def __init__(self, logname, withuuid=True):
print 'Init Log System...'
if not os.path.exists('log'):
os.mkdir('log')
# 创建一个self.logger
if withuuid:
logname = logname + '_' + str(uuid.uuid1())
self.logger = logging.getLogger(logname)
self.logger.setLevel(logging.INFO)
# 创建一个handler，用于写入日志文件
filename = 'log/%s_%s.log' % (logname, utils.GetCurrentTime())
fh = logging.FileHandler(filename)
fh.setLevel(logging.INFO)
# 再创建一个handler，用于输出到控制台
ch = logging.StreamHandler()
ch.setLevel(logging.INFO)
# 定义handler的输出格式
#'%(asctime)s-%(name)s-%(levelname)s-%(message)s'
formatter = logging.Formatter('[%(asctime)s]%(message)s')
fh.setFormatter(formatter)
ch.setFormatter(formatter)
# 给self.logger添加handler
self.logger.addHandler(fh)
self.logger.addHandler(ch)
def incChalNrTimes(userName, chalID, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
userTable = dataBase.table('chal_nr_times')
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime()
}
userTable.insert(row)
except Exception as e:
print("Exception - incChalNrTimes: " + str(e) + "\n")
def addHeartBeat(userName, chalID, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
tLTable = dataBase.table('heartbeat')
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime(),
"ip": ip
}
tLTable.insert(row)
except Exception as e:
print("Exception - addHeartBeat: " + str(e) + "\n")
def addHintTag(userName, chalID, hintTag, html, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
tbl = dataBase.table('hints')
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime(),
"hint": hintTag,
"html": html,
"ip": ip
}
tbl.insert(row)
except Exception as e:
print("Exception - addHintTag: " + str(e) + "\n")
def addChalFeedback(userName, chalID, rate1, rate2, rate3, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
tbl = dataBase.table('chal_feedback')
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime(),
"rate1": str(rate1),
"rate2": str(rate2),
"rate3": str(rate3),
"ip": ip
}
tbl.insert(row)
except Exception as e:
print("Exception - addChalFeedback: " + str(e) + "\n")
def addInteraction(userName, chalID, iType, message, folder, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
tLTable = dataBase.table('timeline')
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime(),
"type": iType,
"message": message,
"folder": folder,
"ip": ip
}
tLTable.insert(row)
except Exception as e:
print("Exception - addInteraction: " + str(e) + "\n")
def unlockChallenge(userName, chalID, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
unlockTable = dataBase.table('unlock')
q = Query()
r = unlockTable.search((q.chalID == chalID)
& (q.userName == userName))
if len(r) == 0:
row = {
"userName": userName,
"chalID": chalID,
"ts": utils.GetCurrentTime(),
"ip": ip
}
unlockTable.insert(row)
except Exception as e:
print("Exception - unlockChallenge: " + str(e) + "\n")
def unlockFile(userName, chalID, fileName, unlockCode, ip):
with lock:
try:
dataBase = TinyDB(dbFileName)
tbl = dataBase.table('unlock_file')
q = Query()
r = tbl.search((q.chalID == chalID) & (q.userName == userName)
& (q.unlockCode == unlockCode))
if len(r) == 0:
row = {
"userName": userName,
"chalID": chalID,
"fileName": fileName,
"unlockCode": unlockCode,
"ts": utils.GetCurrentTime(),
"ip": ip
}
tbl.insert(row)
except Exception as e:
print("Exception - unlockFile: " + str(e) + "\n")
def insertReport(userName, chalID, message, userContent, inputContent, folder,
ip):
exception = None
with lock:
try:
dataBase = TinyDB(dbFileName)
repTable = dataBase.table('reports')
report = {
"userName": userName,
"chalID": chalID,
"message": message,
"userContent": userContent,
"inputContent": inputContent,
"ts": utils.GetCurrentTime(),
"folder": folder,
"ip": ip
}
repTable.insert(report)
except:
exception = "could not open database"
if (exception != None):
raise Exception(exception)
def test(net, test_Loader, device, display_interval, out_dir, num_classes,
iterations):
print('{}: Start testing '.format(utils.GetCurrentTime()))
confusionMatrix = np.zeros((num_classes, num_classes))
proba_all = []
label_all = []
# predict_proba = []
predict_class = []
start_time = time.time()
with torch.no_grad():
for iter_val, data in enumerate(test_Loader):
if iter_val % display_interval == (display_interval - 1):
print("Iterations: [{}/{}]".format(iter_val + 1, iterations))
# images, labels = data
images, labels = data[0].to(device), data[1]
outputs = net(images)
proba = utils.softmax(outputs.cpu())
predicted = torch.max(proba, 1)
proba_all.extend(proba.numpy())
label_all.extend(labels.numpy())
# predict_proba.extend(predicted[0].numpy())
predict_class.extend(predicted[1].numpy())
for idx, label in enumerate(labels):
confusionMatrix[label, predicted[1][idx]] += 1
print("Iterations: [{}/{}]".format(iterations, iterations))
end_time = time.time()
print('{}: Testing Finished'.format(utils.GetCurrentTime()))
data_size = len(predict_class)
proba_all = np.array(proba_all)
label_all = np.reshape(label_all, (-1, 1))
predict_class = np.reshape(predict_class, (-1, 1))
accuracy = np.sum(np.diag(confusionMatrix)) / data_size
error = np.round(1 - accuracy, 6)
accuracy_perClass = np.diag(confusionMatrix) / np.sum(confusionMatrix,
axis=0)
error_perClass = 1 - accuracy_perClass
output = np.concatenate([proba_all, label_all, predict_class], axis=1)
output = output.astype('float')
probaMatrixPath = os.path.join(out_dir, "TestProbaMatrix.txt")
confMatPath = os.path.join(out_dir,
'{}_Err={}.txt'.format("TestConfMat", error))
np.savetxt(probaMatrixPath, output, fmt='%f')
np.savetxt(confMatPath, confusionMatrix, fmt='%d', delimiter='\t')
time_per_img = (end_time - start_time) * 1000 / data_size
print("\n#------------------------------------------------------#\n")
print("Overall Accuracy : {}%".format(round(accuracy * 100, 2)))
print("Overall Error Rate : {}%".format(round(error * 100, 2)))
print('Test time per image (ms): {}'.format(round(time_per_img, 4)))
print()
print("Dump probability matrix: {}".format(
os.path.split(probaMatrixPath)[-1]))
print("Dump confusion matrx: {}".format(os.path.split(confMatPath)[-1]))
print('\n=============================')
print('Error Rate (per-class): ')
for l in range(num_classes):
print(' class {} : {}%'.format(l, round(error_perClass[l] * 100, 2)))
print('=============================\n')