In MartinRoth/visDec: Visibility Detection from Cameras

knitr::opts_chunk$set(
  fig.width  = 7,
  fig.height = 4
)

Example how to use visDec

Load required libaries

library(imager)
library(data.table)
library(ggplot2)
library(visDec)
library(foreach)
library(iterators)
library(doParallel)
registerDoParallel(cores=2)

Read example pictures

path <- system.file("extdata/Meetterrein", package="visDec")
filenames <- list.files(path,
                        pattern=glob2rx("Meetterrein_201510*.jpg"),
                        full.names=TRUE)
#```r
imageSummary <- foreach(file = iter(filenames), .combine = rbind) %dopar% {
  FileNameParser(file, "na*me_yyyymmdd_hhmm.jpg")
}

properties <- fread(system.file("extdata/properties.csv", package="visDec"))

setkey(imageSummary, filePrefix, dateTime)

imageSummary <- merge(imageSummary, properties,
                      by.x = "filePrefix", by.y = "filePrefix")

daylightImages <- imageSummary[IsDayLightImage(dateTime, lon, lat), ]

invisible(daylightImages[, id := 1:.N])
setkey(daylightImages, id)

imageFeatures <- foreach(id = iter(daylightImages[, id]), .combine = rbind) %dopar% {
  daylightImages[id, ImageFeatures(filePath, y > 16)]
}

setkey(daylightImages, filePath)
setkey(imageFeatures, filePath)

imageSummary <- merge(daylightImages, imageFeatures)

Edges in a clear situation

im <- subim(load.image(filenames[75]), y > 16)
old_par <- par(mfrow=c(1,2))
plot(im)
DetectEdges(im) %>% plot
par(old_par)

Edges in a foggy situation

im <- subim(load.image(filenames[49]), y > 16)
old_par <- par(mfrow=c(1,2))
plot(im)
DetectEdges(im) %>% plot
par(old_par)

Load sensor values

path <- system.file("extdata/Sensor", package="visDec")
sensorFiles <- list.files(path,
                          pattern=glob2rx("DeBilt*.csv"),
                          full.names=TRUE)
sensorData <- ReadMORSensorData(sensorFiles)
setkey(sensorData, dateTime)
setkey(imageSummary, dateTime)
imageSummary <- merge(imageSummary, sensorData)
invisible(imageSummary[, MOR := TOA.MOR_10]) # see .e.g https://github.com/rstudio/rmarkdown/issues/829

Time series

ggplot(imageSummary, aes(x = dateTime, y = mean_edge)) + geom_line() + xlab("")
ggplot(imageSummary, aes(x = dateTime, y= MOR)) + geom_line() +
  xlab("") 
ggplot(imageSummary,
       aes(x = dateTime, y = fractal_dim)) + geom_line() + xlab("")

ggplot(imageSummary[hour(dateTime) %in% seq(5, 10, by=1), ],
       aes(x = dateTime, y = mean_edge)) + geom_line() + xlab("")
ggplot(imageSummary[hour(dateTime) %in% seq(5, 10, by=1), ],
       aes(x = dateTime, y = fractal_dim)) + geom_line() + xlab("")

Scatter plots

invisible(imageSummary[, visibility := factor(2000)])
invisible(imageSummary[MOR < 1000, visibility := factor(1000)])
invisible(imageSummary[MOR < 500, visibility := factor(500)])
invisible(imageSummary[MOR < 200, visibility := factor(200)])
#ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(FS261), y = meanEdge, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = mean_edge, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = change_point, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = smoothness, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = fractal_dim, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = mean_hue, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = mean_saturation, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = mean_brightness, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)
ggplot(imageSummary[hour %in% seq(7, 16, by = 1), ], aes(x = log(MOR), y = mean_transmission, col = visibility)) + geom_point() + geom_quantile(aes(col=NULL), quantiles=0.5)