Replace paths.dofile() with require

BatchROISampler.lua

@@ -6,8 +6,7 @@
 
 
 require 'xlua'
---local utils = require 'fastrcnn.utils'
-local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
+local utils = require 'fastrcnn.utils'
 
 if not fastrcnn then fastrcnn = {} end
 

ImageDetector.lua

@@ -3,8 +3,7 @@
 ]]
 
 
---local utils = require 'fastrcnn.utils'
-local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
+local utils = require 'fastrcnn.utils'
 
 if not fastrcnn then fastrcnn = {} end
 

ROIProcessor.lua

@@ -3,9 +3,7 @@
 ]]
 
 
---local box = require 'fastrcnn.utils.box'
---local boxoverlap = box.boxoverlap
-local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
+local utils = require 'fastrcnn.utils'
 local boxoverlap = utils.box.boxoverlap
 
 if not fastrcnn then fastrcnn = {} end

Tester.lua

@@ -5,10 +5,8 @@
 
 local tds = require 'tds'
 local xlua = require 'xlua'
---local eval = require 'fastrcnn.eval'
---local utils = require 'fastrcnn.utils'
-local eval = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/eval/init.lua')
-local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
+local eval = require 'fastrcnn.eval'
+local utils = require 'fastrcnn.utils'
 
 if not fastrcnn then fastrcnn = {} end
 
@@ -208,14 +206,6 @@ function Tester:test()
     local raw_bbox_pred = tds.hash()
 
     local aboxes
-    --self.cache_filename = '/home/mf/Toolkits/Codigo/git/fastrcnn-example/data/cache.t7'
-    --self.cache_filename = '/home/mf/Toolkits/Codigo/git/pedestrian_detector/data/exp/caltech/alexnet_vanilla_frcnn/cache.t7'
-    --if paths.filep(self.cache_filename) then
-    --   print('Load test cache from file: ' .. self.cache_filename)
-    --   aboxes = torch.load(self.cache_filename)
-    --else
-
-
 
     if self.progressbar then xlua.progress(0, self.nFiles) end
     for ifile = 1, self.nFiles do
@@ -233,10 +223,6 @@ function Tester:test()
 
     collectgarbage()
 
-    --print('Save test cache to file: ' .. self.cache_filename)
-    --torch.save(self.cache_filename, aboxes)
-    --end
-
     return self:computeAP(aboxes)
 end
 

eval/coco_eval.lua

@@ -5,8 +5,7 @@
 
 require 'xlua'
 require 'json'
---local coco_eval_python = require 'fastrcnn.eval.coco'
-local coco_eval_python = paths.dofile('coco.lua')
+local coco_eval_python = require 'fastrcnn.eval.coco'
 
 ------------------------------------------------------------------------------------------------------------
 

eval/init.lua

@@ -3,8 +3,6 @@
 ]]
 
 return{
-    coco = paths.dofile('coco_eval.lua'),
-    pascal = paths.dofile('pascal_eval.lua'),
-    --coco = require 'fastrcnn.eval.coco_eval',
-    --pascal = require 'fastrcnn.eval.pascal_eval'
+    coco = require 'fastrcnn.eval.coco_eval',
+    pascal = require 'fastrcnn.eval.pascal_eval'
 }

eval/pascal_eval.lua

@@ -3,10 +3,8 @@
 ]]
 
 
---local box = require 'fastrcnn.utils.box'
---local boxoverlap = box.boxoverlap
-local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
-local boxoverlap = utils.box.boxoverlap
+local box = require 'fastrcnn.utils.box'
+local boxoverlap = box.boxoverlap
 
