| library(httr) | |
| library(devtools) | |
| # make httr set CURL to ignore SSL verification problems | |
| # (needed if the SSL proxy replaces certs with its own) | |
| set_config(config(ssl.verifypeer = 0L)) | |
| # set proxy details | |
| set_config(use_proxy("10.10.10.10",8080)) |
The Leaflet JS mapping library has lots of plugins available. The Leaflet package for R provides direct support for some, but far from all, of these plugins, by providing R functions for invoking the plugins.
If you as an R user find yourself wanting to use a Leaflet plugin that isn't directly supported in the R package, you can use the technique shown here to load the plugin yourself and invoke it using JS code.
| import shapefile | |
| # read the shapefile | |
| reader = shapefile.Reader("my.shp") | |
| fields = reader.fields[1:] | |
| field_names = [field[0] for field in fields] | |
| buffer = [] | |
| for sr in reader.shapeRecords(): | |
| atr = dict(zip(field_names, sr.record)) | |
| geom = sr.shape.__geo_interface__ | |
| buffer.append(dict(type="Feature", \ |
| import fiona | |
| import fiona.crs | |
| def convert(f_in, f_out): | |
| with fiona.open(f_in) as source: | |
| with fiona.open( | |
| f_out, | |
| 'w', | |
| driver='GeoJSON', | |
| crs = fiona.crs.from_epsg(4326), |
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.
On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:
####### 1. A low-resolution photo of road signs
| # Installing TOR on mac: brew install tor | |
| # Run TOR on custom port: tor --SOCKSPort 9050 | |
| # Check the 'origin' field in the response to verify TOR is working. | |
| library(httr) | |
| GET("https://httpbin.org/get", use_proxy("socks5://localhost:9050")) | |
| # Set proxy in curl | |
| library(curl) | |
| h <- new_handle(proxy = "socks5://localhost:9050") |
| // | |
| // _oo0oo_ | |
| // o8888888o | |
| // 88" . "88 | |
| // (| -_- |) | |
| // 0\ = /0 | |
| // ___/`---'\___ | |
| // .' \\| |// '. | |
| // / \\||| : |||// \ | |
| // / _||||| -:- |||||- \ |
| library(shiny) | |
| library(datasets) | |
| Logged = FALSE; | |
| PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad") | |
| # Define server logic required to summarize and view the selected dataset | |
| shinyServer(function(input, output) { | |
| source("www/Login.R", local = TRUE) | |
| observe({ | |
| if (USER$Logged == TRUE) { |
| #! /bin/bash | |
| # | |
| # backup_redmine.sh | |
| # modified by [email protected] | |
| # Inspiration: https://gist.github.com/gabrielkfr/6432185 | |
| # | |
| # Distributed under terms of the MIT license. | |
| # -- VARS | |
| DAY=`date +"%Y%m%d"` |
