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Capture live window data
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0
I would like to capture image data (like red, green, blue values for pixels) for a specified application window, and to do so periodically (like every 100 milliseconds) in R for the purpose of making a game bot. Ideally, I want the data to be directly read into a dataframe so it can immediately be used as input to a learning algorithm.
What are some suggested ways to do this? I am using R on Ubuntu linux.
r
edited Mar 25 at 7:18
Hector Haffenden
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
add a comment |
0
I would like to capture image data (like red, green, blue values for pixels) for a specified application window, and to do so periodically (like every 100 milliseconds) in R for the purpose of making a game bot. Ideally, I want the data to be directly read into a dataframe so it can immediately be used as input to a learning algorithm.
What are some suggested ways to do this? I am using R on Ubuntu linux.
r
edited Mar 25 at 7:18
Hector Haffenden
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30
add a comment |
0
0
0
I would like to capture image data (like red, green, blue values for pixels) for a specified application window, and to do so periodically (like every 100 milliseconds) in R for the purpose of making a game bot. Ideally, I want the data to be directly read into a dataframe so it can immediately be used as input to a learning algorithm.
What are some suggested ways to do this? I am using R on Ubuntu linux.
r
edited Mar 25 at 7:18
Hector Haffenden
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
I would like to capture image data (like red, green, blue values for pixels) for a specified application window, and to do so periodically (like every 100 milliseconds) in R for the purpose of making a game bot. Ideally, I want the data to be directly read into a dataframe so it can immediately be used as input to a learning algorithm.
What are some suggested ways to do this? I am using R on Ubuntu linux.
r
r
edited Mar 25 at 7:18
Hector Haffenden
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
edited Mar 25 at 7:18
Hector Haffenden
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
edited Mar 25 at 7:18
Hector Haffenden
916416
edited Mar 25 at 7:18
Hector Haffenden
916416
edited Mar 25 at 7:18
Hector Haffenden
916416
916416
asked Mar 24 at 19:01
silent_specsilent_spec
377
asked Mar 24 at 19:01
silent_specsilent_spec
377
asked Mar 24 at 19:01
silent_specsilent_spec
377
377
Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30
add a comment |
Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30
Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30
add a comment |
1 Answer
1
active
oldest
votes
3
First you would need to have a way to capture a screenshot and save it to a (temporary) file. The best way I found (using this and this) is using ImageMagick.
If you have ImageMagick installed, you can use the following R function/skript to capture the screen, load the data and plot the data in R (you might want to tweak the arguments based on your desired resolution etc.).
Lastly, if you want to do more with the image, I recommend the imager package.
Skript and load the image into R
library(imager) # for loading and plotting of the PNG file
library(glue) # for string parsing
capture_screen <- function(file = "screenshot.png")
system(glue("import -window root -resize 2560x1440 -delay 200 file"))
invisible(file)
file <- capture_screen()
shot <- load.image(file)
shot
#> Image. Width: 2560 pix Height: 1440 pix Depth: 1 Colour channels: 3
shot[1:10, 1:10, ]
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [2,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [3,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [4,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [5,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [6,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [7,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [8,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [9,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [10,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [2,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [3,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [4,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [5,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [6,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [7,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [8,] 0.3221790 0.3186389 0.3138781 0.3112840
#> [9,] 0.3221790 0.3186389 0.3138018 0.3109636
#> [10,] 0.3221942 0.3185931 0.3136797 0.3123674
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [2,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [3,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [4,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [5,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [6,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [7,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [8,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [9,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [10,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [2,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [3,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [4,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [5,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [6,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [7,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [8,] 0.3121691 0.3096513 0.3048905 0.3013352
#> [9,] 0.3121691 0.3096513 0.3048600 0.3008164
#> [10,] 0.3121996 0.3095750 0.3045701 0.3070420
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [2,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [3,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [4,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [5,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [6,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [7,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [8,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [9,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [10,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2829328
