Datasets:
jblitzar
/
github-python-corpus

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""" Send the response and return the parsed sid. raises an Exception on error """
# Build response params
post_data = {"username": username, "response": challenge_response}
# post_data = urllib.parse.urlencode(post_data_dict).encode()
headers = {"Content-Type": "application/x-www-form-urlencoded"}
url = box_url + LOGIN_SID_ROUTE
r = requests.post(url, headers=headers, data=post_data)
# Parse SID from resulting XML.
xml = etree.fromstring(r.content)
return xml.find("SID").text
def get_page_content(server, session_id, page, port=80):
"""Fetches a page from the Fritzbox and returns its content
:param server: the ip address of the Fritzbox
:param session_id: a valid session id
:param page: the page you are regquesting
:param port: the port the Fritzbox webserver runs on
:return: the content of the page
"""
headers = {"Accept": "application/xml", "Content-Type": "text/plain", "User-Agent": USER_AGENT}
url = "http://{}:{}/{}?sid={}".format(server, port, page, session_id)
try:
r = requests.get(url, headers=headers)
r.raise_for_status()
except requests.exceptions.HTTPError as err:
print(err)
sys.exit(1)
return r.content
def get_xhr_content(server, session_id, page, port=80):
"""Fetches the xhr content from the Fritzbox and returns its content
:param server: the ip address of the Fritzbox
:param session_id: a valid session id
:param page: the page you are regquesting
:param port: the port the Fritzbox webserver runs on
:return: the content of the page
"""
headers = {
"Accept": "application/xml",
"Content-Type": "application/x-www-form-urlencoded",
"User-Agent": USER_AGENT,
}
url = "http://{}:{}/data.lua".format(server, port)
data = {"xhr": 1, "sid": session_id, "lang": "en", "page": page, "xhrId": "all", "no_sidrenew": ""}
try:
r = requests.post(url, data=data, headers=headers)
except requests.exceptions.HTTPError as err:
print(err)
sys.exit(1)
return r.content
# <FILESEP>
import sys
import math
import random
import numpy as np
from numpy import linalg as LA
import cv2
from scipy.spatial import distance
from openvino.inference_engine import IECore
model_det = 'face-detection-adas-0001'
model_hp = 'head-pose-estimation-adas-0001'
model_gaze = 'gaze-estimation-adas-0002'
model_lm = 'facial-landmarks-35-adas-0002'
model_det = './intel/'+model_det +'/FP16/'+model_det
model_hp = './intel/'+model_hp +'/FP16/'+model_hp
model_gaze = './intel/'+model_gaze+'/FP16/'+model_gaze
model_lm = './intel/'+model_lm +'/FP16/'+model_lm
_N = 0
_C = 1
_H = 2
_W = 3
def line(p1, p2):
A = (p1[1] - p2[1])
B = (p2[0] - p1[0])
C = (p1[0]*p2[1] - p2[0]*p1[1])
return A, B, -C
def intersection(L1, L2):
D = L1[0] * L2[1] - L1[1] * L2[0]
Dx = L1[2] * L2[1] - L1[1] * L2[2]
Dy = L1[0] * L2[2] - L1[2] * L2[0]
x = Dx / D
y = Dy / D
return x,y