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Use original colors in an image generated by fast-neural-style
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-- this program takes an original image, such as a photo, | |
-- and a generated image, such as generated by jcjohnson/fast-neural-style | |
-- and copies the original colors to the generated image | |
-- like when using the original_colors param in jcjohnson/neural-style | |
-- | |
-- by hannu töyrylä @htoyryla 30 oct 2016 | |
-- | |
require 'torch' | |
require 'image' | |
local cmd = torch.CmdLine() | |
cmd:option('-generated_image', '', | |
'Image to copy colors to') | |
cmd:option('-original_image', '', | |
'Image to copy colors from') | |
cmd:option('-output_image', 'out.png') | |
local function main(params) | |
local generated_image = image.load(params.generated_image, 3) | |
local oimg = image.load(params.original_image, 3) | |
local original_image = image.scale(oimg, generated_image:size(3), generated_image:size(2)) | |
disp = original_colors(original_image, generated_image) | |
image.save(params.output_image, disp) | |
end | |
function original_colors(content, generated) | |
local generated_y = image.rgb2yuv(generated)[{{1, 1}}] | |
local content_uv = image.rgb2yuv(content)[{{2, 3}}] | |
return image.yuv2rgb(torch.cat(generated_y, content_uv, 1)) | |
end | |
local params = cmd:parse(arg) | |
main(params) |
Maybe I should experiment a bit with blending the channels. I'll keep this in mind.
Do you have this code in python?
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@tkoham, what this script does is so simple that I don't see much benefit adding gpu acceleration. Taking slices of two tensors and concatenating them. No actual computation at all, just copying.