def show_frame(self):
start = time()
_, frame = self.cap.read()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
try:
present_user = Classifier()
present_user.infer(frame)
# self.set_person_name(frame, present_user.person_name, present_user.confidence)
self.set_face_shape_contour(frame)
self.img = Image.fromarray(frame)
self.imgtk = ImageTk.PhotoImage(image=self.img)
self.lmain.imgtk = self.imgtk
self.lmain.configure(image=self.imgtk)
self.lmain.after(1, self.show_frame)
print(time() - start)
print(present_user.person_name, present_user.confidence,
present_user.face_128_chars[:6])
except:
print('Камера не видит твое лицо')
self.img = Image.fromarray(frame)
self.imgtk = ImageTk.PhotoImage(image=self.img)
self.lmain.imgtk = self.imgtk
self.lmain.configure(image=self.imgtk)
self.lmain.after(1, self.show_frame)
print(time() - start)
def crawler(domain, pathseed, uniqueId, maxSize=5000):
pq = queue.PriorityQueue()
visited = []
links = []
pq.put((value(domain + pathseed), domain + pathseed))
visited.append(domain + pathseed)
rp = Robots.fetch(domain + '/robots.txt', verify=False)
driver = webdriver.PhantomJS(
service_args=['--ignore-ssl-errors=true', '--ssl-protocol=any'])
while (not pq.empty() and pq.qsize() < maxSize * 5):
a = pq.get()[1]
print("! " + str(len(links)) + " " + a)
if (len(links) < maxSize):
links.append(a)
ls = get_all_links(domain, a, maxSize, rp, driver)
for l in ls:
if (l not in visited):
if (value(l) == 1 or value(l) == 2):
visited.append(l)
pq.put((value(l), l))
else:
while (not pq.empty()):
pq.get()
while (len(links) < maxSize and not pq.empty()):
links.append(pq.get()[1])
os.makedirs('Docs/HTMLPages/Heuristic2/' + folder(domain) + '/True/',
exist_ok=True)
os.makedirs('Docs/HTMLPages/Heuristic2/' + folder(domain) + '/False/',
exist_ok=True)
print(len(links))
v = 0
clf = Classifier()
pos = 0
res = ""
for l in links:
v += 1
driver.get(l)
time.sleep(1)
soup = BeautifulSoup(driver.page_source, "html.parser")
res = str(clf.classify(soup))
print(str(v) + " " + l + " " + res)
#print(driver.page_source)
if (res == 'True'):
pos += 1
extractorMain.extractor(soup, folder(domain), "Heuristic2",
folder(domain).lower(), l, uniqueId)
uniqueId += 1
with open(
'Docs/HTMLPages/Heuristic2/' + folder(domain) + '/' + res +
'/' + str(v) + '-' + l.replace('/', '*') + '.html', 'wb') as f:
f.write(bytes(driver.page_source, 'UTF-8'))
hr = pos / maxSize
with open('Docs/HTMLPages/Heuristic2/' + folder(domain) + '/' + 'hr.txt',
'wb') as f:
f.write(bytes(str(hr), 'UTF-8'))
return 0
def crawler(domain, pathseed, maxSize=273):
q = queue.Queue()
visited = []
links = []
q.put(domain + pathseed)
visited.append(domain + pathseed)
rp = Robots.fetch(domain + '/robots.txt', verify=False)
driver = webdriver.PhantomJS(
service_args=['--ignore-ssl-errors=true', '--ssl-protocol=any'])
while (not q.empty() and q.qsize() < maxSize):
a = q.get()
print("! " + str(len(links)) + " " + a)
if (len(links) < maxSize):
links.append(a)
ls = get_all_links(domain, a, maxSize, rp, driver)
for l in ls:
if (l not in visited):
visited.append(l)
q.put(l)
else:
while (not q.empty()):
q.get()
while (len(links) < maxSize and not q.empty()):
links.append(q.get())
os.makedirs('Docs/HTMLPages/BFS/' + folder(domain) + '/True/',
exist_ok=True)
os.makedirs('Docs/HTMLPages/BFS/' + folder(domain) + '/False/',
exist_ok=True)
print(len(links))
v = 0
clf = Classifier()
pos = 0
res = ""
for l in links:
v += 1
driver.get(l)
time.sleep(1)
soup = BeautifulSoup(driver.page_source, "html.parser")
res = str(clf.classify(soup))
print(str(v) + " " + l + " " + res)
#print(driver.page_source)
if (res == 'True'):
pos += 1
with open(
'Docs/HTMLPages/BFS/' + folder(domain) + '/' + res + '/' +
str(v) + '-' + l.replace('/', '*') + '.html', 'wb') as f:
f.write(bytes(driver.page_source, 'UTF-8'))
hr = pos / maxSize
with open('Docs/HTMLPages/BFS/' + folder(domain) + '/' + 'hr.txt',
'wb') as f:
f.write(bytes(str(hr), 'UTF-8'))
return 0
def start_capture(self):
"""
Starts demonstrating frames from the camera
"""
if not self.capture:
self.capture = QtCapture(0)
# self.capture.setFPS(1)
self.capture.user_classifier = Classifier()
self.capture.setParent(self)
self.capture.setWindowFlags(QtCore.Qt.Tool)
self.capture.start()
self.capture.show()
def __init__(self, *args):
super(QWidget, self).__init__()
self.fps = 30
self.video_frame = QLabel()
self.cap = cv2.VideoCapture(*args)
self.user_classifier = Classifier()
lay = QVBoxLayout()
# lay.setContentsMargins(0)
lay.addWidget(self.video_frame)
self.setLayout(lay)
self.label_encoder = None
self.classifier = None
self.person_name = None
self.confidence = None
import urllib.request
from selenium import webdriver
from bs4 import BeautifulSoup
import signal
from Classifier.classifier import Classifier
url = "http://www.spoj.com/problems/MMIND/"
driver = webdriver.PhantomJS( service_args=['--ignore-ssl-errors=true', '--ssl-protocol=any'])
driver.get(url)
page = BeautifulSoup(driver.page_source, "html.parser")
driver.service.process.send_signal(signal.SIGTERM)
k = [0,1,2,3,4,5]
for i in k:
clf = Classifier(i)
print(clf.classify(page))
def add_user(self):
person_name = raw_input('Введите ФИО в формате: \'familiya-imya\'\n')
self.make_user_profile(person_name)
add_user = Classifier()
add_user.train_classifier()
print('Пользователь успешно добавлен')