exception handling in zmq. clip_by_shape for floatbox

tensorpack/dataflow/prefetch.py

@@ -198,7 +198,13 @@ class PrefetchDataZMQ(ProxyDataFlow):
         assert os.path.isdir(pipedir), pipedir
         self.pipename = "ipc://{}/dataflow-pipe-".format(pipedir.rstrip('/')) + str(uuid.uuid1())[:6]
         self.socket.set_hwm(self._hwm)
-        self.socket.bind(self.pipename)
+        try:
+            self.socket.bind(self.pipename)
+        except zmq.ZMQError:
+            logger.error(
+                "ZMQError in socket.bind(). Perhaps you're \
+                using pipes on a non-local file system. See documentation of PrefetchDataZMQ for more information.")
+            raise
 
         self.procs = [PrefetchProcessZMQ(self.ds, self.pipename, self._hwm)
                       for _ in range(self.nr_proc)]

tensorpack/utils/rect.py

@@ -85,36 +85,11 @@ class IntBox(BoxBase):
         assert self.is_valid_box(img.shape[:2]), "{} vs {}".format(self, img.shape[:2])
         return img[self.y1:self.y2 + 1, self.x1:self.x2 + 1]
 
-    # def expand(self, frac):
-    #     assert frac > 1.0, frac
-    #     neww = self.w * frac
-    #     newh = self.h * frac
-    #     newx = self.x - (neww - self.w) * 0.5
-    #     newy = self.y - (newh - self.h) * 0.5
-    #     return Rect(*(map(int, [newx, newy, neww, newh])), allow_neg=True)
-
-    # def roi_zeropad(self, img):
-    #     shp = list(img.shape)
-    #     shp[0] = self.h
-    #     shp[1] = self.w
-    #     ret = np.zeros(tuple(shp), dtype=img.dtype)
-
-    #     xstart = 0 if self.x >= 0 else -self.x
-    #     ystart = 0 if self.y >= 0 else -self.y
-
-    #     xmin = max(self.x0, 0)
-    #     ymin = max(self.y0, 0)
-    #     xmax = min(self.x1, img.shape[1])
-    #     ymax = min(self.y1, img.shape[0])
-    #     patch = img[ymin:ymax, xmin:xmax]
-    #     ret[ystart:ystart + patch.shape[0], xstart:xstart + patch.shape[1]] = patch
-    #     return ret
-
 
 class FloatBox(BoxBase):
     def __init__(self, x1, y1, x2, y2):
         for k in [x1, y1, x2, y2]:
-            assert isinstance(k, float)
+            assert isinstance(k, float), "type={},value={}".format(type(k), k)
         super(FloatBox, self).__init__(x1, y1, x2, y2)
 
     @property
@@ -130,9 +105,14 @@ class FloatBox(BoxBase):
         return FloatBox(intbox.x1, intbox.y1,
                         intbox.x2 + 1, intbox.y2 + 1)
 
+    def clip_by_shape(self, shape):
+        self.x1 = np.clip(self.x1, 0, shape[1])
+        self.x2 = np.clip(self.x2, 0, shape[1])
+        self.y1 = np.clip(self.y1, 0, shape[0])
+        self.y2 = np.clip(self.y2, 0, shape[0])
+
 
 if __name__ == '__main__':
     x = IntBox(2, 1, 3, 3)
-
     img = np.random.rand(3, 3)
     print(img)