diff --git a/setup.py b/setup.py
index f7ac314..d18135e 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="stackview",
-    version="0.8.0",
+    version="0.8.1",
     author="Robert Haase",
     author_email="robert.haase@uni-leipzig.de",
     description="Interactive image stack viewing in jupyter notebooks",
diff --git a/stackview/__init__.py b/stackview/__init__.py
index 2228465..8bed0a0 100644
--- a/stackview/__init__.py
+++ b/stackview/__init__.py
@@ -1,4 +1,4 @@
-__version__ = "0.8.0"
+__version__ = "0.8.1"
 
 from ._static_view import jupyter_displayable_output, insight
 from ._utilities import merge_rgb
diff --git a/stackview/_animate.py b/stackview/_animate.py
index 538bdfd..9dddb1a 100644
--- a/stackview/_animate.py
+++ b/stackview/_animate.py
@@ -35,6 +35,9 @@ def animate(timelapse, filename:str=None, overwrite_file:bool=True, frame_delay_
     from stackview._image_widget import _img_to_rgb
     from ._utilities import numpy_to_gif_bytestream, _gif_to_html
 
+    if isinstance(timelapse, list):
+        timelapse = np.asarray(timelapse)
+
     if 0 <= timelapse.min() <= 1 and 0 <= timelapse.max() <= 1:
         warnings.warn("The timelapse has a small intensity range between 0 and 1. Consider normalizing it to the range between 0 and 255.")
     if timelapse.min() < 0 or timelapse.max() > 255:
@@ -115,6 +118,13 @@ def animate_curtain(timelapse, timelapse_curtain,
     import numpy as np
     from ._image_widget import _img_to_rgb
 
+
+    if isinstance(timelapse, list):
+        timelapse = np.asarray(timelapse)
+
+    if isinstance(timelapse_curtain, list):
+        timelapse_curtain = np.asarray(timelapse_curtain)
+
     max_size = timelapse.shape[1]
 
     images = []
diff --git a/stackview/_image_widget.py b/stackview/_image_widget.py
index a65f05c..5d911fd 100644
--- a/stackview/_image_widget.py
+++ b/stackview/_image_widget.py
@@ -72,7 +72,7 @@ def _img_to_rgb(image,
                 display_max=None):
     from ._colormaps import _labels_lut, create_colormap
 
-    if len(image.shape) > 2 and image.shape[-1] == 3:
+    if len(image.shape) > 2 and (image.shape[-1] == 3 or image.shape[-1] == 4):
         return image
 
     if image.dtype == bool: