I\'m currently working on a case study for which I need to work on the MNIST database.
The files in this site are said to be in IDX file format. I tried to take a look at th
endian="big"
, not "high"
:
> to.read = file("~/Downloads/t10k-images-idx3-ubyte", "rb")
magic number:
> readBin(to.read, integer(), n=1, endian="big")
[1] 2051
number of images:
> readBin(to.read, integer(), n=1, endian="big")
[1] 10000
number of rows:
> readBin(to.read, integer(), n=1, endian="big")
[1] 28
number of columns:
> readBin(to.read, integer(), n=1, endian="big")
[1] 28
here comes the data:
> readBin(to.read, integer(), n=1, endian="big")
[1] 0
> readBin(to.read, integer(), n=1, endian="big")
[1] 0
as per the training set image data description on the web site.
Now you just need to loop and read 28*28 byte chunks into matrices.
Start again:
> to.read = file("~/Downloads/t10k-images-idx3-ubyte", "rb")
skip header:
> readBin(to.read, integer(), n=4, endian="big")
[1] 2051 10000 28 28
should really get the 28,28 from the header read but hard-coded here:
> m = matrix(readBin(to.read,integer(), size=1, n=28*28, endian="big"),28,28)
> image(m)
Might need to transpose or flip the matrix, I think its an upside-down "7".
par(mfrow=c(5,5))
par(mar=c(0,0,0,0))
for(i in 1:25){m = matrix(readBin(to.read,integer(), size=1, n=28*28, endian="big"),28,28);image(m[,28:1])}
gets you:
Oh, and google leads me to: http://www.inside-r.org/packages/cran/darch/docs/readMNIST which might be useful.