#> [,8] [,9] [,10]
#> [1,] 0.2799268 0.2769360 0.2740215
#> [2,] 0.2799268 0.2769360 0.2740215
#> [3,] 0.2799268 0.2769360 0.2740215
#> [4,] 0.2799268 0.2769360 0.2740215
#> [5,] 0.2799268 0.2769360 0.2740215
#> [6,] 0.2799268 0.2769360 0.2740215
#> [7,] 0.2799268 0.2769360 0.2740215
#> [8,] 0.2799268 0.2769360 0.2740215
#> [9,] 0.2799268 0.2769207 0.2734569
#> [10,] 0.2796063 0.2775616 0.2841840
Plot the image
plot(shot)
# render only a subset
imsub(shot, y <= 200, y >= 100, x <= 500, x >= 200) %>% plot()
Created on 2019-03-25 by the reprex package (v0.2.1)
Edit
If you only want to load the data without the screenshot.png file, you can also do
capture_screen2 <- function(xmin = 0, xmax = Inf, ymin = 0, ymax = Inf)
tmp <- tempfile(fileext = ".png")
system(glue("import -window root -resize 2560x1440 -delay 200 tmp"))
img <- load.image(tmp)
a <- try(unlink(tmp))
imsub(img, x >= xmin, x <= xmax, y >= ymin, y <= ymax)
shot <- capture_screen2()
Edit 2: Speed Issues
I did some benchmarking of the speed of the code, the fastest option is to use scrot (sudo apt install scrot on Ubuntu) in combination with the png package:
system(glue::glue("scrot --silent screenshot.png"))
img <- png::readPNG("screenshot.png")
dim(img)
answered Mar 25 at 7:45
DavidDavid
3,4862537
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
3
First you would need to have a way to capture a screenshot and save it to a (temporary) file. The best way I found (using this and this) is using ImageMagick.
If you have ImageMagick installed, you can use the following R function/skript to capture the screen, load the data and plot the data in R (you might want to tweak the arguments based on your desired resolution etc.).
Lastly, if you want to do more with the image, I recommend the imager package.
Skript and load the image into R
library(imager) # for loading and plotting of the PNG file
library(glue) # for string parsing
capture_screen <- function(file = "screenshot.png")
system(glue("import -window root -resize 2560x1440 -delay 200 file"))
invisible(file)
file <- capture_screen()
shot <- load.image(file)
shot
#> Image. Width: 2560 pix Height: 1440 pix Depth: 1 Colour channels: 3
shot[1:10, 1:10, ]
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [2,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [3,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [4,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [5,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [6,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [7,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [8,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [9,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [10,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [2,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [3,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [4,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [5,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [6,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [7,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [8,] 0.3221790 0.3186389 0.3138781 0.3112840
#> [9,] 0.3221790 0.3186389 0.3138018 0.3109636
#> [10,] 0.3221942 0.3185931 0.3136797 0.3123674
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [2,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [3,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [4,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [5,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [6,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [7,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [8,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [9,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [10,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [2,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [3,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [4,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [5,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [6,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [7,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [8,] 0.3121691 0.3096513 0.3048905 0.3013352
#> [9,] 0.3121691 0.3096513 0.3048600 0.3008164
#> [10,] 0.3121996 0.3095750 0.3045701 0.3070420
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [2,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [3,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [4,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [5,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [6,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [7,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [8,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [9,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [10,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2829328
#> [,8] [,9] [,10]
#> [1,] 0.2799268 0.2769360 0.2740215
#> [2,] 0.2799268 0.2769360 0.2740215
#> [3,] 0.2799268 0.2769360 0.2740215
#> [4,] 0.2799268 0.2769360 0.2740215
#> [5,] 0.2799268 0.2769360 0.2740215
#> [6,] 0.2799268 0.2769360 0.2740215
#> [7,] 0.2799268 0.2769360 0.2740215
#> [8,] 0.2799268 0.2769360 0.2740215
#> [9,] 0.2799268 0.2769207 0.2734569
#> [10,] 0.2796063 0.2775616 0.2841840
Plot the image
plot(shot)
# render only a subset
imsub(shot, y <= 200, y >= 100, x <= 500, x >= 200) %>% plot()
Created on 2019-03-25 by the reprex package (v0.2.1)
Edit
If you only want to load the data without the screenshot.png file, you can also do
capture_screen2 <- function(xmin = 0, xmax = Inf, ymin = 0, ymax = Inf)
tmp <- tempfile(fileext = ".png")
system(glue("import -window root -resize 2560x1440 -delay 200 tmp"))
img <- load.image(tmp)
a <- try(unlink(tmp))
imsub(img, x >= xmin, x <= xmax, y >= ymin, y <= ymax)
shot <- capture_screen2()
Edit 2: Speed Issues
I did some benchmarking of the speed of the code, the fastest option is to use scrot (sudo apt install scrot on Ubuntu) in combination with the png package:
system(glue::glue("scrot --silent screenshot.png"))
img <- png::readPNG("screenshot.png")
dim(img)
answered Mar 25 at 7:45
DavidDavid
3,4862537
add a comment |
3
First you would need to have a way to capture a screenshot and save it to a (temporary) file. The best way I found (using this and this) is using ImageMagick.
