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fix(LoadImage): ignore broken MPO frames after first decoded image #11565

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fix(LoadImage): ignore broken MPO frames after first decoded image #11565

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48 changes: 26 additions & 22 deletions nodes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1665,32 +1665,36 @@ def load_image(self, image):

excluded_formats = ['MPO']

for i in ImageSequence.Iterator(img):
i = node_helpers.pillow(ImageOps.exif_transpose, i)
try:
for i in ImageSequence.Iterator(img):
i = node_helpers.pillow(ImageOps.exif_transpose, i)

if i.mode == 'I':
i = i.point(lambda i: i * (1 / 255))
image = i.convert("RGB")
if i.mode == 'I':
i = i.point(lambda i: i * (1 / 255))
image = i.convert("RGB")

if len(output_images) == 0:
w = image.size[0]
h = image.size[1]
if len(output_images) == 0:
w = image.size[0]
h = image.size[1]

if image.size[0] != w or image.size[1] != h:
continue
if image.size[0] != w or image.size[1] != h:
continue

image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
if 'A' in i.getbands():
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
elif i.mode == 'P' and 'transparency' in i.info:
mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
else:
mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
output_images.append(image)
output_masks.append(mask.unsqueeze(0))
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
if 'A' in i.getbands():
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
elif i.mode == 'P' and 'transparency' in i.info:
mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
else:
mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
output_images.append(image)
output_masks.append(mask.unsqueeze(0))
except ValueError:
if img.format != "MPO" or len(output_images) == 0:
raise

if len(output_images) > 1 and img.format not in excluded_formats:
output_image = torch.cat(output_images, dim=0)
Expand Down