I have a series of images (.tiff) that are only georeference at the true centroid of the picture. I have calculated the missing coordinates (top right, top left, bottom right and bottom left) in the X and Y plain, and now I will like to write those coordinates in each image. 

In order to do that, I was told that the `exifr` package in R has a function call `exiftool_call` that could be helpful to complete that task. I have tried different things, but they don't seem to be working, so I was wondering if anyone knows how to accomplish this task using `exiftool_call` 

Here is what I have tried so far:

    coordinates.data<-read.csv("...",header=TRUE)
    
    list.pics <- list.files(path ="...",pattern = "*.tif",full.names = TRUE)
     
    exiftool_call(args = coordinates.data, fnames = list.pics)  
    
    exiftool_call(args = c(coordinates.data$TopLeftx,coordinates.data$TopLefty,coordinates.data$TopRightx,
                          coordinates.data$TopRighty,coordinates.data$BottomLeftx,coordinates.data$BottomLefty,
                          coordinates.data$BottomRightx,coordinates.data$BottomRighty),fnames = list.pics)
    
    exiftool_call(args = c("coordinates.data$TopLeftx","coordinates.data$TopLefty","coordinates.data$TopRightx",
                           "coordinates.data$TopRighty","coordinates.data$BottomLeftx","coordinates.data$BottomLefty",
                           "coordinates.data$BottomRightx","coordinates.data$BottomRighty"),fnames = list.pics)

Output `str(coordinates.data)`

    'data.frame':	5 obs. of  16 variables:
     $ X                          : int  1 2 3 4 5
     $ meta.df.FileName           : Factor w/ 5 levels "IMG_0000_1.tif",..: 1 2 3 4 5
     $ meta.df.FileInodeChangeDate: Factor w/ 3 levels "2018:07:11 14:16:48-05:00",..: 1 3 1 2 2
     $ meta.df.BandName           : Factor w/ 5 levels "Blue","Green",..: 1 2 4 3 5
     $ coorMetric.lon             : num  329878 329878 329878 329878 329878
     $ coorMetric.lat             : num  4057023 4057023 4057023 4057023 4057023
     $ ImageWidth                 : num  88.8 88.8 88.8 88.8 88.8
     $ ImageHeight                : num  66.7 66.7 66.7 66.7 66.7
     $ TopLeftx                   : num  329833 329833 329833 329833 329833
     $ TopLefty                   : num  4057056 4057056 4057056 4057056 4057056
     $ TopRightx                  : num  329922 329922 329922 329922 329922
     $ TopRighty                  : num  4057056 4057056 4057056 4057056 4057056
     $ BottomLeftx                : num  329833 329833 329833 329833 329833
     $ BottomLefty                : num  4056989 4056989 4056989 4056989 4056989
     $ BottomRightx               : num  329922 329922 329922 329922 329922
     $ BottomRighty        

       : num  4056989 4056989 4056989 4056989 4056989

One File Example 

    one.Image<-read_exif(path = "...")
    one.Image
    
    coordinate.one.Image<-read.csv("...", header = TRUE)
    head(coordinate.one.Image)
    
    exiftool_call(args = coordinate.one.Image, fnames = one.Image) 

Output str(coordinate.one.Image)

    'data.frame':	1 obs. of  15 variables:
     $ meta.df.FileName           : Factor w/ 1 level "IMG_0001_1.tif": 1
     $ meta.df.FileInodeChangeDate: Factor w/ 1 level "2018:07:11 14:16:49-05:00": 1
     $ meta.df.BandName           : Factor w/ 1 level "Blue": 1
     $ coorMetric.lon             : num 329860
     $ coorMetric.lat             : num 4056981
     $ ImageWidth                 : num 88.8
     $ ImageHeight                : num 66.7
     $ TopLeftx                   : num 329815
     $ TopLefty                   : num 4057015
     $ TopRightx                  : num 329904
     $ TopRighty                  : num 4057015
     $ BottomLeftx                : num 329815
     $ BottomLefty                : num 4056948
     $ BottomRightx               : num 329904
     $ BottomRighty               : num 4056948