DataAugmentation
We first define the
Image item. Since we need to keep track of the spatial bounds for projective transformations we add them as a field. By default, they will simply correspond to the image axes.
"""
Image(image[, bounds])
Item representing an N-dimensional image with element type T.
## Examples
{cell=image}
```julia
using DataAugmentation, Images
imagedata = rand(RGB, 100, 100)
item = Image(imagedata)
showitems(item)
```
If `T` is not a color, the image will be interpreted as grayscale:
{cell=image}
```julia
imagedata = rand(Float32, 100, 100)
item = Image(imagedata)
showitems(item)
```
"""
struct
Image
{
N
,
T
}
<:
AbstractArrayItem
{
N
,
T
}
data
::
AbstractArray
{
T
,
N
}
bounds
::
Bounds
{
N
}
end
Image
(
data
)
=
Image
(
data
,
Bounds
(
axes
(
data
)
)
)
function
Image
(
data
::
AbstractArray
{
T
,
N
}
,
sz
::
NTuple
{
N
,
Int
}
)
where
{
T
,
N
}
return
Image
(
data
,
Bounds
(
sz
)
)
end
Base
.
show
(
io
::
IO
,
item
::
Image
{
N
,
T
}
)
where
{
N
,
T
}
=
print
(
io
,
"
Image{
$
N
,
$
T
}() with bounds
$
(
item
.
bounds
)
"
)
function
showitem!
(
img
,
image
::
Image
{
2
,
<:
Colorant
}
)
showimage!
(
img
,
itemdata
(
image
)
)
end
function
showitem!
(
img
,
image
::
Image
{
2
,
<:
AbstractFloat
}
)
return
showimage!
(
img
,
colorview
(
Gray
,
itemdata
(
image
)
)
)
end
getbounds
(
image
::
Image
)
=
image
.
bounds
For the projection, we use
warp from
ImageTransformations.jl
. We have to pass the inverse of the projection
P as it uses backward mode warping.
function
project
(
P
,
image
::
Image
{
N
,
T
}
,
bounds
::
Bounds
)
where
{
N
,
T
}
# TODO: make interpolation scheme and boundary conditions configurable
data_
=
warp
(
itemdata
(
image
)
,
inv
(
P
)
,
bounds
.
rs
;
fillvalue
=
zero
(
T
)
)
return
Image
(
data_
,
bounds
)
end
The inplace version
project! is quite similar. Note
indices are not needed as they are implicitly given by the buffer.
function
project!
(
bufimage
::
Image
,
P
,
image
::
Image
{
N
,
T
}
,
bounds
::
Bounds
{
N
}
)
where
{
N
,
T
}
a
=
OffsetArray
(
parent
(
itemdata
(
bufimage
)
)
,
bounds
.
rs
)
res
=
warp!
(
a
,
box_extrapolation
(
itemdata
(
image
)
;
fillvalue
=
zero
(
T
)
)
,
inv
(
P
)
,
)
return
Image
(
res
,
bounds
)
end