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require 'csvigo'
require 'image'
local pl = require 'pl.import_into' ()
cv = require 'cv'
require 'cv.imgproc'
local utils = {}
function utils.project(transformation, points)
if points:dim() == 1 then
points = points:repeatTensor(1, 1)
end
points = torch.cat(points, torch.ones(points:size(1)), 2)
points2D = (transformation * points:transpose(1, 2)):transpose(1, 2)
points2D = torch.cdiv(points2D[{{}, {1, 2}}], points2D[{{}, {3}}]:expand(points2D:size(1), 2))
return points2D:squeeze()
end
function utils.loadPointCloud(filename)
local representationExists, representationInfo = pcall(function()
return csvigo.load({path=filename, mode="large", header=false, separator=' ', verbose=false})
end)
local points = {}
if representationExists and representationInfo ~= nil then
local numPoints = tonumber(representationInfo[1][3])
for pointIndex, point in pairs(representationInfo) do
if pointIndex >= 3 then
table.insert(points, {point[2], point[3], point[4]})
end
if pointIndex - 2 == numPoints then
break
end
end
end
return torch.Tensor(points)
end
function utils.drawTopDownView(width, height, points)
local X = points[{{}, 1}]
local Y = points[{{}, 2}]
local points2D = torch.cat(X, Y, 2)
local mean = torch.mean(points2D, 1)
points2D = points2D - mean:expandAs(points2D)
points2D:div(math.sqrt(points2D:size(1) - 1))
local indices = torch.randperm(points2D:size(1)):narrow(1, 1, 10000):long()
points2D = points2D:index(1, indices)
local w, _, _ = torch.svd(points2D:t())
local angle = torch.atan2(w[1][2], w[1][1])
local newX = X * torch.cos(angle) + Y * torch.sin(angle)
local newY = -X * torch.sin(angle) + Y * torch.cos(angle)
local newPoints2D = torch.cat(newX, newY, 2)
local mins = torch.min(newPoints2D, 1)[1]
local maxs = torch.max(newPoints2D, 1)[1]
local paddingRatio = 0.05
local padding = (maxs - mins) * paddingRatio
mins = mins - padding
maxs = maxs + padding
local u = torch.round((newX - mins[1]) / (maxs[1] - mins[1]) * width)
local v = torch.round((newY - mins[2]) / (maxs[2] - mins[2]) * height)
local uv = torch.cat(u, v, 2)
local transformation = torch.zeros(3, 4)
transformation[2][1] = torch.cos(angle)
transformation[2][2] = torch.sin(angle)
transformation[2][4] = -mins[1]
transformation[1][1] = -torch.sin(angle)
transformation[1][2] = torch.cos(angle)
transformation[1][4] = -mins[2]
transformation[3][4] = 1
transformation[2] = transformation[2] * width / (maxs[1] - mins[1])
transformation[1] = transformation[1] * height / (maxs[2] - mins[2])
--transformation[1], transformation[2] = transformation[2], transformation[1]
uv = utils.project(transformation, points)
print(transformation)
print(points[{{1, 5}}])
print(uv[{{1, 5}}])
local topDownView = torch.zeros(height, width)
for i = 1, uv:size(1) do
local point = uv[i]
topDownView[math.max(point[2], 1)][math.max(point[1], 1)] = topDownView[math.max(point[2], 1)][math.max(point[1], 1)] + 1
end
--image.save('test/pointcloud.png', topDownView)
local pointDensity = 10.0
topDownView = topDownView / pointDensity
topDownView[topDownView:gt(1)] = 1
return topDownView, transformation
end
return utils
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