Fix wrong print statements

stardist/stardist_impl/train_stardist_2d.py

@@ -48,7 +48,7 @@ def load_training_data(root, image_folder, labels_folder, ext, multichannel):
     train_images.sort()
 
     label_pattern = os.path.join(root, labels_folder, f'*{ext}')
-    print("Looking for labels with the pattern", image_pattern)
+    print("Looking for labels with the pattern", label_pattern)
     train_labels = glob(label_pattern)
     assert len(train_labels) > 0, "Did not find any labels"
     train_labels.sort()
@@ -166,7 +166,7 @@ def train_stardist_model(root, model_save_path, image_folder, labels_folder, ext
     print("Made train validation split with validation fraction",
           validation_fraction, "resulting in")
     print(len(x_train), "training images")
-    print(len(y_train), "validation images")
+    print(len(x_val), "validation images")
 
     print("Start model training ...")
     print("You can connect to the tensorboard by typing 'tensorboaed --logdir=.' in the folder where the training runs")

stardist/stardist_impl/train_stardist_3d.py

@@ -36,7 +36,7 @@ def load_training_data(root, image_folder, labels_folder, ext):
     train_images.sort()
 
     label_pattern = os.path.join(root, labels_folder, f'*{ext}')
-    print("Looking for labels with the pattern", image_pattern)
+    print("Looking for labels with the pattern", label_pattern)
     train_labels = glob(label_pattern)
     assert len(train_labels) > 0, "Did not find any labels"
     train_labels.sort()
@@ -162,7 +162,7 @@ def train_stardist_model(root, model_save_path, image_folder, labels_folder, ext
 
     print("Made train validation split with validation fraction", validation_fraction, "resulting in")
     print(len(x_train), "training images")
-    print(len(y_train), "validation images")
+    print(len(x_val), "validation images")
 
     print("Start model training ...")
     print("You can connect to the tensorboard by typing 'tensorboaed --logdir=.' in the folder where the training runs")
@@ -188,7 +188,7 @@ def main():
                         help="The fraction of available data that is used for validation, default: .1")
     parser.add_argument('--patch_size', type=int, nargs=3, default=[128, 128, 128],
                         help="Size of the image patches used to train the network, default: 128, 128, 128")
-    aniso_help = """Anisotropy factor, needs to be passed as json encoded list, e.g. \"[.05,0.5,0.5]\".
+    aniso_help = """Anisotropy factor, needs to be passed as json encoded list, e.g. \"[1.0,1.0,0.5]\".
                     If not given, will be computed from the dimensions of the input data, default: None"""
     parser.add_argument('--anisotropy', type=str, default=None, help=aniso_help)