If you have ImageMagick installed, you can use the following R function/skript to capture the screen, load the data and plot the data in R (you might want to tweak the arguments based on your desired resolution etc.).
Lastly, if you want to do more with the image, I recommend the imager package.
Skript and load the image into R
library(imager) # for loading and plotting of the PNG file
library(glue) # for string parsing
capture_screen <- function(file = "screenshot.png")
system(glue("import -window root -resize 2560x1440 -delay 200 file"))
invisible(file)
file <- capture_screen()
shot <- load.image(file)
shot
#> Image. Width: 2560 pix Height: 1440 pix Depth: 1 Colour channels: 3
shot[1:10, 1:10, ]
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [2,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [3,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [4,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [5,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [6,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [7,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [8,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [9,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [10,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [2,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [3,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [4,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [5,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [6,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [7,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [8,] 0.3221790 0.3186389 0.3138781 0.3112840
#> [9,] 0.3221790 0.3186389 0.3138018 0.3109636
#> [10,] 0.3221942 0.3185931 0.3136797 0.3123674
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [2,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [3,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [4,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [5,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [6,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [7,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [8,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [9,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [10,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [2,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [3,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [4,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [5,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [6,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [7,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [8,] 0.3121691 0.3096513 0.3048905 0.3013352
#> [9,] 0.3121691 0.3096513 0.3048600 0.3008164
#> [10,] 0.3121996 0.3095750 0.3045701 0.3070420
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [2,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [3,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [4,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [5,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [6,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [7,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [8,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [9,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [10,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2829328
#> [,8] [,9] [,10]
#> [1,] 0.2799268 0.2769360 0.2740215
#> [2,] 0.2799268 0.2769360 0.2740215
#> [3,] 0.2799268 0.2769360 0.2740215
#> [4,] 0.2799268 0.2769360 0.2740215
#> [5,] 0.2799268 0.2769360 0.2740215
#> [6,] 0.2799268 0.2769360 0.2740215
#> [7,] 0.2799268 0.2769360 0.2740215
#> [8,] 0.2799268 0.2769360 0.2740215
#> [9,] 0.2799268 0.2769207 0.2734569
#> [10,] 0.2796063 0.2775616 0.2841840
Plot the image
plot(shot)
# render only a subset
imsub(shot, y <= 200, y >= 100, x <= 500, x >= 200) %>% plot()
Created on 2019-03-25 by the reprex package (v0.2.1)
Edit
If you only want to load the data without the screenshot.png file, you can also do
capture_screen2 <- function(xmin = 0, xmax = Inf, ymin = 0, ymax = Inf)
tmp <- tempfile(fileext = ".png")
system(glue("import -window root -resize 2560x1440 -delay 200 tmp"))
img <- load.image(tmp)
a <- try(unlink(tmp))
imsub(img, x >= xmin, x <= xmax, y >= ymin, y <= ymax)
shot <- capture_screen2()
Edit 2: Speed Issues
I did some benchmarking of the speed of the code, the fastest option is to use scrot (sudo apt install scrot on Ubuntu) in combination with the png package:
system(glue::glue("scrot --silent screenshot.png"))
img <- png::readPNG("screenshot.png")
dim(img)
answered Mar 25 at 7:45
DavidDavid
3,4862537
add a comment |
3
3
3
First you would need to have a way to capture a screenshot and save it to a (temporary) file. The best way I found (using this and this) is using ImageMagick.
