bhive01

library(feather)

bhive01

R version 3.3.0 (2016-05-03) -- "Supposedly Educational"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin13.4.0 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

bhive01

import argparse
import trans #pip install trans
import time
import cv2
import math
import pandas as pd
import numpy as np

def distance(p, q):
	return math.sqrt(math.pow(math.fabs(p[0]-q[0]),2)+math.pow(math.fabs(p[1]-q[1]),2))

bhive01

import argparse
import cv2
import numpy as np

MIN_MATCH_COUNT = 10

ap = argparse.ArgumentParser()
ap.add_argument("-i1", "--trainimage", required = True, help = "Path to the image")
ap.add_argument("-i2", "--queryimage", required = True, help = "Path to the image")
args = vars(ap.parse_args())

bhive01

---
title: "testforcarson"
author: "Brandon Hurr"
date: "September 15, 2016"
output: html_document
---

```{r setup, eval = TRUE, echo = FALSE, warning = FALSE, message = FALSE, results='asis', out.width = 1000, out.height = 1000}
library(ggplot2)
library(dplyr)

bhive01

---
output:
  html_document:
    mathjax: null
    theme: null
    highlight: null
    pandoc_args: [
      "+RTS", "-K64m",
      "-RTS"
    ]

bhive01

library(tidyverse)

dt <- tibble(V1=c(1,2,4), V2=c("a","a","b"), V3=c(2,3,1))

swap_if<- function (condition, val1, val2, missing = NA) 
{
    if (!is.logical(condition)) {
        stop("`condition` must be logical", call. = FALSE)
    }
    out1 <- val1[rep(NA_integer_, length(condition))]

bhive01

import argparse
import trans #pip install trans
import time
import cv2
import math
import pandas as pd
import numpy as np
import zbar # sudo apt-get install libzbar-dev \ pip install zbar
from sklearn.neighbors import NearestNeighbors
from scipy.spatial.distance import squareform, pdist

bhive01

# Brandon Hurr
# Assumptions
#	1. Color card is Xrite Passport
#	2. Card is not mirrored
#	3. Only color calibration half of card is visible
#	4. When remove edges is selected at command line, the card is not at the edge of the image.
#	3. The scale factor is based upon median width of found objects (contours) that should be xrite squares, but could not be
#		could be problematic with lots of squares objects in image other than color card

import argparse

bhive01

import sys
import os.path
import trans #pip install trans
import time
import datetime
import cv2
import math
import pandas as pd
import numpy as np