bugfix in ResizeShortestEdge.

tensorpack/dataflow/common.py

@@ -5,6 +5,7 @@
 from __future__ import division
 import numpy as np
 from copy import copy
+import pprint
 from termcolor import colored
 from collections import deque, defaultdict
 from six.moves import range, map
@@ -136,8 +137,11 @@ class BatchData(ProxyDataFlow):
                         np.asarray([x[k] for x in data_holder], dtype=tp))
                 except KeyboardInterrupt:
                     raise
-                except:
+                except Exception as e:  # noqa
                     logger.exception("Cannot batch data. Perhaps they are of inconsistent shape?")
+                    if isinstance(dt, np.ndarray):
+                        s = pprint.pformat([x[k].shape for x in data_holder])
+                        logger.error("Shape of all arrays to be batched: " + s)
                     try:
                         # open an ipython shell if possible
                         import IPython as IP; IP.embed()    # noqa

tensorpack/dataflow/imgaug/noname.py

@@ -101,13 +101,16 @@ class ResizeShortestEdge(ImageAugmentor):
         Args:
             size (int): the size to resize the shortest edge to.
         """
-        size = size * 1.0
+        size = int(size)
         self._init(locals())
 
     def _get_augment_params(self, img):
         h, w = img.shape[:2]
-        scale = self.size / min(h, w)
-        newh, neww = map(int, [scale * h, scale * w])
+        scale = self.size * 1.0 / min(h, w)
+        if h < w:
+            newh, neww = self.size, int(scale * w)
+        else:
+            newh, neww = int(scale * h), self.size
         return (h, w, newh, neww)
 
     def _augment(self, img, param):