mitjat

import base64
import json
import matplotlib, matplotlib.pyplot
import numpy
import types 

def show_plot(width, height=None):
    """
    A decorator -- show the matplotlib plot after `f` completes.
    Takes optional parameters (width, height) determining the size of the plot.

vchollati

johnny5550822

Can you imagine a computer can generate an nba article?

The following is some nba articles fully-automatically generated by char-cnn, a recurrent-neural-network library thanks to Andrej Karpathy [link]. The library is awesome to easy, and very user-friendly. You should try it! :)

Basically, I wrote a python script [link] to extract past archives . And use that as the training set for the recurrent neural network.

The articles below are generated by a network trained with rougly about 2 millions character (which is an okay size; not big enough though). You can see that the generated article contains artificial author names, speeches, etc; similar to an nba archive (although the logic has to be improved, it is FUN.)

You can tune the parameter and train with a even bigger dataset using my script. And you will probably get better result! Have fun:)

maraoz

OP_DEPTH 3 OP_EQUAL
OP_IF
  OP_HASH160 <hash160(R)> OP_EQUALVERIFY
  OP_0 2 <AlicePubkey1> <BobPubkey1> 2 OP_CHECKMULTISIG
OP_ELSE
  OP_0 2 <AlicePubkey2> <BobPubkey2> 2 OP_CHECKMULTISIG
OP_END

tylerkerr

#!/usr/bin/env python3

# toy RSA key generation/encryption/decryption
# this is only a demonstration of the underlying math - extremely unsafe!
# unmodified textbook RSA is both malleable and semantically insecure.

import subprocess
from gmpy import invert # requires gmpy for modular inversion

def ascii2int(string): # function for converting an ascii string to a single integer so that we can do math on it

echohack

ffmpeg -i input_file.mp4 -vf scale=320:-1:flags=lanczos,fps=30 frames/ffout%03d.png
convert -loop 0 frames/ffout*.png output_file.gif

pawlos

#!/bin/bash

if [[ $EUID -ne 0 ]]; then
   	echo "This script must be run as root" 
   	exit 1
fi

user=$(who | awk '{print $1}')
#Update and Upgrade
echo "Updating and Upgrading"

njv299

""" 
   Simple test harness for AFL's Unicorn Mode.

   This loads the simple_target.bin binary (precompiled as MIPS code) into
   Unicorn's memory map for emulation, places the specified input into
   simple_target's buffer (hardcoded to be at 0x300000), and executes 'main()'.
   If any crashes occur during emulation, this script throws a matching signal
   to tell AFL that a crash occurred.

   Run under AFL as follows:

tompng

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practicalswift

#!/usr/bin/env python3

# $ ./nakamotos-wild-mouse.py
# Match between the reverse engineered vaccine and the Biontech Pfizer vaccine when using codon optimization for species:
# * Homo sapiens: 91.07%
# * Mus musculus molossinus (Japanese wild mouse): 91.42% (laboratory mice are usually of the species mus musculus)
#
# The Times 01/Jan/2021 Nakamoto's wild mouse on brink of saving humanity

import dnachisel