If you have ImageMagick installed, you can use the following R function/skript to capture the screen, load the data and plot the data in R (you might want to tweak the arguments based on your desired resolution etc.).
Lastly, if you want to do more with the image, I recommend the imager package.
Skript and load the image into R
library(imager) # for loading and plotting of the PNG file
library(glue) # for string parsing
capture_screen <- function(file = "screenshot.png")
system(glue("import -window root -resize 2560x1440 -delay 200 file"))
invisible(file)
file <- capture_screen()
shot <- load.image(file)
shot
#> Image. Width: 2560 pix Height: 1440 pix Depth: 1 Colour channels: 3
shot[1:10, 1:10, ]
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [2,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [3,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [4,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [5,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [6,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [7,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [8,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [9,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [10,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [2,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [3,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [4,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [5,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [6,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [7,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [8,] 0.3221790 0.3186389 0.3138781 0.3112840
#> [9,] 0.3221790 0.3186389 0.3138018 0.3109636
#> [10,] 0.3221942 0.3185931 0.3136797 0.3123674
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [2,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [3,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [4,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [5,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [6,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [7,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [8,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [9,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [10,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [2,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [3,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [4,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [5,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [6,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [7,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [8,] 0.3121691 0.3096513 0.3048905 0.3013352
#> [9,] 0.3121691 0.3096513 0.3048600 0.3008164
#> [10,] 0.3121996 0.3095750 0.3045701 0.3070420
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [2,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [3,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [4,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [5,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [6,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [7,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [8,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [9,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [10,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2829328
#> [,8] [,9] [,10]
#> [1,] 0.2799268 0.2769360 0.2740215
#> [2,] 0.2799268 0.2769360 0.2740215
#> [3,] 0.2799268 0.2769360 0.2740215
#> [4,] 0.2799268 0.2769360 0.2740215
#> [5,] 0.2799268 0.2769360 0.2740215
#> [6,] 0.2799268 0.2769360 0.2740215
#> [7,] 0.2799268 0.2769360 0.2740215
#> [8,] 0.2799268 0.2769360 0.2740215
#> [9,] 0.2799268 0.2769207 0.2734569
#> [10,] 0.2796063 0.2775616 0.2841840
Plot the image
plot(shot)
# render only a subset
imsub(shot, y <= 200, y >= 100, x <= 500, x >= 200) %>% plot()
Created on 2019-03-25 by the reprex package (v0.2.1)
Edit
If you only want to load the data without the screenshot.png file, you can also do
capture_screen2 <- function(xmin = 0, xmax = Inf, ymin = 0, ymax = Inf)
tmp <- tempfile(fileext = ".png")
system(glue("import -window root -resize 2560x1440 -delay 200 tmp"))
img <- load.image(tmp)
a <- try(unlink(tmp))
imsub(img, x >= xmin, x <= xmax, y >= ymin, y <= ymax)
shot <- capture_screen2()
Edit 2: Speed Issues
I did some benchmarking of the speed of the code, the fastest option is to use scrot (sudo apt install scrot on Ubuntu) in combination with the png package:
system(glue::glue("scrot --silent screenshot.png"))
img <- png::readPNG("screenshot.png")
dim(img)
answered Mar 25 at 7:45
DavidDavid
3,4862537
First you would need to have a way to capture a screenshot and save it to a (temporary) file. The best way I found (using this and this) is using ImageMagick.
If you have ImageMagick installed, you can use the following R function/skript to capture the screen, load the data and plot the data in R (you might want to tweak the arguments based on your desired resolution etc.).
Lastly, if you want to do more with the image, I recommend the imager package.
