convert scripts

diff --git a/src/caffe/pyutil/convert.py b/src/caffe/pyutil/convert.py
index 56650c6c734976a09963cf3ccd726446f12b294f..efcea42e8cc45021bbe43889ea0db39fab87102d 100644 (file)
--- a/src/caffe/pyutil/convert.py
+++ b/src/caffe/pyutil/convert.py
@@ -12,7 +12,17 @@ def blobproto_to_array(blob):
 def array_to_blobproto(arr):
   if arr.ndim != 4:
     raise ValueError('Incorrect array shape.')
-  blob = caffe_pb2.Blob()
+  blob = caffe_pb2.BlobProto()
   blob.num, blob.channels, blob.height, blob.width = arr.shape;
   blob.data.extend(arr.flat)
-  return blob
\ No newline at end of file
+  return blob
+
+def array_to_datum(arr):
+  if arr.ndim != 3:
+    raise ValueError('Incorrect array shape.')
+  if arr.dtype != np.uint8:
+    raise TypeError('Input array has to be of type uint8.')
+  datum = caffe_pb2.Datum()
+  datum.channels, datum.height, datum.width = arr.shape
+  datum.data = arr.tostring()
+  return datum

diff --git a/src/caffe/pyutil/convert_ilsvrc.py b/src/caffe/pyutil/convert_ilsvrc.py
deleted file mode 100644 (file)
index c494c01..0000000
--- a/src/caffe/pyutil/convert_ilsvrc.py
+++ /dev/null
@@ -1,63 +0,0 @@
-"""This script converts images stored in the ILSVRC format to a leveldb,
-converting every image to a 256*256 image as well as converting them to channel
-first storage. The output will be shuffled - so that a sequential read will
-result in pseudo-random minibatches.
-"""
-
-from decaf import util
-from decaf.util import transform
-import glob
-import leveldb
-import numpy as np
-import random
-import os
-from skimage import io
-import sys
-
-from caffe.proto import caffe_pb2
-
-def main(argv):
-  root = argv[0]
-  db_name = argv[1]
-  db = leveldb.LevelDB(db_name)
-  synsets = glob.glob(os.path.join(root, "n????????"))
-  synsets.sort()
-  print 'A total of %d synsets' % len(synsets)
-  all_files = [glob.glob(os.path.join(root, synset, "*.JPEG"))
-      for synset in synsets]
-  all_labels = [[i] * len(files) for i, files in enumerate(all_files)]
-  all_files = sum(all_files, [])
-  all_labels = sum(all_labels, [])
-  print 'A total of %d files' % len(all_files)
-  random_indices = list(range(len(all_files)))
-  random.shuffle(random_indices)
-  datum = caffe_pb2.Datum()
-  datum.blob.num = 1
-  datum.blob.channels = 3
-  datum.blob.height = 256
-  datum.blob.width = 256
-  my_timer = util.Timer()
-  batch = leveldb.WriteBatch()
-  for i in range(len(all_files))[:1281]:
-    filename = all_files[random_indices[i]]
-    basename = os.path.basename(filename)
-    label = all_labels[random_indices[i]]
-    image = io.imread(filename)
-    image = transform.scale_and_extract(transform.as_rgb(image), 256)
-    image = np.ascontiguousarray(image.swapaxes(1,2).swapaxes(0,1))
-    del datum.blob.data[:]
-    datum.blob.data.extend(list(image.flatten()))
-    datum.label = label
-    batch.Put('%d_%d_%s' % (i, label, basename),
-        datum.SerializeToString())
-    print '(%d %s) Wrote file %s' % (i, my_timer.total(), basename)
-    if (i % 256 and i > 0):
-      # write and start a new batch
-      db.Write(batch)
-      batch = leveldb.WriteBatch()
-
-if __name__ == '__main__':
-  if len(sys.argv) != 3:
-    print 'Usage: convert_ilsvrc.py DATA_ROOT OUTPUT_DB'
-  else:
-    main(sys.argv[1:])
\ No newline at end of file