diff --git a/object-locator/logger.py b/object-locator/logger.py
index 0d22d9d..224e5f6 100644
--- a/object-locator/logger.py
+++ b/object-locator/logger.py
@@ -94,23 +94,23 @@ def train_losses(self, terms, iteration_number, terms_legends=None):
                                            xlabel='Epoch'),
                                  win='train_losses')
 
-    def image(self, imgs, titles, windows):
+    def image(self, imgs, titles, window_ids):
         """Send images to Visdom.
         Each image will be shown in a different window/plot.
 
         :param imgs: List of numpy images.
         :param titles: List of titles of each image.
-        :param windows: List of window names.
+        :param window_ids: List of window IDs.
         """
 
         # Watchdog
-        if not(len(imgs) == len(titles) == len(windows)):
+        if not(len(imgs) == len(titles) == len(window_ids)):
             raise ValueError('The number of "imgs", "titles" and '
-                             '"windows" must be equal, got '
+                             '"window_ids" must be equal, got '
                              '%s, %s and %s, respectively'
-                             % (len(imgs), len(titles), len(windows)))
+                             % (len(imgs), len(titles), len(window_ids)))
 
-        for img, title, win in zip(imgs, titles, windows):
+        for img, title, win in zip(imgs, titles, window_ids):
             self.client.image(img,
                               opts=dict(title=title),
                               win=str(win))
diff --git a/object-locator/train.py b/object-locator/train.py
index d2693d7..9838b35 100644
--- a/object-locator/train.py
+++ b/object-locator/train.py
@@ -237,7 +237,7 @@
             log.image(imgs=[orig_img_origsize, est_map_origsize],
                       titles=['(Training) Input',
                               '(Training) U-Net output'],
-                      windows=[1, 2])
+                      window_ids=[1, 2])
 
             # # Read image with GT dots from disk
             # gt_img_numpy = skimage.io.imread(
@@ -375,7 +375,7 @@
             log.image(imgs=[orig_img_origsize, est_map_origsize],
                       titles=['(Validation) Input',
                               '(Validation) U-Net output'],
-                      windows=[5, 6])
+                      window_ids=[5, 6])
 
             # # Read image with GT dots from disk
             # gt_img_numpy = skimage.io.imread(
@@ -401,7 +401,7 @@
                 log.image(imgs=[np.moveaxis(image_with_x, 2, 0)],
                           titles=[
                               '(Validation) Estimated centers @ crossings'],
-                          windows=[8])
+                          window_ids=[8])
 
     avg_term1_val = sum_term1 / len(valset_loader)
     avg_term2_val = sum_term2 / len(valset_loader)