Skript and load the image into R
library(imager) # for loading and plotting of the PNG file
library(glue) # for string parsing
capture_screen <- function(file = "screenshot.png")
system(glue("import -window root -resize 2560x1440 -delay 200 file"))
invisible(file)
file <- capture_screen()
shot <- load.image(file)
shot
#> Image. Width: 2560 pix Height: 1440 pix Depth: 1 Colour channels: 3
shot[1:10, 1:10, ]
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [2,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [3,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [4,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [5,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [6,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [7,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [8,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [9,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [10,] 0.3440452 0.3385519 0.3357443 0.3331807 0.3284199 0.3248798
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [2,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [3,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [4,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [5,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [6,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [7,] 0.3221790 0.3186389 0.3138781 0.3112993
#> [8,] 0.3221790 0.3186389 0.3138781 0.3112840
#> [9,] 0.3221790 0.3186389 0.3138018 0.3109636
#> [10,] 0.3221942 0.3185931 0.3136797 0.3123674
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [2,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [3,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [4,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [5,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [6,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [7,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [8,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [9,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [10,] 0.3319905 0.3292439 0.3244831 0.3209583 0.3181506 0.3152209
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [2,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [3,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [4,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [5,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [6,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [7,] 0.3121691 0.3096513 0.3048905 0.3013504
#> [8,] 0.3121691 0.3096513 0.3048905 0.3013352
#> [9,] 0.3121691 0.3096513 0.3048600 0.3008164
#> [10,] 0.3121996 0.3095750 0.3045701 0.3070420
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [2,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [3,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [4,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [5,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [6,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [7,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [8,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [9,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2828412
#> [10,] 0.300679 0.2975357 0.2945907 0.2916915 0.2887007 0.2857862 0.2829328
#> [,8] [,9] [,10]
#> [1,] 0.2799268 0.2769360 0.2740215
#> [2,] 0.2799268 0.2769360 0.2740215
#> [3,] 0.2799268 0.2769360 0.2740215
#> [4,] 0.2799268 0.2769360 0.2740215
#> [5,] 0.2799268 0.2769360 0.2740215
#> [6,] 0.2799268 0.2769360 0.2740215
#> [7,] 0.2799268 0.2769360 0.2740215
#> [8,] 0.2799268 0.2769360 0.2740215
#> [9,] 0.2799268 0.2769207 0.2734569
#> [10,] 0.2796063 0.2775616 0.2841840
Plot the image
plot(shot)
# render only a subset
imsub(shot, y <= 200, y >= 100, x <= 500, x >= 200) %>% plot()
Created on 2019-03-25 by the reprex package (v0.2.1)
Edit
If you only want to load the data without the screenshot.png file, you can also do
capture_screen2 <- function(xmin = 0, xmax = Inf, ymin = 0, ymax = Inf)
tmp <- tempfile(fileext = ".png")
system(glue("import -window root -resize 2560x1440 -delay 200 tmp"))
img <- load.image(tmp)
a <- try(unlink(tmp))
imsub(img, x >= xmin, x <= xmax, y >= ymin, y <= ymax)
shot <- capture_screen2()
Edit 2: Speed Issues
I did some benchmarking of the speed of the code, the fastest option is to use scrot (sudo apt install scrot on Ubuntu) in combination with the png package:
system(glue::glue("scrot --silent screenshot.png"))
img <- png::readPNG("screenshot.png")
dim(img)
answered Mar 25 at 7:45
DavidDavid
3,4862537
edited Mar 26 at 8:49
answered Mar 25 at 7:45
DavidDavid
3,4862537
answered Mar 25 at 7:45
DavidDavid
3,4862537
answered Mar 25 at 7:45
DavidDavid
3,4862537
3,4862537
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Is it correct to assume your data is stored in the form of say an image on your computer? And this image may change, say every 100 milliseconds, Or do you have lots of different images? Or is it not stored as an image, but rather an excel filed? Or.... you see where this is going.....
– Hector Haffenden
Mar 24 at 19:19
The data should be in the form of an image. I don't intend to 'store' anything as in save it to a file to disk, but if this is inevitable then I would prefer your first scenario where the same image changes rather than storing many images.
– silent_spec
Mar 24 at 21:26
Maybe there is another way, one way would be to store this image, read it into r, do what analysis u want, then overwrite the image etc... Although, this doesn't sound fast enough for your application. If you can store the images as a data frame, this will increase speed, but again unsure of specifics in your case.
– Hector Haffenden
Mar 24 at 21:30