FRCNN.lua

local FRCNN = torch.class('nnf.FRCNN')

function FRCNN:__init(dataset)
  self.dataset = dataset
  
  self.scale = {600}
  self.max_dim = 1000
  self.randomscale = true
  
  --self.sz_conv_standard = 13
  self.step_standard = 16
  --self.offset0 = 21
  --self.offset = 6.5
  
  --self.inputArea = 224^2
 
end

function FRCNN:getScale(I)
  local min_size = math.min(I[2],I[3])
  local max_size = math.max(I[2],I[3])
  local scale
  if max_size <= self.max_dim then
    scale = self.scale[1]/min_size
  else
    scale = self.max_dim/max_size
  end
  return scale
end

function FRCNN:projectBBoxes(bboxes,scale)
  return (bboxes-1)*scale+1
end

function FRCNN:getFeatures(i,flip)
  local I = self.dataset:getImage(i)
  local bboxes = self.dataset:attachProposals(i)
  I = prepareImage(I)
  if flip then
    
  end
end