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local SpatialColorTransform, parent = torch.class('nn.SpatialColorTransform', 'nn.Module')
local help_desc =
[[Provides a set of widely used/known color space transforms,
for images: RGB->YUV, YUV->RGB, RGB->Y transforms, and
more exotic transforms such as RGB->Normed-RGB]]
local help_example =
[[-- transforms an RGB image into a YUV image:
converter = nn.SpatialColorTransform('rgb2yuv')
rgb = image.lena()
yuv = converter:forward(rgb)
image.display(yuv) ]]
function SpatialColorTransform:__init(type)
-- parent init
parent.__init(self)
-- require the image package
xlua.require('image',true)
-- usage
self.usage = xlua.usage(
'nn.SpatialColorTransform', help_desc, help_example,
{type='string', req=true,
help='transform = yuv2rgb | rgb2yuv | rgb2y | hsl2rgb | hsv2rgb | rgb2hsl | rgb2hsv | rgb2nrgb | rgb2y+nrgb'}
)
-- transform type
self.transform = type
if type == 'yuv2rgb' then
self.islinear = true
self.linear = nn.SpatialLinear(3,3)
-- R
self.linear.weight[1][1] = 1
self.linear.weight[1][2] = 0
self.linear.weight[1][3] = 1.13983
self.linear.bias[1] = 0
-- G
self.linear.weight[2][1] = 1
self.linear.weight[2][2] = -0.39465
self.linear.weight[2][3] = -0.58060
self.linear.bias[2] = 0
-- B
self.linear.weight[3][1] = 1
self.linear.weight[3][2] = 2.03211
self.linear.weight[3][3] = 0
self.linear.bias[3] = 0
elseif type == 'rgb2yuv' then
self.islinear = true
self.linear = nn.SpatialLinear(3,3)
-- Y
self.linear.weight[1][1] = 0.299
self.linear.weight[1][2] = 0.587
self.linear.weight[1][3] = 0.114
self.linear.bias[1] = 0
-- U
self.linear.weight[2][1] = -0.14713
self.linear.weight[2][2] = -0.28886
self.linear.weight[2][3] = 0.436
self.linear.bias[2] = 0
-- V
self.linear.weight[3][1] = 0.615
self.linear.weight[3][2] = -0.51499
self.linear.weight[3][3] = -0.10001
self.linear.bias[3] = 0
elseif type == 'rgb2y' then
self.islinear = true
self.linear = nn.SpatialLinear(3,1)
-- Y
self.linear.weight[1][1] = 0.299
self.linear.weight[1][2] = 0.587
self.linear.weight[1][3] = 0.114
self.linear.bias[1] = 0
elseif type == 'hsl2rgb' then
self.islinear = false
elseif type == 'hsv2rgb' then
self.islinear = false
elseif type == 'rgb2hsl' then
self.islinear = false
elseif type == 'rgb2hsv' then
self.islinear = false
elseif type == 'rgb2nrgb' then
self.islinear = false
elseif type == 'rgb2y+nrgb' then
self.islinear = false
else
xlua.error('transform required','nn.SpatialColorTransform',self.usage)
end
end
function SpatialColorTransform:updateOutput(input)
if self.islinear then
self.output = self.linear:updateOutput(input)
else
if self.transform == 'rgb2hsl' then
self.output = image.rgb2hsl(input, self.output)
elseif self.transform == 'rgb2hsv' then
self.output = image.rgb2hsv(input, self.output)
elseif self.transform == 'hsl2rgb' then
self.output = image.hsl2rgb(input, self.output)
elseif self.transform == 'rgb2hsv' then
self.output = image.rgb2hsv(input, self.output)
elseif self.transform == 'rgb2nrgb' then
self.output = image.rgb2nrgb(input, self.output)
elseif self.transform == 'rgb2y+nrgb' then
self.output:resize(4, input:size(2), input:size(3))
image.rgb2y(input, self.output:narrow(1,1,1))
image.rgb2nrgb(input, self.output:narrow(1,2,3))
end
end
return self.output
end
function SpatialColorTransform:updateGradInput(input, gradOutput)
if self.islinear then
self.gradInput = self.linear:updateGradInput(input, gradOutput)
else
xlua.error('updateGradInput not implemented for non-linear transforms',
'SpatialColorTransform.updateGradInput')
end
return self.gradInput
end
function SpatialColorTransform:type(type)
parent.type(self,type)
if self.islinear then
self.linear:type(type)
end
end
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