[MXNET-696] Fix undefined variable errors (apache#11982)

* Fix undefined error in image segmentation

ctx is used undefined. Setting the default ctx to cpu and
editing the comment to let the user know that it can be
changed to GPU as required.

* Fix undefined names in SSD example

maskUtils is disabled. Remove code referencing it.
Initializing start_offset.

example/fcn-xs/image_segmentaion.py

@@ -93,8 +93,8 @@ def main():
     model_prefix = "FCN8s_VGG16"
     epoch = 19
 
-    # By default, MXNet will run on the CPU. Uncomment the line below to execute on the GPU
-    # ctx = mx.gpu()
+    # By default, MXNet will run on the CPU. Change to ctx = mx.gpu() to run on GPU.
+    ctx = mx.cpu()
 
     fcnxs, fcnxs_args, fcnxs_auxs = mx.model.load_checkpoint(model_prefix, epoch)
     fcnxs_args["data"] = mx.nd.array(get_data(args.input), ctx)

example/ssd/dataset/pycocotools/coco.py

@@ -255,22 +255,7 @@ def showAnns(self, anns):
                             color.append(c)
                     else:
                         # mask
-                        t = self.imgs[ann['image_id']]
-                        if type(ann['segmentation']['counts']) == list:
-                            # rle = maskUtils.frPyObjects([ann['segmentation']], t['height'], t['width'])
-                            raise NotImplementedError("maskUtils disabled!")
-                        else:
-                            rle = [ann['segmentation']]
-                        # m = maskUtils.decode(rle)
                         raise NotImplementedError("maskUtils disabled!")
-                        img = np.ones( (m.shape[0], m.shape[1], 3) )
-                        if ann['iscrowd'] == 1:
-                            color_mask = np.array([2.0,166.0,101.0])/255
-                        if ann['iscrowd'] == 0:
-                            color_mask = np.random.random((1, 3)).tolist()[0]
-                        for i in range(3):
-                            img[:,:,i] = color_mask[i]
-                        ax.imshow(np.dstack( (img, m*0.5) ))
                 if 'keypoints' in ann and type(ann['keypoints']) == list:
                     # turn skeleton into zero-based index
                     sks = np.array(self.loadCats(ann['category_id'])[0]['skeleton'])-1
@@ -430,6 +415,4 @@ def annToMask(self, ann):
         :return: binary mask (numpy 2D array)
         """
         rle = self.annToRLE(ann)
-        # m = maskUtils.decode(rle)
         raise NotImplementedError("maskUtils disabled!")
-        return m

example/ssd/symbol/common.py

@@ -206,6 +206,9 @@ def multibox_layer(from_layers, num_classes, sizes=[.2, .95],
          assert sizes[0] > 0 and sizes[0] < 1
          assert sizes[1] > 0 and sizes[1] < 1 and sizes[1] > sizes[0]
          tmp = np.linspace(sizes[0], sizes[1], num=(len(from_layers)-1))
+         # Ref for start_offset value:
+         # https://arxiv.org/abs/1512.02325
+         start_offset = 0.1
          min_sizes = [start_offset] + tmp.tolist()
          max_sizes = tmp.tolist() + [tmp[-1]+start_offset]
          sizes = zip(min_sizes, max_sizes)