mnist

REQUIRE

@@ -6,3 +6,5 @@ NNlib
 ForwardDiff 0.5.0
 Requires
 Adapt
+GZip
+Colors

src/data/Data.jl

@@ -8,6 +8,7 @@ function __init__()
   mkpath(deps())
 end
 
+include("mnist.jl")
 include("cmudict.jl")
 using .CMUDict
 

src/data/mnist.jl

@@ -0,0 +1,84 @@
+module MNIST
+
+using GZip, Colors
+
+const Gray = Colors.Gray{Colors.N0f8}
+
+const dir = joinpath(@__DIR__, "../../deps/mnist")
+
+function load()
+  mkpath(dir)
+  cd(dir) do
+    for file in ["train-images-idx3-ubyte",
+                 "train-labels-idx1-ubyte",
+                 "t10k-images-idx3-ubyte",
+                 "t10k-labels-idx1-ubyte"]
+      isfile(file) && continue
+      download("http://yann.lecun.com/exdb/mnist/$file.gz", "$file.gz")
+      open(file, "w") do io
+        write(io, GZip.open(read, "$file.gz"))
+      end
+    end
+  end
+end
+
+const IMAGEOFFSET = 16
+const LABELOFFSET = 8
+
+const NROWS = 28
+const NCOLS = 28
+
+const TRAINIMAGES = joinpath(dir, "train-images-idx3-ubyte")
+const TRAINLABELS = joinpath(dir, "train-labels-idx1-ubyte")
+const TESTIMAGES = joinpath(dir, "t10k-images-idx3-ubyte")
+const TESTLABELS = joinpath(dir, "t10k-labels-idx1-ubyte")
+
+function imageheader(io::IO)
+  magic_number = bswap(read(io, UInt32))
+  total_items = bswap(read(io, UInt32))
+  nrows = bswap(read(io, UInt32))
+  ncols = bswap(read(io, UInt32))
+  return magic_number, Int(total_items), Int(nrows), Int(ncols)
+end
+
+function labelheader(io::IO)
+  magic_number = bswap(read(io, UInt32))
+  total_items = bswap(read(io, UInt32))
+  return magic_number, Int(total_items)
+end
+
+function rawimage(io::IO)
+  img = Array{Gray}(NCOLS, NROWS)
+  for i in 1:NCOLS, j in 1:NROWS
+    img[i, j] = reinterpret(Colors.N0f8, read(io, UInt8))
+  end
+  return img
+end
+
+function rawimage(io::IO, index::Integer)
+  seek(io, IMAGEOFFSET + NROWS * NCOLS * (index - 1))
+  return rawimage(io)
+end
+
+rawlabel(io::IO) = Int(read(io, UInt8))
+
+function rawlabel(io::IO, index::Integer)
+  seek(io, LABELOFFSET + (index - 1))
+  return rawlabel(io)
+end
+
+getfeatures(io::IO, index::Integer) = vec(getimage(io, index))
+
+function images(set = :train)
+  io = IOBuffer(read(set == :train ? TRAINIMAGES : TESTIMAGES))
+  _, N, nrows, ncols = imageheader(io)
+  [rawimage(io) for _ in 1:N]
+end
+
+function labels(set = :train)
+  io = IOBuffer(read(set == :train ? TRAINLABELS : TESTLABELS))
+  _, N = labelheader(io)
+  [rawlabel(io) for _ = 1:N]
+end
+
+end # module