def main():
"""
The main function
"""
'''
database = input("Enter the name of database: ")
user = input("Enter your Username: "******"Enter the password: "******"Enter the host name where PostgreSQL database is install: ")
port = input("Enter the port: ")
Data = date_import(database, user, password, host, port)
'''
Data = pd.read_csv("Data.csv")
# create anomalies
percent = 10 # percentage of anomalies in the data
Data, true_data, anom_patients = generator(Data, percent)
# calculate distances
Mahaldist, Eucliddist, Cosinedist = calculate_dist(Data)
# detection of anomalies
(euclid, mahal, cosin, macos, maeuc, eucos, maeuccos,
outliers) = detector(Mahaldist, Eucliddist, Cosinedist)
# quality control
#true_data = np.zeros(len(euclid))
max_acc, accuracy, frame_dict = quality_of_classification(
euclid, mahal, cosin, macos, maeuc, eucos, maeuccos, true_data)
return Data, max_acc, accuracy, frame_dict, outliers, anom_patients
def xml2json(file_name):
# total_member, ref, nvd, non_nvd = 0, 0, 0, 0
with open('/home/wenbing/Desktop/Don_NTU/CNVD_dataset/'+file_name, 'r', encoding='UTF-8') as f:
xmlString = f.read()
jsonString = json.dumps(xmltodict.parse(xmlString),ensure_ascii=False, indent=4)
output = json.loads(jsonString)
member = output['vulnerabilitys']['vulnerability']
for _ in member:
# total_member = total_member +1
if 'referenceLink' in _:
url = _['referenceLink']
print("链接：", url)
print(detector(url))
#reading the current frame
ret, captured_frame = capture.read()
#break the loop if no input is received
if captured_frame is None:
break
#resizing the frame received
captured_frame = cv2.resize(captured_frame, (imageSize))
#applying background subtraction method to get foreground mask
fg_mask = bg_sub.apply(captured_frame)
#creating an instance of detector object
DetectorObject = detector(fg_mask, minimumDetectionArea, image_no,
captured_frame)
# Obtain measurements
centers, coordinates = DetectorObject.detect()
# Draws boxes where object detected, if no measurements, do nothing
try:
DetectorObject.draw_rectangles(coordinates, (0, 0, 0))
except:
pass
cv2.imshow('Detection on the Original Image', captured_frame)
cv2.imshow('Detected Background After Filtering', fg_mask)
# Write images into desired folder
# cv2.imwrite(f'pics\org_box\{image_no}.jpg', captured_frame)