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pushd "%~dp0" | |
dir /b %SystemRoot%\servicing\Packages\*Hyper-V*.mum >hyper-v.txt | |
for /f %%i in ('findstr /i . hyper-v.txt 2^>nul') do dism /online /norestart /add-package:"%SystemRoot%\servicing\Packages\%%i" | |
del hyper-v.txt | |
Dism /online /enable-feature /featurename:Microsoft-Hyper-V -All /LimitAccess /ALL | |
Pause |
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import os, urllib.request | |
from urllib.parse import urlsplit | |
LINK_FILE, links, filter, download = 'links.txt', [], (lambda l=None: links.append(l.replace('\n', '')) if l != "" or l != "\n" else None), (lambda url=None: urllib.request.urlretrieve(url, os.path.basename(urlsplit(url).path)) if url != None else None) | |
for line in open(os.path.join(os.getcwd(), LINK_FILE), 'w+').readlines(): filter(line) | |
for l in links: download(l) |
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crunch 0 25 abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWX YZ0123456789 | aircrack-ng --bssid aa:aa:aa:aa:aa:aa -w- cap.cap |
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import cv2 | |
import numpy as np | |
from matplotlib import pyplot as plt | |
hog = cv2.HOGDescriptor() | |
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector()) | |
# Detect faces | |
faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") | |
eyeCascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye.xml") |
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class GeoSolver: | |
def __init__(self): | |
return | |
def triangular_solver(self, a=None, b=None, c=None): | |
def solve_for_angles(self, a, b, c): | |
if (a & b & c == None): | |
return | |
else: | |
return_value = 180 |
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<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no"> | |
<body> | |
<div id="container"> | |
<canvas class="center-block" id="canvasOutput" width=320 height=240></canvas> | |
</div> | |
<div class="text-center"> | |
<input type="checkbox" id="face" name="classifier" value="face" checked> | |
<label for="face">face</label> | |
<input type="checkbox" id="eye" name="cascade" value="eye"> | |
<label for="eye">eye</label> |