/
utils.lua
163 lines (141 loc) · 5.12 KB
/
utils.lua
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-------------------------------------------------------------------------------
-- Coordinate transformation
-------------------------------------------------------------------------------
function getTransform(center, scale, rot, res)
local h = 200 * scale
local t = torch.eye(3)
-- Scaling
t[1][1] = res / h
t[2][2] = res / h
-- Translation
t[1][3] = res * (-center[1] / h + .5)
t[2][3] = res * (-center[2] / h + .5)
-- Rotation
if rot ~= 0 then
rot = -rot
local r = torch.eye(3)
local ang = rot * math.pi / 180
local s = math.sin(ang)
local c = math.cos(ang)
r[1][1] = c
r[1][2] = -s
r[2][1] = s
r[2][2] = c
-- Need to make sure rotation is around center
local t_ = torch.eye(3)
t_[1][3] = -res/2
t_[2][3] = -res/2
local t_inv = torch.eye(3)
t_inv[1][3] = res/2
t_inv[2][3] = res/2
t = t_inv * r * t_ * t
end
return t
end
function transform(pt, center, scale, rot, res, invert)
local pt_ = torch.ones(3)
pt_[1],pt_[2] = pt[1]-1,pt[2]-1
local t = getTransform(center, scale, rot, res)
if invert then
t = torch.inverse(t)
end
local new_point = (t*pt_):sub(1,2):add(1e-4)
return new_point:int():add(1)
end
function crop(img, center, scale, rot, res)
local ul = transform({1,1}, center, scale, 0, res, true)
local br = transform({res+1,res+1}, center, scale, 0, res, true)
local pad = math.floor(torch.norm((ul - br):float())/2 - (br[1]-ul[1])/2)
if rot ~= 0 then
ul = ul - pad
br = br + pad
end
local newDim,newImg,ht,wd
if img:size():size() > 2 then
newDim = torch.IntTensor({img:size(1), br[2] - ul[2], br[1] - ul[1]})
newImg = torch.zeros(newDim[1],newDim[2],newDim[3])
ht = img:size(2)
wd = img:size(3)
else
newDim = torch.IntTensor({br[2] - ul[2], br[1] - ul[1]})
newImg = torch.zeros(newDim[1],newDim[2])
ht = img:size(1)
wd = img:size(2)
end
local newX = torch.Tensor({math.max(1, -ul[1] + 2), math.min(br[1], wd+1) - ul[1]})
local newY = torch.Tensor({math.max(1, -ul[2] + 2), math.min(br[2], ht+1) - ul[2]})
local oldX = torch.Tensor({math.max(1, ul[1]), math.min(br[1], wd+1) - 1})
local oldY = torch.Tensor({math.max(1, ul[2]), math.min(br[2], ht+1) - 1})
if newDim:size(1) > 2 then
newImg:sub(1,newDim[1],newY[1],newY[2],newX[1],newX[2]):copy(img:sub(1,newDim[1],oldY[1],oldY[2],oldX[1],oldX[2]))
else
newImg:sub(newY[1],newY[2],newX[1],newX[2]):copy(img:sub(oldY[1],oldY[2],oldX[1],oldX[2]))
end
if rot ~= 0 then
newImg = image.rotate(newImg, rot * math.pi / 180, 'bilinear')
if newDim:size(1) > 2 then
newImg = newImg:sub(1,newDim[1],pad,newDim[2]-pad,pad,newDim[3]-pad)
else
newImg = newImg:sub(pad,newDim[1]-pad,pad,newDim[2]-pad)
end
end
newImg = image.scale(newImg,res,res)
return newImg
end
local magic_gaussian = image.gaussian(7)
function drawGaussian(img, pt, sigma)
-- Check if the gaussian is in-bounds
local ul = {math.floor(pt[1] - 3 * sigma), math.floor(pt[2] - 3 * sigma)}
local br = {math.floor(pt[1] + 3 * sigma), math.floor(pt[2] + 3 * sigma)}
-- return the image otherwise
if (ul[1] > img:size(2) or ul[2] > img:size(1) or br[1] < 1 or br[2] < 1) then return img end
-- Generate gaussian
local size = 6 * sigma + 1
-- Avoid the need of generating the gaussian for each sample
local g = magic_gaussian:clone()--image.gaussian(size) -- , 1 / size, 1)
-- Usable gaussian range
local g_x = {math.max(1, -ul[1]), math.min(br[1], img:size(2)) - math.max(1, ul[1]) + math.max(1, -ul[1])}
local g_y = {math.max(1, -ul[2]), math.min(br[2], img:size(1)) - math.max(1, ul[2]) + math.max(1, -ul[2])}
-- Image range
local img_x = {math.max(1, ul[1]), math.min(br[1], img:size(2))}
local img_y = {math.max(1, ul[2]), math.min(br[2], img:size(1))}
assert(g_x[1] > 0 and g_y[1] > 0)
img:sub(img_y[1], img_y[2], img_x[1], img_x[2]):add(g:sub(g_y[1], g_y[2], g_x[1], g_x[2]))
img[img:gt(1)] = 1
return img
end
function shuffleLR(x)
local dim
if x:nDimension() == 4 then
dim = 2
else
assert(x:nDimension() == 3)
dim = 1
end
-- Keypoints pairs for 300W_LP, 300VW, 300W and LS3D-W datasets
local matchedParts = {
{1,17}, {2,16}, {3,15},
{4,14}, {5,13}, {6,12}, {7,11}, {8,10},
{18,27},{19,26},{20,25},{21,24},{22,23},
{37,46},{38,45},{39,44},{40,43},
{42,47},{41,48},
{32,36},{33,35},
{51,53},{50,54},{49,55},{62,64},{61,65},{68,66},{60,56},
{59,57}
}
for i = 1,#matchedParts do
local idx1, idx2 = unpack(matchedParts[i])
local tmp = x:narrow(dim, idx1, 1):clone()
x:narrow(dim, idx1, 1):copy(x:narrow(dim, idx2, 1))
x:narrow(dim, idx2, 1):copy(tmp)
end
return x
end
function flip(x)
require 'image'
local y = torch.FloatTensor(x:size())
for i = 1, x:size(1) do
image.hflip(y[i], x[i]:float())
end
return y:typeAs(x)
end