add openface scripts

batch-represent/batch-represent.lua

@@ -0,0 +1,77 @@
+local ffi = require 'ffi'
+
+local batchNumber, nImgs = 0
+
+torch.setdefaulttensortype('torch.FloatTensor')
+
+function batchRepresent()
+   local loadSize   = {3, opt.imgDim, opt.imgDim}
+   print(opt.data)
+   local cacheFile = paths.concat(opt.data, 'cache.t7')
+   print('cache lotation: ', cacheFile)
+   local dumpLoader
+   if paths.filep(cacheFile) then
+      print('Loading metadata from cache.')
+      print('If your dataset has changed, delete the cache file.')
+      dumpLoader = torch.load(cacheFile)
+   else
+      print('Creating metadata for cache.')
+      dumpLoader = dataLoader{
+         paths = {opt.data},
+         loadSize = loadSize,
+         sampleSize = loadSize,
+         split = 0,
+         verbose = true
+      }
+      torch.save(cacheFile, dumpLoader)
+   end
+   collectgarbage()
+   nImgs = dumpLoader:sizeTest()
+   print('nImgs: ', nImgs)
+   assert(nImgs > 0, "Failed to get nImgs")
+
+   batchNumber = 0
+
+   for i=1,math.ceil(nImgs/opt.batchSize) do
+      local indexStart = (i-1) * opt.batchSize + 1
+      local indexEnd = math.min(nImgs, indexStart + opt.batchSize - 1)
+      local batchSz = indexEnd-indexStart+1
+      local inputs, labels = dumpLoader:get(indexStart, indexEnd)
+      local paths = {}
+      for j=indexStart,indexEnd do
+         table.insert(paths,
+                      ffi.string(dumpLoader.imagePath[dumpLoader.testIndices[j]]:data()))
+      end
+      repBatch(paths, inputs, labels, batchSz)
+      if i % 5 == 0 then
+         collectgarbage()
+      end
+   end
+
+   if opt.cuda then
+      cutorch.synchronize()
+   end
+end
+
+function repBatch(paths, inputs, labels, batchSz)
+   batchNumber = batchNumber + batchSz
+
+   if opt.cuda then
+      inputs = inputs:cuda()
+   end
+   local embeddings = model:forward(inputs):float()
+   if opt.cuda then
+      cutorch.synchronize()
+   end
+
+   if batchSz == 1 then
+      embeddings = embeddings:reshape(1, embeddings:size(1))
+   end
+
+   for i=1,batchSz do
+      labelsCSV:write({labels[i], paths[i]})
+      repsCSV:write(embeddings[i]:totable())
+   end
+
+   print(('Represent: %d/%d'):format(batchNumber, nImgs))
+end