diff --git a/freevideo_engine/geometry.py b/freevideo_engine/geometry.py
index d51a748f..e0cc0e37 100644
--- a/freevideo_engine/geometry.py
+++ b/freevideo_engine/geometry.py
@@ -5,8 +5,23 @@
 
 
 def geometry(width=1344, height=768, frames=None, seconds=None):
-    if any(not isinstance(n, int) or n < 256 or n % 32 for n in (width, height)):
-        raise ValueError('Width and height must be multiples of 32, at least 256 pixels.')
+    # Accept numpy integer types and integer-valued floats from upstream nodes,
+    # not only Python int; reject values that do not convert to a whole integer.
+    dims = []
+    for n in (width, height):
+        if isinstance(n, bool):
+            raise ValueError('Width and height must be multiples of 32, at least 256 pixels.')
+        # Normalize via float so strings ("640"), numpy integers and integer-valued
+        # floats all compare by numeric value rather than Python identity/type.
+        try:
+            f = float(n)
+        except (TypeError, ValueError):
+            raise ValueError('Width and height must be multiples of 32, at least 256 pixels.')
+        ni = int(f)
+        if f != ni or ni < 256 or ni % 32:
+            raise ValueError('Width and height must be multiples of 32, at least 256 pixels.')
+        dims.append(ni)
+    width, height = dims
     if frames is not None and seconds is not None:
         raise ValueError('Specify frames or seconds, not both.')
     if seconds is not None and (not math.isfinite(seconds) or seconds <= 0):
diff --git a/freevideo_engine/latent_upscale.py b/freevideo_engine/latent_upscale.py
index 7a71d346..1903d71d 100644
--- a/freevideo_engine/latent_upscale.py
+++ b/freevideo_engine/latent_upscale.py
@@ -33,8 +33,17 @@ def upscale(video, checkpoint, width, height, *, memory_saving=False):
     if (not isinstance(video, torch.Tensor) or video.ndim != 5 or tuple(video.shape[:2]) != (1,24)
             or not video.is_floating_point() or not bool(torch.isfinite(video).all())):
         raise ValueError('Latent upscaling requires finite batch-one, 24-channel video latents')
-    if any(type(value) is not int or value % 32 for value in (width,height)):
-        raise ValueError('Upscale target dimensions must be multiples of 32')
+    _dims = []
+    for value in (width, height):
+        try:
+            _f = float(value)
+        except (TypeError, ValueError):
+            raise ValueError('Upscale target dimensions must be multiples of 32')
+        _iv = int(_f)
+        if _f != _iv or _iv % 32:
+            raise ValueError('Upscale target dimensions must be multiples of 32')
+        _dims.append(_iv)
+    width, height = _dims
     source_h, source_w = video.shape[-2:]
     target_h, target_w = height//16, width//16
     if target_h < source_h or target_w < source_w or target_h*source_w != target_w*source_h: