def load_image(request):
img_name = 'img' + str(time.time() * 1000) + '.jpg'
img_path = '/img/' + img_name
dest = open(img_path, 'wb+')
for chunk in request.FILES['image'].chunks():
dest.write(chunk)
dest.close()
if request.user.is_authenticated():
add_time = time.gmtime()
ans = request.POST.get('ans', '')
obj = Picture(pic_name=img_name,
user=request.user.username,
add_time=add_time,
vote=0,
ans=ans,
recognized='')
else:
add_time = time.gmtime()
ans = request.POST.get('ans', '')
obj = Picture(pic_name=img_name,
user='******',
add_time=add_time,
vote=0,
ans=ans,
recognized='')
doc = Document()
body = doc.createElement('body')
doc.appendChild(body)
thx = doc.createTextNode('Thanx!')
doc.appendChild(thx)
c = Client()
c.Connect()
c.Send(img_path)
return HttpResponse(doc, mimetype='application/xml')
def __init__(self, gun):
self.gun = gun
test_server = self.gun.get_option('test_server')
test_port = self.gun.get_option('test_port')
test_socket = TSocket.TSocket(test_server, test_port)
socket = test_socket.create()
self.transport = TTransport.TFramedTransport(socket)
protocol = TBinaryProtocol.TBinaryProtocol(self.transport)
self.client = Client(protocol)
from service.client import Client
# 数据组
sample = [[0, 1], [1, 0], [1, 1], [1, 2], [2, 1], [2, 2]]
# 标签组
label = [0, 0, 0, 1, 1, 1]
# 创建SVM学习器，使用默认参数。
svm = SVM()
# 训练分类器
svm.train(sample, label)
#测试分类器对新样本的分类
print(svm.classify([3, 3]))
print(svm.classify([0, 0]))
print(svm.classify([[1, 3], [0, 3], [0, 2], [0, 1]]))
# 创建服务器连接
c = Client("219.223.243.8", 8088)
# 保存分类器到服务器
c.save(svm, "test")
# 载入之前保存在服务器上的分类器
new_svm = c.load("test")
# 测试新分类器是否和之前的结果一样
print(new_svm.classify([3, 3]))
print(new_svm.classify([0, 0]))
print(new_svm.classify([[1, 3], [0, 3], [0, 2], [0, 1]]))
def setUp(self):
self.test_client = Client('mock name', 'mock last', '')
class ClientTestCase(unittest.TestCase):
def setUp(self):
self.test_client = Client('mock name', 'mock last', '')
def test_name_last_name(self):
expected_name = 'mock name mock last'
self.assertEqual(self.test_client.get_formatted_name(), expected_name)
def test_name_add_preexistence(self):
self.assertEqual(len(self.test_client.get_all_preexistence()), 0)
self.test_client.add_preexistence('mock preexistence')
self.assertEqual(len(self.test_client.get_all_preexistence()), 1)
self.assertEqual(self.test_client.get_preexistence(0),
'mock preexistence')
self.assertEqual(self.test_client.get_preexistence(1),
'There is no such preexistence')
def test_name_remove_preexistence(self):
self.assertEqual(len(self.test_client.get_all_preexistence()), 0)
self.test_client.add_preexistence('mock preexistence')
self.test_client.add_preexistence('mock preexistence 2')
self.test_client.add_preexistence('mock preexistence 3')
self.assertEqual(len(self.test_client.get_all_preexistence()), 3)
self.test_client.remove_preexistence(1)
self.assertEqual(self.test_client.get_preexistence(0),
'mock preexistence')
self.assertEqual(self.test_client.get_preexistence(1),
'mock preexistence 3')
self.assertEqual(self.test_client.get_preexistence(2),
