.client.textCensorUserDefined((text))
if res['conclusion'] != '合规':
result_list = list()
try:
datas = res['data']
for data in datas:
if (data['msg'] != '存在百度官方默认违禁词库不合规'):
result_list.append(
data['msg'].strip("存在").strip("不合规"))
except Exception as e:
print(e)
sql = "update url_flow set status=%s where url= %s"
val = (str(result_list), url)
self.mysqlPool.execute(sql, val, commit=True)
except urllib.error.URLError:
print('网页不可访问')
from aip import AipImageCensor
# 图片审核
filePath = '../media/upload/aa.jpg'
def get_picture(filePath):
with open(filePath, 'rb') as f:
return f.read()
APP_ID = '16295532'
API_KEY = 'gWSlD06wqf8yADLNw1PSdIhI'
SECRET_KEY = 'pqxslzYtZvoDrpEN3qtebSexw8vqDlR7'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
result = client.imageCensorUserDefined(get_picture(filePath))
print(result)
if __name__ == '__main__':
get_picture(filePath)
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_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
from aip import AipImageCensor
""" 你的 APPID AK SK """
APP_ID = '10699663'
API_KEY = 'h6laYDwumS3UzwiCCjYGQPkP'
SECRET_KEY = 'd9GFQc6ntq0pBGHRv6YrFxxfEfDYq3QH'
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('cb.jpg')
result = client.imageCensorUserDefined(img)
print(result)
# if isinstance(result, dict):
# if result.has_key('conclusion'):
# if result['conclusion'] != u'合规':
# for data in result['data']:
# print (data['msg'])
from django.shortcuts import render
from django.http import HttpResponse, JsonResponse
from . import models
import json
import random
from aip import AipImageCensor
APP_ID = '20127419'
API_KEY = 'HnCMlNQBzVsQr4z3S57vClIK'
SECRET_KEY = 'hqpehal5EiZtqs3bjCgoroLpRF9PZwLW'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
def check(str):
result = client.textCensorUserDefined(str)
if result.get('conclusion') == '不合规':
return True
return False
# 添加评论
# todo: 自动审核
def addComment(request):
comment = models.Comment()
comment.Department = request.GET['Department']
comment.Grade = request.GET['Grade']
comment.Identity = request.GET['Identity']
comment.Name = request.GET['Name']
comment.Post = request.GET['Post']
comment.Phone = request.GET['Phone']
from aip import AipImageCensor
# """ 你的 APPID AK SK """
# APP_ID = '17899842'
# API_KEY = 'VM5S1ouZgwmk7Icc8x2l75pK'
# SECRET_KEY = '9Cvxl1qB4zGuidQod9Sw6zadQHcnIQZz'
""" API """
APP_ID = '19891414' # 你的appid
API_KEY = 'usNMOs7sdzwep3QOgY4xoFV2' # 你的apikey
SECRET_KEY = 'gw5vs1lKOLRGE6MstE8X8zbmxsXVBWIg' # 你的secretkey
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 = client.imageCensorUserDefined(get_file_content('sex3.jpg'))
""" 如果图片是url调用如下 """
#result = client.imageCensorUserDefined('https://imgsa.baidu.com/forum/w%3D580/sign=559cf2cad93f8794d3ff4826e21a0ead/f3bc0ddda3cc7cd94ac925ab3401213fb90e91eb.jpg')
print(result)
#官方测试:
from aip import AipImageCensor
import passwd
APP_ID = passwd.sex.APP_ID # 你的app id , 此处被隐藏,放在pass wd.py文件内,请自行申请
API_KEY = passwd.sex.API_KEY # 你的api key
SECRET_KEY = passwd.sex.SECRET_KEY # 你的secret key
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
# 读取图片
def get_file_content(file_path):
with open(file_path, 'rb') as fp:
return fp.read()
# 调用色情识别接口
# result = client.imageCensorUserDefined(get_file_content('sex1.png'))
# result = client.imageCensorUserDefined(get_file_content('sex2.jpg'))
# result = client.imageCensorUserDefined(get_file_content('sex3.jpg'))
# 如果图片是url调用如下
result = client.imageCensorUserDefined(
'https://imgsa.baidu.com/forum/w%3D580/sign=559cf2cad93f8794d3ff4826e21a0ead/f3bc0ddda3cc7cd94ac925ab3401213fb90e91eb.jpg'
)
print(result)
# 官方测试 :https://ai.baidu.com/tech/imagecensoring
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
from aip import AipImageCensor
""" 你的 APPID AK SK """
APP_ID = '11156578'
API_KEY = '3K73kH6H4aGoZbUrE1N0oTO5'
SECRET_KEY = 'YoL5g6BCnWG4mQvEo0TjyDPozlySdDRp'
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 = client.imageCensorUserDefined(get_file_content('c:/code/11.jpg'))
result2 = client.imageCensorUserDefined(get_file_content('c:/code/22.jpg'))
print(result)
print(result2)
""" 如果图片是url调用如下 """
result3 = client.imageCensorUserDefined('http://www.example.com/image.jpg')
from aip import AipImageCensor
""" 你的 APPID AK SK """
APP_ID = '11156578'
API_KEY = '3K73kH6H4aGoZbUrE1N0oTO5'
SECRET_KEY = 'YoL5g6BCnWG4mQvEo0TjyDPozlySdDRp'
client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
result = client.antiSpam('民警提醒说，此类骗局中，通常骗子要求汇款的理由包括“发红包”、“买礼物”、“生病就医”、“凑路费”、“生意需要资金”、“见面需要彩礼”等各种理由。因此，微信交友遇到这样情形要小心防骗')
print(result)
def __init__(self):
self.client = AipImageCensor(APP_ID, API_KEY, SECRET_KEY)
#
# # """ 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)
# -*- coding: utf-8 -*-
# 定义常量
APP_ID = '9839224'
API_KEY = '38aM2cGHnGXgfjwPgNv3hgHN'
SECRET_KEY = 'ze0DckCR2GTpFcz8LX17L61Ec8NV9Bc7'
# 引入AipImageCensor SDK
from aip import AipImageCensor
# 初始化AipImageCensor对象
aipImageCensor = 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 = aipImageCensor.antiPorn(get_file_content('antiporn.jpg'))
print(result)