Add files via upload

load_tracking_model.lua

@@ -0,0 +1,44 @@
+require 'torch'   -- torch
+require 'optim'
+require 'rnn'      -- provides a normalization operator
+
+function string:split(sep)
+  local sep, fields = sep, {}
+  local pattern = string.format("([^%s]+)", sep)
+  self:gsub(pattern, function(substr) fields[#fields + 1] = substr end)
+  return fields
+end
+
+local f_file = io.open(arg[1], 'r')
+local p_file = io.open(arg[2], 'w')
+local i = 0
+for line in f_file:lines('*l') do
+	i = i + 1
+end
+local data = torch.Tensor(i, 351)
+i = 0
+local names = {}
+local line_counter = 0
+local f_file = io.open(arg[1], 'r')
+for line in f_file:lines('*l') do
+	i = i+1
+	line_counter = line_counter+1
+	local l = line:split(',')
+	first = true
+	for key, val in ipairs(l) do
+	  if first == false then
+	  data[i][key] = val
+	  else data[i][key] = line_counter
+	  names[i] = val
+	  first = false
+	  end
+	end
+end
+local X = data[{{},{2,-1}}]
+model = torch.load('Tracking_model.dat')
+local myPrediction = model:forward(X)
+p_file:write('NAME,F1,F2,F3,F4\n')
+for p=1, (#myPrediction)[1] do
+	p_file:write(names[p]..','..tostring(myPrediction[p][1])..','..tostring(myPrediction[p][2])..','..tostring(myPrediction[p][3])..','..tostring(myPrediction[p][4])..'\n')
+
+end