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Fix shorter/longer edge resize for square images

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This commit is contained in:
Nicolas Stepien 2026-01-27 19:03:43 +00:00
parent 09725967cf
commit 46e6d07cfd
1 changed files with 10 additions and 2 deletions
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12
comfy_extras/nodes_dataset.py
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@ -644,9 +644,13 @@ class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
if w < h: if w < h:
new_w = shorter_edge new_w = shorter_edge
new_h = int(h * (shorter_edge / w)) new_h = int(h * (shorter_edge / w))
else: elif h < w:
new_h = shorter_edge new_h = shorter_edge
new_w = int(w * (shorter_edge / h)) new_w = int(w * (shorter_edge / h))
else:
# Square image: set both dimensions directly to avoid precision loss from float operations
new_w = shorter_edge
new_h = shorter_edge
img = img.resize((new_w, new_h), Image.Resampling.LANCZOS) img = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
return pil_to_tensor(img) return pil_to_tensor(img)
@ -674,9 +678,13 @@ class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
if w > h: if w > h:
new_w = longer_edge new_w = longer_edge
new_h = int(h * (longer_edge / w)) new_h = int(h * (longer_edge / w))
else: elif h > w:
new_h = longer_edge new_h = longer_edge
new_w = int(w * (longer_edge / h)) new_w = int(w * (longer_edge / h))
else:
# Square image: set both dimensions directly to avoid precision loss from float operations
new_w = longer_edge
new_h = longer_edge
img = img.resize((new_w, new_h), Image.Resampling.LANCZOS) img = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
resized_images.append(pil_to_tensor(img)) resized_images.append(pil_to_tensor(img))
return torch.cat(resized_images, dim=0) return torch.cat(resized_images, dim=0)