 
 ---------------------------------------------------------------------------------------------------------------------

init.lua

@@ -16,7 +16,7 @@ require 'cudnn'
 require 'inn'
 
 fastrcnn = {}
---[[
+
 require 'fastrcnn.modules'         -- bbox modules for train/test
 require 'fastrcnn.BatchROISampler' -- data loader/generator
 require 'fastrcnn.ImageDetector'   -- single image detector/tester
@@ -30,20 +30,5 @@ fastrcnn.train = require 'fastrcnn.train'
 fastrcnn.test = require 'fastrcnn.test'
 fastrcnn.utils = require 'fastrcnn.utils'
 fastrcnn.visualize_detections = require 'fastrcnn.visualize'
-]]
-
-paths.dofile('modules/init.lua')    -- bbox modules for train/test
-paths.dofile('BatchROISampler.lua') -- data loader/generator
-paths.dofile('ImageDetector.lua')   -- single image detector/tester
-paths.dofile('Tester.lua')          -- dataset tester
-paths.dofile('Options.lua')         -- Fast-RCNN options parser
-paths.dofile('ROIProcessor.lua')
-paths.dofile('Transform.lua')
-
--- load setup/options functions
-fastrcnn.train = paths.dofile('train.lua')
-fastrcnn.test = paths.dofile('test.lua')
-fastrcnn.utils = paths.dofile('utils/init.lua')
-fastrcnn.visualize_detections = paths.dofile('visualize.lua')
 
 return fastrcnn

modules/init.lua

@@ -1,8 +1,4 @@
 require 'nn'
-paths.dofile('BBoxNorm.lua')
-paths.dofile('BBoxRegressionCriterion.lua')
-paths.dofile('NoBackprop.lua')
-
---require 'fastrcnn.modules.BBoxNorm'
---require 'fastrcnn.modules.BBoxRegressionCriterion'
---require 'fastrcnn.modules.NoBackprop'
+require 'fastrcnn.modules.BBoxNorm'
+require 'fastrcnn.modules.BBoxRegressionCriterion'
+require 'fastrcnn.modules.NoBackprop'

train.lua

@@ -27,7 +27,6 @@
 --]]
 
 
---local function train(dataLoadTable, rois, model, modelParameters, opts)
 local function train(data_gen, rois, model, modelParameters, opts)
 
     assert(data_gen, 'Invalid input: dataLoadTable')
@@ -36,17 +35,15 @@ local function train(data_gen, rois, model, modelParameters, opts)
     assert(modelParameters, 'Invalid input: modelParameters')
 
     local tnt = require 'torchnet'
-    --local utils = require 'fastrcnn.utils'
-    local utils = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/init.lua')
+    local utils = require 'fastrcnn.utils'
     local modelStorageFn = utils.model.storeModel
 
 
     --------------------------------------------------------------------------------
     -- Load configs (data, model, criterion, optimState)
     --------------------------------------------------------------------------------
 
-    local configs = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/configs.lua')
-    --local configs = require 'fastrcnn.configs'
+    local configs = require 'fastrcnn.configs'
     local dataLoadTable = data_gen()
     local opt, modelOut, criterion, optimStateFn, nEpochs = configs(model, dataLoadTable, rois, modelParameters, opts or {})
     local lopt = opt
@@ -57,65 +54,14 @@ local function train(data_gen, rois, model, modelParameters, opts)
 
     -- set number of iterations
     local nItersTrain = opt.trainIters
-    local nItersTest
-    if dataLoadTable.test then
-        nItersTest = dataLoadTable.test.nfiles/opt.frcnn_imgs_per_batch
-    end
+    local nItersTest = opt.trainIters
 
     -- classes
     local classes = utils.table.concatTables({'background'}, dataLoadTable.train.classLabel)
 
     -- convert modules to a specified tensor type
     local function cast(x) return x:type(opt.dataType) end
 
---[[
-    local function getIterator_test(mode)
-       return tnt.ParallelDatasetIterator{
-          nthread = opt.nThreads,
-          init    = function(threadid)
-             require 'torch'
-             require 'torchnet'
-             opt = lopt
-             paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/init.lua')
-             torch.manualSeed(threadid+opt.manualSeed)
-          end,
-          closure = function()
-
-              -- data loader/generator
-              local data_loader = data_gen()
-              local batchprovider = fastrcnn.BatchROISampler(data_loader[mode], rois[mode], modelParameters, opt, mode)
-
-              -- number of iterations per epoch
-              local nIters = data_loader[mode].nfiles
-
-              -- setup dataset iterator
-              local list_dataset = tnt.ListDataset{
-                  list = torch.range(1, nIters):long(),
-                  load = function(idx)
-                      return batchprovider:getSample(idx)
-                  end
-              }
-              return list_dataset
-          end,
-       }
-    end
-
-    for _, mode in pairs({'train', 'test'}) do
-        print('Starting mode: ', mode)
-        local iter = getIterator_test(mode)
-        local idx = 1
-        local data_loader = data_gen()
-        local nfiles = data_loader[mode].nfiles
-        for saple in iter() do
-            xlua.progress(idx, nfiles)
-            idx = idx + 1
-        end
-    end
-
-    os.exit()
---]]
-
-
 
     --------------------------------------------------------------------------------
     -- Setup data generator
@@ -127,11 +73,8 @@ local function train(data_gen, rois, model, modelParameters, opts)
           init    = function(threadid)
              require 'torch'
              require 'torchnet'
+             require 'fastrcnn'
              opt = lopt
-             --require 'fastrcnn.BatchROISampler'
-             paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/init.lua')
-             --paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/BatchROISampler.lua')
-             --paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/ROIProcessor.lua')
              torch.manualSeed(threadid+opt.manualSeed)
           end,
           closure = function()

utils/box.lua

@@ -3,8 +3,7 @@
 ]]
 
 
---local utils_table = require 'fastrcnn.utils.table'
-local utils_table = paths.dofile('/home/mf/Toolkits/Codigo/git/fastrcnn/utils/table.lua')
+local utils_table = require 'fastrcnn.utils.table'
 
 
 ------------------------------------------------------------------------------------------------------------

utils/init.lua

@@ -3,6 +3,8 @@
 ]]
 
 
+------------------------------------------------------------------------------------------------------------
+
 local function logical2ind(logical)
     if logical:numel() == 0 then
         return torch.LongTensor()
@@ -58,24 +60,19 @@ end
 
 return {
     -- model utility functions
-    model = paths.dofile('model.lua'),
-    --model = require 'fastrcnn.utils.model',
+    model = require 'fastrcnn.utils.model',
 
     -- non-maximum suppression
-    nms = paths.dofile('nms.lua'),
-    --nms = require 'fastrcnn.utils.nms',
+    nms = require 'fastrcnn.utils.nms',
 
     -- bounding box overlap
-    box = paths.dofile('box.lua'),
-    --box = require 'fastrcnn.utils.box',
+    box = require 'fastrcnn.utils.box',
 
     -- table functions
-    table = paths.dofile('table.lua'),
-    --table = require 'fastrcnn.utils.table',
+    table = require 'fastrcnn.utils.table',
 
     -- load matlab files
-    load = paths.dofile('load.lua'),
-    --load = require 'fastrcnn.utils.load',
+    load = require 'fastrcnn.utils.load',
 
     -- other functions
     logical2ind = logical2ind,

utils/model.lua

@@ -3,6 +3,10 @@
 ]]
 
 
+require 'nn'
+
+------------------------------------------------------------------------------------------------------------
+
 local function MSRinit(model)
     for k,v in pairs(model:findModules('nn.SpatialConvolution')) do
         local n = v.kW*v.kH*v.nOutputPlane

utils/nms.lua

@@ -9,8 +9,7 @@ void bbox_vote(THFloatTensor *res, THFloatTensor *nms_boxes, THFloatTensor *scor
 void NMS(THFloatTensor *keep, THFloatTensor *scored_boxes, float overlap);
 ]]
 
---local ok, C = pcall(ffi.load, package.searchpath('libfastrcnn', package.cpath))
-local ok, C = pcall(ffi.load, '/home/mf/Toolkits/Codigo/git/fastrcnn/lib/libnms.so')
+local ok, C = pcall(ffi.load, package.searchpath('libfastrcnn', package.cpath))
 assert(ok, 'Installation went wrong when compiling the C code.')
 
 ------------------------------------------------------------------------------------------------------------

visualize.lua

@@ -2,8 +2,7 @@
     Visualize detections using a GUI window (requires qlua/qt).
 ]]
 
---local nms = require 'fastrcnn.utils.nms'
-local nms = paths.dofile('utils/nms.lua')
+local nms = require 'fastrcnn.utils.nms'
 
 ---------------------------------------------------------------------------------------------------------------------