minor changes

Author: chenliu-wustl

code/checkpoints.lua

@@ -14,14 +14,11 @@ function checkpoint.latest(opt)
 end
 
 function checkpoint.load(opt)
-   if opt.useCheckpoint == false then
-      return nil
-   end
    --print(opt.epochNumber)
-   local epoch = opt.epochNumber
-   if epoch == 0 then
+   local epoch = opt.useCheckpoint
+   if epoch == -1 then
       return nil
-   elseif epoch < 0 then
+   if epoch == 0 then
       -- finding the latest epoch, requiring 'latest.t7'
       return checkpoint.latest(opt)
    end

code/datasets/floorplan-representation.lua

@@ -12,11 +12,8 @@ local FloorplanDataset = torch.class('FloorplanDataset', M)
 function FloorplanDataset:__init(imageInfo, opt, split)
    self.imageInfo = imageInfo[split]
    if split == 'train' then
-      self.imageInfo.floorplanPaths = self.imageInfo.floorplanPaths:repeatTensor(opt.nRepetitionsPerEpochTrain, 1)            
-      self.imageInfo.representationPaths = self.imageInfo.representationPaths:repeatTensor(opt.nRepetitionsPerEpochTrain, 1)
-   else
-      self.imageInfo.floorplanPaths = self.imageInfo.floorplanPaths:repeatTensor(opt.nRepetitionsPerEpochTest, 1)      
-      self.imageInfo.representationPaths = self.imageInfo.representationPaths:repeatTensor(opt.nRepetitionsPerEpochTest, 1)
+      self.imageInfo.floorplanPaths = self.imageInfo.floorplanPaths:repeatTensor(opt.checkpointEpochInterval, 1)            
+      self.imageInfo.representationPaths = self.imageInfo.representationPaths:repeatTensor(opt.checkpointEpochInterval, 1)
    end
    self.opt = opt
    self.split = split

code/evaluate.lua

@@ -1,9 +1,9 @@
 package.path = '../util/lua/?.lua;' .. package.path
 local fp_ut = require 'floorplan_utils'
 
-dataPath = '../data/'
+local dataPath = '../data/'
 
-local imageInfo = csvigo.load({path=dataPath + '/test.txt', mode="large", header=false, separator='\t'})
+local imageInfo = csvigo.load({path=dataPath .. '/test.txt', mode="large", header=false, separator='\t'})
 
 local result = {}
 for _, mode in pairs({'Wall Junction', 'Door', 'Object', 'Room'}) do
@@ -19,11 +19,11 @@ local filenames = {}
 --local finalExamples = {1, 2, 4, 5, 6}
 --for _, i in pairs(finalExamples) do
 local results = {}
-for k, v in pairs(photo_info) do
+for k, v in pairs(imageInfo) do
    local floorplanFilename = dataPath .. v[1]
    local representationFilename = dataPath .. v[2]
 
-
+   
    representationPrediction = fp_ut.invertFloorplan(floorplan, false)
    local singleResult = fp_ut.evaluateResult(floorplan:size(3), floorplan:size(2), representationTarget, representationPrediction, {pointDistanceThreshold = 0.02, doorDistanceThreshold = 0.02, iconIOUThreshold = 0.5, segmentIOUThreshold = 0.7}, result)
    table.insert(results, singleResult)

code/models/heatmap-segmentation.lua

@@ -6,6 +6,13 @@ local nn = require 'nn'
 
 local function createModel(opt)
 
+   if opt.loadModel ~= '' then
+      local model = torch.load(opt.loadModel)
+      model:cuda()
+      print(model)      
+      return model
+   end
+   
    if opt.loadPoseEstimationModel ~= '' then
       local nOutput = 51 --This is slightly more than our final number of output channels. The actually used number of channels is 13 (wall corner) + 4 (opening corner) + 4 (icon corner) + 10 (opening/icon/empty segmentation) + 11 (wall/room segmentation)
 
@@ -33,12 +40,6 @@ local function createModel(opt)
       return model
    end
 
-   if opt.loadModel ~= '' then
-      local model = torch.load(opt.loadModel)
-      model:cuda()
-      print(model)      
-      return model
-   end
    assert(false, 'Please specify either opt.loadPoseEstimationModel or opt.loadModel')
 end
 

code/opts.lua

@@ -37,10 +37,8 @@ function M.parse(arg)
    cmd:option('-maskProb',         0.5,      'The probability of training masks')
    cmd:option('-IOUThreshold',         0.95,      'The probability of training masks')
    ------------- Training/testing options ----------
-   cmd:option('-nEpochs',         100,       'Number of total epochs to run')
-   cmd:option('-nRepetitionsPerEpochTrain',         10,       'Number of total epochs to run')
-   cmd:option('-nRepetitionsPerEpochTest',         10,       'Number of total epochs to run')
-   cmd:option('-epochNumber',     -1,        'Manual epoch number (useful on restarts)')
+   cmd:option('-nEpochs',         1000,       'Number of total epochs to run')
+   cmd:option('-checkpointEpochInterval',         1,       'Number of epochs between two saved checkpoints')
    cmd:option('-batchSize',       16,        'mini-batch size (1 = pure stochastic)')
    cmd:option('-valOnly',         false,     'Run on validation set only')
    cmd:option('-testOnly',        false,     'Run on validation set only')
@@ -65,7 +63,7 @@ function M.parse(arg)
    cmd:option('-segmentationDim',          500,       'Input dimensions')
    cmd:option('-retrain',      'none',   'Path to model to retrain with')
    cmd:option('-optimState',   'none',   'Path to an optimState to reload from')
-   cmd:option('-useCheckpoint',         true,      'Load checkpoint or not')
+   cmd:option('-useCheckpoint',         0,      'Load checkpoint or not')
    ------------- Other model options ---------------
    cmd:option('-nClasses',         13,      'The number of classes in the dataset')
    cmd:option('-nSegmentationClasses',         26,      'Number of classes of segmentation')   
@@ -87,7 +85,7 @@ function M.parse(arg)
    cmd:option('-resnetDepth', 34, 'ResNet depth')
    cmd:option('-weight_1', 3, 'Weight 1')
 
-   cmd:option('-loadModel',         '../checkpoint/model_best.t7',      'load trained model')
+   cmd:option('-loadModel',         '',      'load trained model')
    cmd:option('-loadPoseEstimationModel', '../PoseEstimation/human_pose_mpii.t7', 'load pretrained model')   
    ------------- pre-process options ---------------
    cmd:option('-scaleProb',         0.5,      'The probability of using scaling instead of random cropping')    

util/lua/ginit.lua

@@ -27,7 +27,7 @@ function ginit(opt)
 --  py = require 'fb.python'
 
   --gp = require 'gpath'
-  --ut = require 'utils'
+  ut = require 'utils'
   fp_ut = require 'floorplan_utils'
   --nnut = require 'nn_utils'
   --wut = require 'www_utils'