# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages
# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats
# For example, here's several helpful packages to load in 

library(ggplot2) # Data visualization
library(readr) # CSV file I/O, e.g. the read_csv function
library(jpeg)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

system("ls ../input")

# Any results you write to the current directory are saved as output.

#list.files("../input/train/c0/")
c0img = readJPEG("../input/train/c0/img_100026.jpg")
#rasterImage(c0img, 1.2, 1.27, 1.8, 1.73)
str(c0img)
summary(c0img)
# table(c0img)
typeof(c0img)

driverlist = read_csv("../input/driver_imgs_list.csv")

# str(driverlist)
# head(driverlist)
# table(driverlist$subject)