nodes/cubiq-ComfyUI_essentials
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Support single image input for ImageBatchMultiple

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Signed-off-by: mymusise <mymusise1@gmail.com>
This commit is contained in:
mymusise
2024-06-26 15:36:07 +08:00
parent 4f2f11ca3c
commit 70841ac8d1
1 changed files with 12 additions and 9 deletions
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image.py
+12 -9
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@@ -55,9 +55,9 @@ class ImageBatchMultiple:
return {
"required": {
"image_1": ("IMAGE",),
"image_2": ("IMAGE",),
"method": (["nearest-exact", "bilinear", "area", "bicubic", "lanczos"], { "default": "lanczos" }),
}, "optional": {
"image_2": ("IMAGE",),
"image_3": ("IMAGE",),
"image_4": ("IMAGE",),
"image_5": ("IMAGE",),
@@ -67,25 +67,28 @@ class ImageBatchMultiple:
FUNCTION = "execute"
CATEGORY = "essentials/image batch"
def execute(self, image_1, image_2, method, image_3=None, image_4=None, image_5=None):
if image_1.shape[1:] != image_2.shape[1:]:
image_2 = comfy.utils.common_upscale(image_2.movedim(-1,1), image_1.shape[2], image_1.shape[1], method, "center").movedim(1,-1)
out = torch.cat((image_1, image_2), dim=0)
def execute(self, image_1, method, image_2=None, image_3=None, image_4=None, image_5=None):
images = [image_1]
if image_2 is not None:
if image_1.shape[1:] != image_2.shape[1:]:
image_2 = comfy.utils.common_upscale(image_2.movedim(-1,1), image_1.shape[2], image_1.shape[1], method, "center").movedim(1,-1)
images.append(image_2)
if image_3 is not None:
if image_1.shape[1:] != image_3.shape[1:]:
image_3 = comfy.utils.common_upscale(image_3.movedim(-1,1), image_1.shape[2], image_1.shape[1], method, "center").movedim(1,-1)
out = torch.cat((out, image_3), dim=0)
images.append(image_3)
if image_4 is not None:
if image_1.shape[1:] != image_4.shape[1:]:
image_4 = comfy.utils.common_upscale(image_4.movedim(-1,1), image_1.shape[2], image_1.shape[1], method, "center").movedim(1,-1)
out = torch.cat((out, image_4), dim=0)
images.append(image_4)
if image_5 is not None:
if image_1.shape[1:] != image_5.shape[1:]:
image_5 = comfy.utils.common_upscale(image_5.movedim(-1,1), image_1.shape[2], image_1.shape[1], method, "center").movedim(1,-1)
out = torch.cat((out, image_5), dim=0)
images.append(image_5)
return (out,)
out = torch.cat(images, dim=0)
return (out, )
class ImageExpandBatch: