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@n1k0
n1k0 / gist:1501173
Created December 20, 2011 10:44 — forked from fbuchinger/gist:1501115
PhantomJS: Capturing single dom elements as png files
var page = new WebPage(),
address, output, size;
//capture and captureSelector functions adapted from CasperJS - https://github.com/n1k0/casperjs
capture = function(targetFile, clipRect) {
var previousClipRect;
var clipRect = {top: 0, left:0, width: 40, height: 40};
if (clipRect) {
if (!isType(clipRect, "object")) {
throw new Error("clipRect must be an Object instance.");
@luw2007
luw2007 / 词性标记.md
Last active May 29, 2024 20:18
词性标记: 包含 ICTPOS3.0词性标记集、ICTCLAS 汉语词性标注集、jieba 字典中出现的词性、simhash 中可以忽略的部分词性

词的分类

  • 实词:名词、动词、形容词、状态词、区别词、数词、量词、代词
  • 虚词:副词、介词、连词、助词、拟声词、叹词。

ICTPOS3.0词性标记集

n 名词

nr 人名

@bsweger
bsweger / useful_pandas_snippets.md
Last active April 19, 2024 18:04
Useful Pandas Snippets

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

@st-j
st-j / date_conversion.cpp
Created August 23, 2014 21:46
Convert between boost dates and Unix timestamps (time_t)
#include <ctime>
#include <iostream>
#include <boost/date_time/gregorian/gregorian.hpp>
#include <boost/date_time/posix_time/posix_time.hpp>
//==============================================================================
//! Convert date part of Unix timestamp (time_t) to boost date
//!
@songron
songron / weibo_login_with_cookie.py
Created December 18, 2014 14:25
Simulate Weibo Login
@colah
colah / translations.md
Last active December 28, 2019 06:31
A list of translations of posts from colah.github.io
@danijar
danijar / blog_tensorflow_scope_decorator.py
Last active January 17, 2023 01:58
TensorFlow Scope Decorator
# Working example for my blog post at:
# https://danijar.github.io/structuring-your-tensorflow-models
import functools
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
def doublewrap(function):
"""
A decorator decorator, allowing to use the decorator to be used without
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.datasets import fetch_20newsgroups
from sklearn.decomposition import NMF, LatentDirichletAllocation
def display_topics(model, feature_names, no_top_words):
for topic_idx, topic in enumerate(model.components_):
print "Topic %d:" % (topic_idx)
print " ".join([feature_names[i]
for i in topic.argsort()[:-no_top_words - 1:-1]])
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.datasets import fetch_20newsgroups
from sklearn.decomposition import NMF, LatentDirichletAllocation
import numpy as np
def display_topics(H, W, feature_names, documents, no_top_words, no_top_documents):
for topic_idx, topic in enumerate(H):
print "Topic %d:" % (topic_idx)
print " ".join([feature_names[i]
for i in topic.argsort()[:-no_top_words - 1:-1]])
@asimshankar
asimshankar / export.py
Created June 20, 2017 00:17
Keras Models --> TensorFlow SavedModel format
# Mostly copied from https://keras.io/applications/#usage-examples-for-image-classification-models
# Changing it to use InceptionV3 instead of ResNet50
from keras.applications.inception_v3 import InceptionV3, preprocess_input, decode_predictions
from keras.preprocessing import image
import numpy as np
model = InceptionV3()
img_path = 'elephant.jpg'