Fix handling detections that return no masks.

mrcnn/model.py

@@ -2418,7 +2418,7 @@ def unmold_detections(self, detections, mrcnn_mask, original_image_shape,
             full_mask = utils.unmold_mask(masks[i], boxes[i], original_image_shape)
             full_masks.append(full_mask)
         full_masks = np.stack(full_masks, axis=-1)\
-            if full_masks else np.empty((0,) + masks.shape[1:3])
+            if full_masks else np.empty(masks.shape[1:3] + (0,))
 
         return boxes, class_ids, scores, full_masks
 

samples/nucleus/nucleus.py

@@ -335,6 +335,9 @@ def rle_decode(rle, shape):
 def mask_to_rle(image_id, mask, scores):
     "Encodes instance masks to submission format."
     assert mask.ndim == 3, "Mask must be [H, W, count]"
+    # If mask is empty, return line with image ID only
+    if mask.shape[-1] == 0:
+        return "{},".format(image_id)
     # Remove mask overlaps
     # Multiply each instance mask by its score order
     # then take the maximum across the last dimension