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Code Issues Releases Wiki Activity

Fix a performance problem in resampling

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nagadomi 2016-05-30 19:15:54 +09:00
parent 70a2849e39
commit 70eb2b508f
3 changed files with 13 additions and 9 deletions
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6
lib/pairwise_transform_jpeg.lua
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@ -30,8 +30,12 @@ function pairwise_transform.jpeg_(src, quality, size, offset, n, options)
assert(x:size(1) == y:size(1) and x:size(2) == y:size(2) and x:size(3) == y:size(3))
local batch = {}
local lowres_y = gm.Image(y, "RGB", "DHW"):
size(y:size(3) * 0.5, y:size(2) * 0.5, "Box"):
size(y:size(3), y:size(2), "Box"):
toTensor(t, "RGB", "DHW")
for i = 1, n do
local xc, yc = pairwise_utils.active_cropping(x, y, size, 1,
local xc, yc = pairwise_utils.active_cropping(x, y, lowres_y, size, 1,
options.active_cropping_rate,
options.active_cropping_tries)
xc = iproc.byte2float(xc)

7
lib/pairwise_transform_scale.lua
View file

@ -1,5 +1,6 @@
local pairwise_utils = require 'pairwise_transform_utils'
local iproc = require 'iproc'
local gm = require 'graphicsmagick'
local pairwise_transform = {}
function pairwise_transform.scale(src, scale, size, offset, n, options)
@ -43,8 +44,12 @@ function pairwise_transform.scale(src, scale, size, offset, n, options)
assert(x:size(1) == y:size(1) and x:size(2) * scale == y:size(2) and x:size(3) * scale == y:size(3))
end
local batch = {}
local lowres_y = gm.Image(y, "RGB", "DHW"):
size(y:size(3) * 0.5, y:size(2) * 0.5, "Box"):
size(y:size(3), y:size(2), "Box"):
toTensor(t, "RGB", "DHW")
for i = 1, n do
local xc, yc = pairwise_utils.active_cropping(x, y,
local xc, yc = pairwise_utils.active_cropping(x, y, lowres_y,
size,
scale_inner,
options.active_cropping_rate,

9
lib/pairwise_transform_utils.lua
View file

@ -1,5 +1,4 @@
require 'image'
local gm = require 'graphicsmagick'
local iproc = require 'iproc'
local data_augmentation = require 'data_augmentation'
local pairwise_transform_utils = {}
@ -42,7 +41,7 @@ function pairwise_transform_utils.preprocess(src, crop_size, options)
return dest
end
function pairwise_transform_utils.active_cropping(x, y, size, scale, p, tries)
function pairwise_transform_utils.active_cropping(x, y, lowres_y, size, scale, p, tries)
assert("x:size == y:size", x:size(2) * scale == y:size(2) and x:size(3) * scale == y:size(3))
assert("crop_size % scale == 0", size % scale == 0)
local r = torch.uniform()
@ -57,10 +56,6 @@ function pairwise_transform_utils.active_cropping(x, y, size, scale, p, tries)
local xc = iproc.crop(x, xi, yi, xi + size / scale, yi + size / scale)
return xc, yc
else
local lowres = gm.Image(y, "RGB", "DHW"):
size(y:size(3) * 0.5, y:size(2) * 0.5, "Box"):
size(y:size(3), y:size(2), "Box"):
toTensor(t, "RGB", "DHW")
local best_se = 0.0
local best_xi, best_yi
local m = torch.FloatTensor(y:size(1), size, size)
@ -68,7 +63,7 @@ function pairwise_transform_utils.active_cropping(x, y, size, scale, p, tries)
local xi = torch.random(0, x:size(3) - (size + 1)) * scale
local yi = torch.random(0, x:size(2) - (size + 1)) * scale
local xc = iproc.crop(y, xi, yi, xi + size, yi + size)
local lc = iproc.crop(lowres, xi, yi, xi + size, yi + size)
local lc = iproc.crop(lowres_y, xi, yi, xi + size, yi + size)
local xcf = iproc.byte2float(xc)
local lcf = iproc.byte2float(lc)
local se = m:copy(xcf):add(-1.0, lcf):pow(2):sum()