rename xmap to xmap_readers and remove 'from cv2 import resize' in image.py

Author: wanghaoshuang

python/paddle/v2/dataset/flowers.py

@@ -105,7 +105,8 @@ def reader():
  for sample, label in itertools.izip(data, batch['label']):
  yield sample, int(label)
 
- return paddle.reader.xmap(mapper, reader, cpu_count(), buffered_size)
+ return paddle.reader.xmap_readers(mapper, reader,
+ cpu_count(), buffered_size)
 
 
 def train(mapper=default_mapper, buffered_size=1024):

python/paddle/v2/image.py

@@ -3,8 +3,6 @@
  import cv2
 except ImportError:
  cv2 = None
-
-from cv2 import resize
 import os
 import tarfile
 import cPickle
@@ -164,7 +162,7 @@ def resize_short(im, size):
  h_new = size * h / w
  else:
  w_new = size * w / h
- im = resize(im, (h_new, w_new), interpolation=cv2.INTER_CUBIC)
+ im = cv2.resize(im, (h_new, w_new), interpolation=cv2.INTER_CUBIC)
  return im
 
 

python/paddle/v2/reader/decorator.py

@@ -14,7 +14,7 @@
 
 __all__ = [
  'map_readers', 'buffered', 'compose', 'chain', 'shuffle',
- 'ComposeNotAligned', 'firstn', 'xmap'
+ 'ComposeNotAligned', 'firstn', 'xmap_readers'
 ]
 
 import itertools
@@ -230,7 +230,7 @@ class XmapEndSignal():
  pass
 
 
-def xmap(mapper, reader, process_num, buffer_size):
+def xmap_readers(mapper, reader, process_num, buffer_size):
  """
  Use multiprocess to map samples from reader by a mapper defined by user.
  And this function contains a buffered decorator.