support int in add_moving_summary.

tensorpack/dataflow/image.py

@@ -94,6 +94,7 @@ class AugmentImageComponent(MapDataComponent):
 class AugmentImageCoordinates(MapData):
     """
     Apply image augmentors on an image and a list of coordinates.
+    Coordinates must be a Nx2 floating point array, each row is (x, y).
     """
     def __init__(self, ds, augmentors, img_index=0, coords_index=1, copy=True):
         """
@@ -116,6 +117,9 @@ class AugmentImageCoordinates(MapData):
         def func(dp):
             try:
                 img, coords = dp[img_index], dp[coords_index]
+                assert coords.ndim == 2, coords.ndim
+                assert coords.shape[1] == 2, coords.shape
+                assert np.issubdtype(coords.dtype, np.float), coords.dtype
                 if copy:
                     img, coords = copy_mod.deepcopy((img, coords))
                 img, prms = self.augs._augment_return_params(img)

tensorpack/dataflow/imgaug/noname.py

@@ -30,7 +30,7 @@ class Flip(ImageAugmentor):
         elif vert:
             self.code = 0
         else:
-            raise ValueError("Are you kidding?")
+            raise ValueError("At least one of horiz or vert has to be True!")
         self.prob = prob
         self._init()
 

tensorpack/tfutils/summary.py

@@ -197,6 +197,8 @@ def add_moving_summary(*args, **kwargs):
     for c in v:
         name = re.sub('tower[0-9]+/', '', c.op.name)
         with G.colocate_with(c), tf.name_scope(None):
+            if not c.dtype.is_floating:
+                c = tf.cast(c, tf.float32)
             # assign_moving_average creates variables with op names, therefore clear ns first.
             with _enter_vs_reuse_ns('EMA') as vs:
                 ema_var = tf.get_variable(name, shape=c.shape, dtype=c.dtype,