Monero XMR mining via termux ;ubuntu
- install ubuntu in termux command; (ubuntu is optional)
pkg install update && upgrade
apt install git
apt install wget
apt install prootMonero XMR mining via termux ;ubuntu
pkg install update && upgrade
apt install git
apt install wget
apt install proot如果你想补充内容,建议优先给 free-for-dev 提PR,还能混个高星repo的contributor,没必要加到本列表里。
If you want to make improvements, I would recommend you contributing to free-for-dev rather than this list.
| #coding=utf8 | |
| import itchat | |
| # tuling plugin can be get here: | |
| # https://github.com/littlecodersh/EasierLife/tree/master/Plugins/Tuling | |
| from tuling import get_response | |
| @itchat.msg_register('Text') | |
| def text_reply(msg): | |
| if u'作者' in msg['Text'] or u'主人' in msg['Text']: | |
| return u'你可以在这里了解他:https://github.com/littlecodersh' |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| # coding: utf8 | |
| ''' | |
| 对于图片相似度比较有很多方法,我们这以RGB直方图为例。 | |
| 我们以一种规则,使得每个图片生成一组描述的特征向量。 | |
| opencv的直方图比较函数我们可以巧妙的利用,其有若干比较规则,但只支持直方图的数据结构,我们可以将特征向量拟合成直方图的数据结构,然后使用其的相似度比较函数。 | |
| 具体的数学计算方法有兴趣的可以看opencv的官方教程,这里我们期望生成百分比形式的相似度参数,所以使用CV_COMP_CORREL | |
| 以下是代码,以python编写 | |
| ''' | |
| import cv2.cv as cv |
Using Python's built-in defaultdict we can easily define a tree data structure:
def tree(): return defaultdict(tree)That's it!