Kendrick Tan kendricktan

GK7102 Based IP Camera

Background

Just bought one unit of GK7102-based camera at US$8 (Yes, just US$8!). The seller claimed it had a 1080p sensor and three antennas but the sensor was found to be 720p and only one antenna is wired. No manufacturer information available but only a model "Y6A-WA" printed on the box.

After unboxing, the PCB was found detached from the base. Opening the base and show that the PCB has two mounting holes but only one screw was found. Moreover, the size of the mounting holes are too big for that screw!

Hardware info

CPU: ARMv6 CPU

A Tour of PyTorch Internals (Part I)

The fundamental unit in PyTorch is the Tensor. This post will serve as an overview for how we implement Tensors in PyTorch, such that the user can interact with it from the Python shell. In particular, we want to answer four main questions:

How does PyTorch extend the Python interpreter to define a Tensor type that can be manipulated from Python code?
How does PyTorch wrap the C libraries that actually define the Tensor's properties and methods?
How does PyTorch cwrap work to generate code for Tensor methods?
How does PyTorch's build system take all of these components to compile and generate a workable application?

Extending the Python Interpreter

PyTorch defines a new package torch. In this post we will consider the ._C module. This module is known as an "extension module" - a Python module written in C. Such modules allow us to define new built-in object types (e.g. the Tensor) and to call C/C++ functions.

Talks about Programming, Design, and Human Understanding

	# Based on https://github.com/kobigurk/circomlib/blob/feature/mimcsponge/circuits/mimcsponge.circom

	from sha3 import keccak_256


	SNARK_SCALAR_FIELD = 0x30644e72e131a029b85045b68181585d2833e84879b9709143e1f593f0000001
	DEFAULT_SEED = b"mimcsponge"
	DEFAULT_ROUNDS = 220
	DEFAULT_p = SNARK_SCALAR_FIELD

	// Copyright (c) 2018 HarryR
	// License: LGPL-3.0+

	pragma solidity ^0.5.0;

	/**
	* Implements MiMC-p/p over the altBN scalar field used by zkSNARKs
	*
	* See: https://eprint.iacr.org/2016/492.pdf
	*

	#!/bin/bash

	# install CUDA Toolkit v9.0
	# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb)
	CUDA_REPO_PKG="cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb"
	wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/${CUDA_REPO_PKG}
	sudo dpkg -i ${CUDA_REPO_PKG}
	sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
	sudo apt-get update
	sudo apt-get -y install cuda-9-0

	## bitwalletrecover.py - recover private keys from your darkcoin wallet
	## (this version was not tested with bitcoin/litecoin).
	## Requires python3, pycoin (https://pypi.python.org/pypi/pycoin),
	## and base58 (https://pypi.python.org/pypi/base58).
	##
	## Starting with Python 3.4, pip is included by default with the Python binary
	## installers. To install pip for older versions 3.x:
	##
	## sudo apt-get install python3-setuptools
	## sudo easy_install3 pip

	#!/usr/bin/env python3
	# coding=utf-8
	import json

	from ansible.executor.task_queue_manager import TaskQueueManager
	from ansible.inventory import Inventory
	from ansible.inventory.group import Group
	from ansible.inventory.host import Host
	from ansible.parsing.dataloader import DataLoader
	from ansible.playbook.play import Play

	# Required downloads:
	# NVIDIA-Linux-x86_64-367.27.run
	# cuda_8.0.27_linux.run
	# cudnn-8.0-linux-x64-v5.0-ga.tgz

	sudo apt-get install build-essential
	sudo apt-get install linux-image-extra-`uname -r`
	sudo ./NVIDIA-Linux-x86_64-367.27.run
	./cuda_8.0.27_linux.run --extract=`pwd`/extracts
	sudo ./extracts/cuda-linux64-rel-8.0.27-20733550.run

	import re
	import hashlib
	import base58
	from pycoin.ecdsa import generator_secp256k1, public_pair_for_secret_exponent

	def bytetohex(byteStr):
	return ''.join( [ "%02X" % x for x in byteStr ] ).strip()

	litecoin = [b"\x30", b"\xb0"]
	bitcoin = [b"\x00", b"\x80"]