removed obsolete scripts

diff --git a/python/caffe/imagenet/script_reshape_imagenet_imgs.py b/python/caffe/imagenet/script_reshape_imagenet_imgs.py
deleted file mode 100644 (file)
index ac8c9a5..0000000
--- a/python/caffe/imagenet/script_reshape_imagenet_imgs.py
+++ /dev/null
@@ -1,41 +0,0 @@
-from mincepie import mapreducer, launcher
-import gflags
-import glob
-import os
-
-gflags.DEFINE_string("input_folder", "",
-                     "The folder that contains all input folders")
-gflags.DEFINE_string("output_folder", "",
-                     "The folder that we write output images to")
-gflags.DEFINE_bool("subfolder", True,
-                   "If subfolder is true, the input key is a subfolder"
-                   " instead of a file name (like in ILSVRC train).")
-gflags.DEFINE_string("ext", "JPEG", "The image extension.")
-FLAGS = gflags.FLAGS
-
-class ConvertMapper(mapreducer.BasicMapper):
-    """The ImageNet Compute mapper. The input value would be a synset name.
-    """
-    def map(self, key, value):
-        if FLAGS.subfolder:
-            files = glob.glob(os.path.join(FLAGS.input_folder, value, '*.' + FLAGS.ext))
-            try:
-                os.makedirs(os.path.join(FLAGS.output_folder, value))
-            except OSError:
-                pass
-            for file in files:
-                os.system('convert %s -resize 256x256\\! %s' %
-                    (file, os.path.join(FLAGS.output_folder, value, os.path.basename(file))))
-        else:
-            os.system('convert %s -resize 256x256\\! %s' %
-                    (os.path.join(FLAGS.input_folder, value),
-                     os.path.join(FLAGS.output_folder, value)))
-        yield value, 'done'
-
-mapreducer.REGISTER_DEFAULT_MAPPER(ConvertMapper)
-mapreducer.REGISTER_DEFAULT_REDUCER(mapreducer.IdentityReducer)
-mapreducer.REGISTER_DEFAULT_READER(mapreducer.FileReader)
-mapreducer.REGISTER_DEFAULT_WRITER(mapreducer.FileWriter)
-
-if __name__ == "__main__":
-    launcher.launch()

diff --git a/python/caffe/imagenet/script_write_leveldb.py b/python/caffe/imagenet/script_write_leveldb.py
deleted file mode 100644 (file)
index e4f11e9..0000000
--- a/python/caffe/imagenet/script_write_leveldb.py
+++ /dev/null
@@ -1,70 +0,0 @@
-"""Writes to a leveldb from a bunch of files.
-
-This program converts a set of images to a leveldb by storing them as Datum
-proto buffers. The input file should be a list of files as well as their labels,
-in the format of
-    file1.JPEG 0
-    file2.JPEG 1
-    ....
-For the leveldb, the keys will be a monotonically increasing id followed by the
-filename. If --shuffle, we will shuffle the lines before writing to leveldb,
-which will make a random order easier for training.
-
-To make the output consistent with the C++ code, we will store the images in
-BGR format.
-
-Copyright 2013 Yangqing Jia
-"""
-
-import gflags
-import leveldb
-import numpy as np
-import os
-import random
-from skimage import io
-import sys
-
-from caffe.pyutil import convert
-
-BATCH_SIZE=256
-
-gflags.DEFINE_string("filename", "", "The input file name.")
-gflags.DEFINE_string("input_folder", "", "The input folder that stores images.")
-gflags.DEFINE_string("db_name", "", "The output leveldb name.")
-gflags.DEFINE_bool("shuffle", False,
-    "If True, shuffle the lines before writing.")
-FLAGS = gflags.FLAGS
-
-def write_db():
-  """The main script to write the leveldb database."""
-  db = leveldb.LevelDB(FLAGS.db_name, write_buffer_size=268435456,
-      create_if_missing=True, error_if_exists=True)
-  lines = [line.strip() for line in open(FLAGS.filename)]
-  if FLAGS.shuffle:
-    random.shuffle(lines)
-  total = len(lines)
-  key_format = '%%0%dd_%%s' % len(str(total))
-  batch = leveldb.WriteBatch()
-  for line_id, line in enumerate(lines):
-    imagename, label = line.split(' ')
-    label = int(label)
-    img = io.imread(os.path.join(FLAGS.input_folder, imagename))
-    if img.ndim == 2:
-      img = np.tile(img, (1,1,3))
-    # convert to BGR, and then swap the axes.
-    img = img[::-1].swapaxes(1,2).swapaxes(0,1)
-    datum = convert.array_to_datum(img, label=label)
-    batch.Put(key_format % (line_id, imagename), datum.SerializeToString())
-    if line_id > 0 and line_id % 1000 == 0:
-      print '%d of %d done.' % (line_id, total)
-    if line_id > 0 and line_id % BATCH_SIZE == 0:
-      # Write the current batch and start a new batch.
-      db.Write(batch)
-      batch = leveldb.WriteBatch()
-  # finishing the job.
-  del db
-  return
-
-if __name__ == '__main__':
-  FLAGS(sys.argv)
-  write_db()