'There is no such preexistence')
__author__ = 'ict'
from service.client import Client
# 测试用的变量
test = {
1: [1, 2, 3],
2: [1, 2, 3],
3: [1, 2, 3],
}
# 创建一个到服务器的连接
c = Client("219.223.243.8", 8088)
# 测试对变量的各种存取操作
print(c.save(test, "test"))
print(c.load("test"))
print(c.list())
print(c.remove("test"))
print(c.load("test"))
print(c.list())
# 关闭连接
c.close()
# 数据组
sample = [[0, 1], [1, 0], [1, 1], [1, 2], [2, 1], [2, 2]]
# 标签组
label = [0, 0, 0, 1, 1, 1]
# k值
k = 3
# 创建k近邻学习器，使用欧几里得距离。
knn = KNN(k)
# 训练分类器
knn.train(sample, label)
# 测试分类器对新样本的分类
print(knn.classify([3, 3]))
print(knn.classify([0, 0]))
print(knn.classify([[1, 3], [0, 3]]))
# 创建服务器连接
c = Client("219.223.243.8", 8088)
# 保存分类器到服务器
c.save(knn, "test-knn")
# 载入之前保存在服务器上的分类器
new_knn = c.load("test-knn")
# 测试新分类器是否和之前的结果一样
print(new_knn.classify([3, 3]))
print(new_knn.classify([0, 0]))
print(new_knn.classify([[1, 3], [0, 3]]))
"-" * size_len + "-+-" + "-" * lock_len + "-+")
for name, attr in var_dict.items():
size_str = normal_size(attr[size_offset])
print("| " + str(name) + " " * (name_len - len(str(name))), end="")
print(" | " + str(attr[type_offset]) + " " *
(type_len - len(str(attr[type_offset]))),
end="")
print(" | " + str(size_str) + " " * (size_len - len(size_str)), end="")
print(" | " + str(attr[lock_offset]) + " " *
(lock_len - len(str(attr[lock_offset]))) + " |")
print("+-" + "-" * name_len + "-+-" + "-" * type_len + "-+-" +
"-" * size_len + "-+-" + "-" * lock_len + "-+")
if __name__ == "__main__":
c = Client("219.223.243.8", 10555)
while True:
var = c.list()
print_list(var)
cmd = input(">>> ")
tmp_list = cmd.split(" ")
cmd_list = []
for one_cmd in tmp_list:
if len(one_cmd) != 0:
cmd_list.append(one_cmd)
if len(cmd_list) == 0:
continue
start_time = time.time()
try:
if cmd_list[0] == "print":
if len(cmd_list) != 2:
print("| " + name_title + " " * (name_len - len(name_title)), end="")
print(" | " + type_title + " " * (type_len - len(type_title)), end="")
print(" | " + size_title + " " * (size_len - len(size_title)), end="")
print(" | " + lock_title + " " * (lock_len - len(lock_title)) + " |")
print("+-" + "-" * name_len + "-+-" + "-" * type_len + "-+-" + "-" * size_len + "-+-" + "-" * lock_len + "-+")
for name, attr in var_dict.items():
size_str = normal_size(attr[size_offset])
print("| " + str(name) + " " * (name_len - len(str(name))), end="")
print(" | " + str(attr[type_offset]) + " " * (type_len - len(str(attr[type_offset]))), end="")
print(" | " + str(size_str) + " " * (size_len - len(size_str)), end="")
print(" | " + str(attr[lock_offset]) + " " * (lock_len - len(str(attr[lock_offset]))) + " |")
print("+-" + "-" * name_len + "-+-" + "-" * type_len + "-+-" + "-" * size_len + "-+-" + "-" * lock_len + "-+")
if __name__ == "__main__":
c = Client("219.223.243.8", 10555)
while True:
var = c.list()
print_list(var)
cmd = input(">>> ")
tmp_list = cmd.split(" ")
cmd_list = []
for one_cmd in tmp_list:
if len(one_cmd) != 0:
cmd_list.append(one_cmd)
if len(cmd_list) == 0:
continue
start_time = time.time()
try:
if cmd_list[0] == "print":
if len(cmd_list) != 2: