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fix output bug of ImageScaleByAspectRatio

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chflame
2024-04-25 11:11:56 +08:00
parent 346de14872
commit bb9d40dcf2
2 changed files with 12 additions and 12 deletions
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py/image_scale_by_aspect_ratio.py
+6 -6
View File
@@ -65,14 +65,14 @@ class ImageScaleByAspectRatio:
_width, _height = tensor2pil(orig_masks[0]).size
if (orig_width > 0 and orig_width != _width) or (orig_height > 0 and orig_height != _height):
log(f"Error: {NODE_NAME} skipped, because the mask is does'nt match image.", message_type='error')
return (None, None,)
return (None, None, None)
elif orig_width + orig_height == 0:
orig_width = _width
orig_height = _height
if orig_width + orig_height == 0:
log(f"Error: {NODE_NAME} skipped, because the image or mask at least one must be input.", message_type='error')
return (None, None,)
return (None, None, None)
if aspect_ratio == 'original':
ratio = orig_width / orig_height
@@ -137,16 +137,16 @@ class ImageScaleByAspectRatio:
ret_masks.append(image2mask(_mask))
if len(ret_images) > 0 and len(ret_masks) >0:
log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
elif len(ret_images) > 0 and len(ret_masks) == 0:
log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0), None,)
return (torch.cat(ret_images, dim=0), None,[orig_width, orig_height],)
elif len(ret_images) == 0 and len(ret_masks) > 0:
log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
return (None, torch.cat(ret_masks, dim=0),)
return (None, torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
else:
log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
return (None, None,)
return (None, None, None)
NODE_CLASS_MAPPINGS = {
"LayerUtility: ImageScaleByAspectRatio": ImageScaleByAspectRatio
py/image_scale_by_aspect_ratio_v2.py
+6 -6
View File
@@ -65,14 +65,14 @@ class ImageScaleByAspectRatioV2:
_width, _height = tensor2pil(orig_masks[0]).size
if (orig_width > 0 and orig_width != _width) or (orig_height > 0 and orig_height != _height):
log(f"Error: {NODE_NAME} skipped, because the mask is does'nt match image.", message_type='error')
return (None, None,)
return (None, None, None)
elif orig_width + orig_height == 0:
orig_width = _width
orig_height = _height
if orig_width + orig_height == 0:
log(f"Error: {NODE_NAME} skipped, because the image or mask at least one must be input.", message_type='error')
return (None, None,)
return (None, None, None)
if aspect_ratio == 'original':
ratio = orig_width / orig_height
@@ -136,16 +136,16 @@ class ImageScaleByAspectRatioV2:
ret_masks.append(image2mask(_mask))
if len(ret_images) > 0 and len(ret_masks) >0:
log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
elif len(ret_images) > 0 and len(ret_masks) == 0:
log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0), None,)
return (torch.cat(ret_images, dim=0), None, [orig_width, orig_height],)
elif len(ret_images) == 0 and len(ret_masks) > 0:
log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
return (None, torch.cat(ret_masks, dim=0),)
return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
else:
log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
return (None, None,)
return (None, None, None)
NODE_CLASS_MAPPINGS = {
"LayerUtility: ImageScaleByAspectRatio V2": ImageScaleByAspectRatioV2